Ce Zhang - RankMe

364 papers A* 73A 12B 9Misc 3Journal 210Unranked 53

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Not All Prefills Are Equal: PPD Disaggregation for Multi-turn LLM Serving. CoRR Zongze Li, Jingyu Liu, Zach Xu, Yineng Zhang, Tahseen Rabbani, Ce Zhang
2026	J	`jnl`	TablePuppet: Towards a Generic Framework for Learning over Relational Tables. VLDB J. Lijie Xu, Chulin Xie, Yiran Guo, Haiyang Lu, Gustavo Alonso, Bo Li, Guoliang Li, Wei Wang, Wentao Wu, Ce Zhang
2026	J	`jnl`	When RL Meets Adaptive Speculative Training: A Unified Training-Serving System. CoRR Junxiong Wang, Fengxiang Bie, Jisen Li, Zhongzhu Zhou, Zelei Shao, Yubo Wang, Yinghui Liu, Qingyang Wu, Avner May, Sri Yanamandra, Yineng Zhang, Ce Zhang, Tri Dao, Percy Liang, Ben Athiwaratkun, Shuaiwen Leon Song, Chenfeng Xu, Xiaoxia Wu
2025	J	`jnl`	Beat the long tail: Distribution-Aware Speculative Decoding for RL Training. CoRR Zelei Shao, Vikranth Srivatsa, Sanjana Srivastava, Qingyang Wu, Alpay Ariyak, Xiaoxia Wu, Ameen Patel, Jue Wang, Percy Liang, Tri Dao, Ce Zhang, Yiying Zhang, Ben Athiwaratkun, Chenfeng Xu, Junxiong Wang
2025	J	`jnl`	Data Diversification Methods In Alignment Enhance Math Performance In LLMs. CoRR Berkan Dokmeci, Qingyang Wu, Ben Athiwaratkun, Ce Zhang, Shuaiwen Leon Song, James Zou
2025	J	`jnl`	HAMburger: Accelerating LLM Inference via Token Smashing. CoRR Jingyu Liu, Ce Zhang
2025	J	`jnl`	Hold Onto That Thought: Assessing KV Cache Compression On Reasoning. CoRR Minghui Liu, Aadi Palnitkar, Tahseen Rabbani, Hyunwoo Jae, Kyle Rui Sang, Dixi Yao, Shayan Shabihi, Fuheng Zhao, Tian Li, Ce Zhang, Furong Huang, Kunpeng Zhang
2025	J	`jnl`	Improving Model Alignment Through Collective Intelligence of Open-Source LLMS. CoRR Junlin Wang, Roy Xie, Shang Zhu, Jue Wang, Ben Athiwaratkun, Bhuwan Dhingra, Shuaiwen Leon Song, Ce Zhang, James Zou
2025	A*	`conf`	Improving Model Alignment Through Collective Intelligence of Open-Source Models. ICML Junlin Wang, Roy Xie, Shang Zhu, Jue Wang, Ben Athiwaratkun, Bhuwan Dhingra, Shuaiwen Leon Song, Ce Zhang, James Zou
2025	A*	`conf`	MLKV: Efficiently Scaling up Large Embedding Model Training with Disk-based Key-Value Storage. ICDE Yongjun He, Roger Waleffe, Zhichao Han, Johnu George, Binhang Yuan, Zitao Zhang, Yinan Shan, Yang Zhao, Debojyoti Dutta, Theodoros Rekatsinas, Ce Zhang
2025	J	`jnl`	MLKV: Efficiently Scaling up Large Embedding Model Training with Disk-based Key-Value Storage. CoRR Yongjun He, Roger Waleffe, Zhichao Han, Johnu George, Binhang Yuan, Zitao Zhang, Yinan Shan, Yang Zhao, Debojyoti Dutta, Theodoros Rekatsinas, Ce Zhang
2025	A*	`conf`	Mixture-of-Agents Enhances Large Language Model Capabilities. ICLR Junlin Wang, Jue Wang, Ben Athiwaratkun, Ce Zhang, James Zou
2025	J	`jnl`	Scaling Instruction-Tuned LLMs to Million-Token Contexts via Hierarchical Synthetic Data Generation. CoRR Linda He, Jue Wang, Maurice Weber, Shang Zhu, Ben Athiwaratkun, Ce Zhang
2025	A*	`conf`	Scaling Instruction-tuned LLMs to Million-token Contexts via Hierarchical Synthetic Data Generation. ICLR Linda He, Jue Wang, Maurice Weber, Shang Zhu, Ben Athiwaratkun, Ce Zhang
2025	A*	`conf`	Speculative Prefill: Turbocharging TTFT with Lightweight and Training-Free Token Importance Estimation. ICML Jingyu Liu, Beidi Chen, Ce Zhang
2025	J	`jnl`	Speculative Prefill: Turbocharging TTFT with Lightweight and Training-Free Token Importance Estimation. CoRR Jingyu Liu, Beidi Chen, Ce Zhang
2025	J	`jnl`	Staircase Streaming for Low-Latency Multi-Agent Inference. CoRR Junlin Wang, Jue Wang, Zhen Xu, Ben Athiwaratkun, Bhuwan Dhingra, Ce Zhang, James Zou
2025	J	`jnl`	Think Deep, Think Fast: Investigating Efficiency of Verifier-free Inference-time-scaling Methods. CoRR Junlin Wang, Shang Zhu, Jon Saad-Falcon, Ben Athiwaratkun, Qingyang Wu, Jue Wang, Shuaiwen Leon Song, Ce Zhang, Bhuwan Dhingra, James Zou
2025	J	`jnl`	TiDAR: Think in Diffusion, Talk in Autoregression. CoRR Jingyu Liu, Xin Dong, Zhifan Ye, Rishabh Mehta, Yonggan Fu, Vartika Singh, Jan Kautz, Ce Zhang, Pavlo Molchanov
2025	J	`jnl`	When Does Divide and Conquer Work for Long Context LLM? A Noise Decomposition Framework. CoRR Zhen Xu, Shang Zhu, Jue Wang, Junlin Wang, Ben Athiwaratkun, Chi Wang, James Zou, Ce Zhang
2024	J	`jnl`	A systematic evaluation of machine learning on serverless infrastructure. VLDB J. Jiawei Jiang, Shaoduo Gan, Bo Du, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Sheng Wang, Ce Zhang
2024	J	`jnl`	Analysis of Distributed Optimization Algorithms on a Real Processing-In-Memory System. CoRR Steve Rhyner, Haocong Luo, Juan Gómez-Luna, Mohammad Sadrosadati, Jiawei Jiang, Ataberk Olgun, Harshita Gupta, Ce Zhang, Onur Mutlu
2024	J	`jnl`	BgGPT 1.0: Extending English-centric LLMs to other languages. CoRR Anton Alexandrov, Veselin Raychev, Dimitar I. Dimitrov, Ce Zhang, Martin T. Vechev, Kristina Toutanova
2024	J	`jnl`	DMLR: Data-centric Machine Learning Research - Past, Present and Future. J. Data-centric Mach. Learn. Res. Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G. Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson
2024	A*	`conf`	Data Debugging with Shapley Importance over Machine Learning Pipelines. ICLR Bojan Karlas, David Dao, Matteo Interlandi, Sebastian Schelter, Wentao Wu, Ce Zhang
2024	A*	`conf`	Effective and Efficient Federated Tree Learning on Hybrid Data. ICLR Qinbin Li, Chulin Xie, Xiaojun Xu, Xiaoyuan Liu, Ce Zhang, Bo Li, Bingsheng He, Dawn Song
2024	J	`jnl`	How good are machine learning clouds? Benchmarking two snapshots over 5 years. VLDB J. Jiawei Jiang, Yi Wei, Yu Liu, Wentao Wu, Chuang Hu, Zhigao Zheng, Ziyi Zhang, Yingxia Shao, Ce Zhang
2024	—	`conf`	Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM. SaTML Chulin Xie, Pin-Yu Chen, Qinbin Li, Arash Nourian, Ce Zhang, Bo Li
2024	—	`conf`	MS MARCO Web Search: A Large-scale Information-rich Web Dataset with Millions of Real Click Labels. WWW (Companion Volume) Qi Chen, Xiubo Geng, Corby Rosset, Carolyn Buractaon, Jingwen Lu, Tao Shen, Kun Zhou, Chenyan Xiong, Yeyun Gong, Paul N. Bennett, Nick Craswell, Xing Xie, Fan Yang, Bryan Tower, Nikhil Rao, Anlei Dong, Wenqi Jiang, Zheng Liu, Mingqin Li, Chuanjie Liu, Zengzhong Li, Rangan Majumder, Jennifer Neville, Andy Oakley, Knut Magne Risvik, Harsha Vardhan Simhadri, Manik Varma, Yujing Wang, Linjun Yang, Mao Yang, Ce Zhang
2024	J	`jnl`	MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels. CoRR Qi Chen, Xiubo Geng, Corby Rosset, Carolyn Buractaon, Jingwen Lu, Tao Shen, Kun Zhou, Chenyan Xiong, Yeyun Gong, Paul N. Bennett, Nick Craswell, Xing Xie, Fan Yang, Bryan Tower, Nikhil Rao, Anlei Dong, Wenqi Jiang, Zheng Liu, Mingqin Li, Chuanjie Liu, Zengzhong Li, Rangan Majumder, Jennifer Neville, Andy Oakley, Knut Magne Risvik, Harsha Vardhan Simhadri, Manik Varma, Yujing Wang, Linjun Yang, Mao Yang, Ce Zhang
2024	A*	`conf`	Mechanistic Design and Scaling of Hybrid Architectures. ICML Michael Poli, Armin W. Thomas, Eric Nguyen, Pragaash Ponnusamy, Björn Deiseroth, Kristian Kersting, Taiji Suzuki, Brian L. Hie, Stefano Ermon, Christopher Ré, Ce Zhang, Stefano Massaroli
2024	J	`jnl`	Mechanistic Design and Scaling of Hybrid Architectures. CoRR Michael Poli, Armin W. Thomas, Eric Nguyen, Pragaash Ponnusamy, Björn Deiseroth, Kristian Kersting, Taiji Suzuki, Brian L. Hie, Stefano Ermon, Christopher Ré, Ce Zhang, Stefano Massaroli
2024	—	`conf`	Mitigating Catastrophic Forgetting in Language Transfer via Model Merging. EMNLP (Findings) Anton Alexandrov, Veselin Raychev, Mark Niklas Müller, Ce Zhang, Martin T. Vechev, Kristina Toutanova
2024	J	`jnl`	Mitigating Catastrophic Forgetting in Language Transfer via Model Merging. CoRR Anton Alexandrov, Veselin Raychev, Mark Niklas Müller, Ce Zhang, Martin T. Vechev, Kristina Toutanova
2024	J	`jnl`	Mixture-of-Agents Enhances Large Language Model Capabilities. CoRR Junlin Wang, Jue Wang, Ben Athiwaratkun, Ce Zhang, James Zou
2024	A*	`conf`	OAM-TCD: A globally diverse dataset of high-resolution tree cover maps. NeurIPS Josh Veitch-Michaelis, Andrew Cottam, Daniella Schweizer, Eben N. Broadbent, David Dao, Ce Zhang, Angelica M. Almeyda Zambrano, Simeon Max
2024	J	`jnl`	OAM-TCD: A globally diverse dataset of high-resolution tree cover maps. CoRR Josh Veitch-Michaelis, Andrew Cottam, Daniella Schweizer, Eben N. Broadbent, David Dao, Ce Zhang, Angelica M. Almeyda Zambrano, Simeon Max
2024	J	`jnl`	OpenBox: A Python Toolkit for Generalized Black-box Optimization. J. Mach. Learn. Res. Huaijun Jiang, Yu Shen, Yang Li, Beicheng Xu, Sixian Du, Wentao Zhang, Ce Zhang, Bin Cui
2024	B	`conf`	PIM-Opt: Demystifying Distributed Optimization Algorithms on a Real-World Processing-In-Memory System. PACT Steve Rhyner, Haocong Luo, Juan Gómez-Luna, Mohammad Sadrosadati, Jiawei Jiang, Ataberk Olgun, Harshita Gupta, Ce Zhang, Onur Mutlu
2024	J	`jnl`	Red Onions, Soft Cheese and Data: From Food Safety to Data Traceability for Responsible AI. IEEE Data Eng. Bull. Stefan Grafberger, Zeyu Zhang, Sebastian Schelter, Ce Zhang
2024	A*	`conf`	RedPajama: an Open Dataset for Training Large Language Models. NeurIPS Maurice Weber, Daniel Y. Fu, Quentin Anthony, Yonatan Oren, Shane Adams, Anton Alexandrov, Xiaozhong Lyu, Huu Nguyen, Xiaozhe Yao, Virginia Adams, Ben Athiwaratkun, Rahul Chalamala, Kezhen Chen, Max Ryabinin, Tri Dao, Percy Liang, Christopher Ré, Irina Rish, Ce Zhang
2024	J	`jnl`	RedPajama: an Open Dataset for Training Large Language Models. CoRR Maurice Weber, Daniel Y. Fu, Quentin Anthony, Yonatan Oren, Shane Adams, Anton Alexandrov, Xiaozhong Lyu, Huu Nguyen, Xiaozhe Yao, Virginia Adams, Ben Athiwaratkun, Rahul Chalamala, Kezhen Chen, Max Ryabinin, Tri Dao, Percy Liang, Christopher Ré, Irina Rish, Ce Zhang
2024	J	`jnl`	Semantic-Enhanced Indirect Call Analysis with Large Language Models. CoRR Baijun Cheng, Ce Zhang, Kailong Wang, Ling Shi, Yang Liu, Haoyu Wang, Yao Guo, Xiangqun Chen
2024	J	`jnl`	Stochastic gradient descent without full data shuffle: with applications to in-database machine learning and deep learning systems. VLDB J. Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang
2024	J	`jnl`	TablePuppet: A Generic Framework for Relational Federated Learning. CoRR Lijie Xu, Chulin Xie, Yiran Guo, Gustavo Alonso, Bo Li, Guoliang Li, Wei Wang, Wentao Wu, Ce Zhang
2023	A*	`conf`	Automatic Feasibility Study via Data Quality Analysis for ML: A Case-Study on Label Noise. ICDE Cédric Renggli, Luka Rimanic, Luka Kolar, Wentao Wu, Ce Zhang
2023	J	`jnl`	BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks. CoRR Qiang Huang, Jiawei Jiang, Susie Xi Rao, Ce Zhang, Zhichao Han, Zitao Zhang, Xin Wang, Yongjun He, Quanqing Xu, Yang Zhao, Chuang Hu, Shuo Shang, Bo Du
2023	—	`ed.`	Benchmarking, Measuring, and Optimizing - 14th BenchCouncil International Symposium, Bench 2022, Virtual Event, November 7-9, 2022, Revised Selected Papers Bench Ana Gainaru, Ce Zhang, Chunjie Luo
2023	—	`conf`	CARE: Certifiably Robust Learning with Reasoning via Variational Inference. SaTML Jiawei Zhang, Linyi Li, Ce Zhang, Bo Li
2023	A*	`conf`	CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks. ICML Jue Wang, Yucheng Lu, Binhang Yuan, Beidi Chen, Percy Liang, Christopher De Sa, Christopher Ré, Ce Zhang
2023	A*	`conf`	Contrastive Learning for Unsupervised Domain Adaptation of Time Series. ICLR Yilmazcan Özyurt, Stefan Feuerriegel, Ce Zhang
2023	J	`jnl`	Convolution-Enhanced Evolving Attention Networks. IEEE Trans. Pattern Anal. Mach. Intell. Yujing Wang, Yaming Yang, Zhuo Li, Jiangang Bai, Mingliang Zhang, Xiangtai Li, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong
2023	A*	`conf`	DBCatcher: A Cloud Database Online Anomaly Detection System based on Indicator Correlation. ICDE Guangyu Zhang, Chunhua Li, Ke Zhou, Li Liu, Ce Zhang, Wancheng Chen, Haotian Fang, Bin Cheng, Jie Yang, Jiashu Xing
2023	J	`jnl`	DMLR: Data-centric Machine Learning Research - Past, Present and Future. CoRR Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G. Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed M. Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson
2023	A*	`conf`	DSG: An End-to-End Document Structure Generator. ICDM Johannes Rausch, Gentiana Rashiti, Maxim Gusev, Ce Zhang, Stefan Feuerriegel
2023	J	`jnl`	DSG: An End-to-End Document Structure Generator. CoRR Johannes Rausch, Gentiana Rashiti, Maxim Gusev, Ce Zhang, Stefan Feuerriegel
2023	A*	`conf`	DataPerf: Benchmarks for Data-Centric AI Development. NeurIPS Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Will Cukierski, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Raje, Max Bartolo, Evan Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Addison Howard, Oana Inel, Tariq Kane, Christine R. Kirkpatrick, D. Sculley, Tzu-Sheng Kuo, Jonas W. Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Y. Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi
2023	A*	`conf`	Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. ICML Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Ré, Beidi Chen
2023	J	`jnl`	Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. CoRR Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Ré, Beidi Chen
2023	J	`jnl`	Effective and Efficient Federated Tree Learning on Hybrid Data. CoRR Qinbin Li, Chulin Xie, Xiaojun Xu, Xiaoyuan Liu, Ce Zhang, Bo Li, Bingsheng He, Dawn Song
2023	A*	`conf`	FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization. ICML Zhen Wang, Weirui Kuang, Ce Zhang, Bolin Ding, Yaliang Li
2023	A*	`conf`	FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU. ICML Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Beidi Chen, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang
2023	J	`jnl`	Hierarchical Classification of Research Fields in the "Web of Science" Using Deep Learning. CoRR Susie Xi Rao, Peter H. Egger, Ce Zhang
2023	J	`jnl`	High-throughput Generative Inference of Large Language Models with a Single GPU. CoRR Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Daniel Y. Fu, Zhiqiang Xie, Beidi Chen, Clark W. Barrett, Joseph E. Gonzalez, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang
2023	J	`jnl`	Holistic Evaluation of Language Models. Trans. Mach. Learn. Res. Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda
2023	J	`jnl`	Improving Retrieval-Augmented Large Language Models via Data Importance Learning. CoRR Xiaozhong Lyu, Stefan Grafberger, Samantha Biegel, Shaopeng Wei, Meng Cao, Sebastian Schelter, Ce Zhang
2023	J	`jnl`	In-Context Few-Shot Relation Extraction via Pre-Trained Language Models. CoRR Yilmazcan Özyurt, Stefan Feuerriegel, Ce Zhang
2023	J	`jnl`	Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-Aware Deep Architecture. IEEE Trans. Knowl. Data Eng. Xupeng Miao, Wentao Zhang, Yingxia Shao, Bin Cui, Lei Chen, Ce Zhang, Jiawei Jiang
2023	A*	`conf`	Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions. NeurIPS Stefano Massaroli, Michael Poli, Daniel Y. Fu, Hermann Kumbong, Rom N. Parnichkun, David W. Romero, Aman Timalsina, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio
2023	J	`jnl`	Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions. CoRR Stefano Massaroli, Michael Poli, Daniel Y. Fu, Hermann Kumbong, Rom N. Parnichkun, Aman Timalsina, David W. Romero, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio
2023	J	`jnl`	OpenBox: A Python Toolkit for Generalized Black-box Optimization. CoRR Huaijun Jiang, Yu Shen, Yang Li, Wentao Zhang, Ce Zhang, Bin Cui
2023	—	`conf`	Proactively Screening Machine Learning Pipelines with ARGUSEYES. SIGMOD Conference Companion Sebastian Schelter, Stefan Grafberger, Shubha Guha, Bojan Karlas, Ce Zhang
2023	A*	`conf`	RAB: Provable Robustness Against Backdoor Attacks. SP Maurice Weber, Xiaojun Xu, Bojan Karlas, Ce Zhang, Bo Li
2023	J	`jnl`	Skill-it! A Data-Driven Skills Framework for Understanding and Training Language Models. CoRR Mayee F. Chen, Nicholas Roberts, Kush Bhatia, Jue Wang, Ce Zhang, Frederic Sala, Christopher Ré
2023	A*	`conf`	Skill-it! A data-driven skills framework for understanding and training language models. NeurIPS Mayee F. Chen, Nicholas Roberts, Kush Bhatia, Jue Wang, Ce Zhang, Frederic Sala, Christopher Ré
2023	J	`jnl`	Towards General and Efficient Online Tuning for Spark. CoRR Yang Li, Huaijun Jiang, Yu Shen, Yide Fang, Xiaofeng Yang, Danqing Huang, Xinyi Zhang, Wentao Zhang, Ce Zhang, Peng Chen, Bin Cui
2023	J	`jnl`	Towards General and Efficient Online Tuning for Spark. Proc. VLDB Endow. Yang Li, Huaijun Jiang, Yu Shen, Yide Fang, Xiaofeng Yang, Danqing Huang, Xinyi Zhang, Wentao Zhang, Ce Zhang, Peng Chen, Bin Cui
2023	J	`jnl`	VolcanoML: speeding up end-to-end AutoML via scalable search space decomposition. VLDB J. Yang Li, Yu Shen, Wentao Zhang, Ce Zhang, Bin Cui
2023	A*	`conf`	WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data. NeurIPS Maurice Weber, Carlo Siebenschuh, Rory Butler, Anton Alexandrov, Valdemar Thanner, Georgios Tsolakis, Haris Jabbar, Ian T. Foster, Bo Li, Rick Stevens, Ce Zhang
2023	J	`jnl`	WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data. CoRR Maurice Weber, Carlo Siebenschuh, Rory Butler, Anton Alexandrov, Valdemar Thanner, Georgios Tsolakis, Haris Jabbar, Ian T. Foster, Bo Li, Rick Stevens, Ce Zhang
2022	A*	`conf`	A Deep Markov Model for Clickstream Analytics in Online Shopping. WWW Yilmazcan Özyurt, Tobias Hatt, Ce Zhang, Stefan Feuerriegel
2022	J	`jnl`	Advances, challenges and opportunities in creating data for trustworthy AI. Nat. Mach. Intell. Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou
2022	J	`jnl`	Author Correction: Advances, challenges and opportunities in creating data for trustworthy AI. Nat. Mac. Intell. Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou
2022	J	`jnl`	BRIGHT - Graph Neural Networks in Real-Time Fraud Detection. CoRR Mingxuan Lu, Zhichao Han, Susie Xi Rao, Zitao Zhang, Yang Zhao, Yinan Shan, Ramesh Raghunathan, Ce Zhang, Jiawei Jiang
2022	A	`conf`	BRIGHT - Graph Neural Networks in Real-time Fraud Detection. CIKM Mingxuan Lu, Zhichao Han, Susie Xi Rao, Zitao Zhang, Yang Zhao, Yinan Shan, Ramesh Raghunathan, Ce Zhang, Jiawei Jiang
2022	J	`jnl`	Bringing artificial intelligence to business management. Nat. Mach. Intell. Stefan Feuerriegel, Yash Raj Shrestha, Georg von Krogh, Ce Zhang
2022	J	`jnl`	CARE: Certifiably Robust Learning with Reasoning via Variational Inference. CoRR Jiawei Zhang, Linyi Li, Ce Zhang, Bo Li
2022	A*	`conf`	Certifying Out-of-Domain Generalization for Blackbox Functions. ICML Maurice Weber, Linyi Li, Boxin Wang, Zhikuan Zhao, Bo Li, Ce Zhang
2022	J	`jnl`	Certifying Out-of-Domain Generalization for Blackbox Functions. CoRR Maurice Weber, Linyi Li, Boxin Wang, Zhikuan Zhao, Bo Li, Ce Zhang
2022	A*	`conf`	Certifying Some Distributional Fairness with Subpopulation Decomposition. NeurIPS Mintong Kang, Linyi Li, Maurice Weber, Yang Liu, Ce Zhang, Bo Li
2022	J	`jnl`	Certifying Some Distributional Fairness with Subpopulation Decomposition. CoRR Mintong Kang, Linyi Li, Maurice Weber, Yang Liu, Ce Zhang, Bo Li
2022	J	`jnl`	Contrastive Learning for Unsupervised Domain Adaptation of Time Series. CoRR Yilmazcan Özyurt, Stefan Feuerriegel, Ce Zhang
2022	J	`jnl`	Convolution-enhanced Evolving Attention Networks. CoRR Yujing Wang, Yaming Yang, Zhuo Li, Jiangang Bai, Mingliang Zhang, Xiangtai Li, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong
2022	A	`conf`	DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines. CIDR Patrick Damme, Marius Birkenbach, Constantinos Bitsakos, Matthias Boehm, Philippe Bonnet, Florina M. Ciorba, Mark Dokter, Pawel Dowgiallo, Ahmed Eleliemy, Christian Faerber, Georgios I. Goumas, Dirk Habich, Niclas Hedam, Marlies Hofer, Wenjun Huang, Kevin Innerebner, Vasileios Karakostas, Roman Kern, Tomaz Kosar, Alexander Krause, Daniel Krems, Andreas Laber, Wolfgang Lehner, Eric Mier, Marcus Paradies, Bernhard Peischl, Gabrielle Poerwawinata, Stratos Psomadakis, Tilmann Rabl, Piotr Ratuszniak, Pedro Silva, Nikolai Skuppin, Andreas Starzacher, Benjamin Steinwender, Ilin Tolovski, Pinar Tözün, Wojciech Ulatowski, Yuanyuan Wang, Izajasz P. Wrosz, Ales Zamuda, Ce Zhang, Xiaoxiang Zhu
2022	J	`jnl`	Data Debugging with Shapley Importance over End-to-End Machine Learning Pipelines. CoRR Bojan Karlas, David Dao, Matteo Interlandi, Bo Li, Sebastian Schelter, Wentao Wu, Ce Zhang
2022	J	`jnl`	Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines. SIGMOD Rec. Fotis Psallidas, Yiwen Zhu, Bojan Karlas, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, K. Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos
2022	J	`jnl`	DataPerf: Benchmarks for Data-Centric AI Development. CoRR Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Juan Ciro, Lora Aroyo, Bilge Acun, Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Tariq Kane, Christine R. Kirkpatrick, Tzu-Sheng Kuo, Jonas Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi
2022	A*	`conf`	Decentralized Training of Foundation Models in Heterogeneous Environments. NeurIPS Binhang Yuan, Yongjun He, Jared Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Ré, Ce Zhang
2022	J	`jnl`	Decentralized Training of Foundation Models in Heterogeneous Environments. CoRR Binhang Yuan, Yongjun He, Jared Quincy Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Ré, Ce Zhang
2022	—	`ch.`	Deep Learning for Recommender Systems. Recommender Systems Handbook Shuai Zhang, Yi Tay, Lina Yao, Aixin Sun, Ce Zhang
2022	—	`book`	Distributed Machine Learning and Gradient Optimization Jiawei Jiang, Bin Cui, Ce Zhang
2022	B	`conf`	Dynamic Human Evaluation for Relative Model Comparisons. LREC Thórhildur Thorleiksdóttir, Cédric Renggli, Nora Hollenstein, Ce Zhang
2022	J	`jnl`	Efficient End-to-End AutoML via Scalable Search Space Decomposition. CoRR Yang Li, Yu Shen, Wentao Zhang, Ce Zhang, Bin Cui
2022	J	`jnl`	Experiments as Code: A Concept for Reproducible, Auditable, Debuggable, Reusable, & Scalable Experiments. CoRR Leonel Aguilar, Michal Gath-Morad, Jascha Grübel, Jasper Ermatinger, Hantao Zhao, Stefan Wehrli, Robert W. Sumner, Ce Zhang, Dirk Helbing, Christoph Hölscher
2022	J	`jnl`	FedHPO-B: A Benchmark Suite for Federated Hyperparameter Optimization. CoRR Zhen Wang, Weirui Kuang, Ce Zhang, Bolin Ding, Yaliang Li
2022	J	`jnl`	Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees. CoRR Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Ré, Ce Zhang
2022	A*	`conf`	Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees. NeurIPS Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Ré, Ce Zhang
2022	—	`conf`	GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networks. LoG Kenza Amara, Zhitao Ying, Zitao Zhang, Zhichao Han, Yang Zhao, Yinan Shan, Ulrik Brandes, Sebastian Schemm, Ce Zhang
2022	J	`jnl`	GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networks. CoRR Kenza Amara, Rex Ying, Zitao Zhang, Zhihao Han, Yinan Shan, Ulrik Brandes, Sebastian Schemm, Ce Zhang
2022	—	`conf`	HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements. SIGMOD Conference Baoqing Cai, Yu Liu, Ce Zhang, Guangyu Zhang, Ke Zhou, Li Liu, Chunhua Li, Bin Cheng, Jie Yang, Jiashu Xing
2022	J	`jnl`	Holistic Evaluation of Language Models. CoRR Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda
2022	J	`jnl`	Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale. CoRR Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Jixiang Li, Ji Liu, Ce Zhang, Bin Cui
2022	J	`jnl`	Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale. Proc. VLDB Endow. Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Jixiang Li, Ji Liu, Ce Zhang, Bin Cui
2022	A*	`conf`	Improving Certified Robustness via Statistical Learning with Logical Reasoning. NeurIPS Zhuolin Yang, Zhikuan Zhao, Boxin Wang, Jiawei Zhang, Linyi Li, Hengzhi Pei, Bojan Karlas, Ji Liu, Heng Guo, Ce Zhang, Bo Li
2022	J	`jnl`	Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM. CoRR Chulin Xie, Pin-Yu Chen, Ce Zhang, Bo Li
2022	—	`conf`	In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle. SIGMOD Conference Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang
2022	—	`conf`	Keyword Extraction in Scientific Documents. SwissText Susie Xi Rao, Piriyakorn Piriyatamwong, Parijat Ghoshal, Sara Nasirian, Sandra Mitrovic, Emmanuel de Salis, Michael Wechner, Vanya Brucker, Peter H. Egger, Ce Zhang
2022	J	`jnl`	Keyword Extraction in Scientific Documents. CoRR Susie Xi Rao, Piriyakorn Piriyatamwong, Parijat Ghoshal, Sara Nasirian, Emmanuel de Salis, Sandra Mitrovic, Michael Wechner, Vanya Brucker, Peter H. Egger, Ce Zhang
2022	A*	`conf`	LINKTELLER: Recovering Private Edges from Graph Neural Networks via Influence Analysis. SP Fan Wu, Yunhui Long, Ce Zhang, Bo Li
2022	A*	`conf`	Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture (Extended Abstract). ICDE Xupeng Miao, Wentao Zhang, Yingxia Shao, Bin Cui, Lei Chen, Ce Zhang, Jiawei Jiang
2022	J	`jnl`	Modelling graph dynamics in fraud detection with "Attention". CoRR Susie Xi Rao, Clémence Lanfranchi, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Mo Cheng, Yinan Shan, Yang Zhao, Ce Zhang
2022	J	`jnl`	Neural Methods for Logical Reasoning Over Knowledge Graphs. CoRR Alfonso Amayuelas, Shuai Zhang, Susie Xi Rao, Ce Zhang
2022	A*	`conf`	Neural Methods for Logical Reasoning over Knowledge Graphs. ICLR Alfonso Amayuelas, Shuai Zhang, Susie Xi Rao, Ce Zhang
2022	J	`jnl`	New primitives for bounded degradation in network service. CoRR Simon Kassing, Vojislav Dukic, Ce Zhang, Ankit Singla
2022	A*	`conf`	Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters. KDD Xiangru Lian, Binhang Yuan, Xuefeng Zhu, Yulong Wang, Yongjun He, Honghuan Wu, Lei Sun, Haodong Lyu, Chengjun Liu, Xing Dong, Yiqiao Liao, Mingnan Luo, Congfei Zhang, Jingru Xie, Haonan Li, Lei Chen, Renjie Huang, Jianying Lin, Chengchun Shu, Xuezhong Qiu, Zhishan Liu, Dongying Kong, Lei Yuan, Hai Yu, Sen Yang, Ce Zhang, Ji Liu
2022	A*	`conf`	ReforesTree: A Dataset for Estimating Tropical Forest Carbon Stock with Deep Learning and Aerial Imagery. AAAI Gyri Reiersen, David Dao, Björn Lütjens, Konstantin Klemmer, Kenza Amara, Attila Steinegger, Ce Zhang, Xiaoxiang Zhu
2022	J	`jnl`	ReforesTree: A Dataset for Estimating Tropical Forest Carbon Stock with Deep Learning and Aerial Imagery. CoRR Gyri Reiersen, David Dao, Björn Lütjens, Konstantin Klemmer, Kenza Amara, Attila Steinegger, Ce Zhang, Xiaoxiang Zhu
2022	J	`jnl`	SHiFT: An Efficient, Flexible Search Engine for Transfer Learning. CoRR Cédric Renggli, Xiaozhe Yao, Luka Kolar, Luka Rimanic, Ana Klimovic, Ce Zhang
2022	J	`jnl`	SHiFT: An Efficient, Flexible Search Engine for Transfer Learning. Proc. VLDB Endow. Cédric Renggli, Xiaozhe Yao, Luka Kolar, Luka Rimanic, Ana Klimovic, Ce Zhang
2022	A	`conf`	Screening Native Machine Learning Pipelines with ArgusEyes. CIDR Sebastian Schelter, Stefan Grafberger, Shubha Guha, Olivier Sprangers, Bojan Karlas, Ce Zhang
2022	J	`jnl`	Stochastic Gradient Descent without Full Data Shuffle. CoRR Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang
2022	—	`conf`	TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets. SDU@AAAI Susie Xi Rao, Johannes Rausch, Peter H. Egger, Ce Zhang
2022	J	`jnl`	TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets. CoRR Susie Xi Rao, Johannes Rausch, Peter H. Egger, Ce Zhang
2022	A*	`conf`	TransBO: Hyperparameter Optimization via Two-Phase Transfer Learning. KDD Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Zhi Yang, Ce Zhang, Bin Cui
2022	J	`jnl`	TransBO: Hyperparameter Optimization via Two-Phase Transfer Learning. CoRR Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Zhi Yang, Ce Zhang, Bin Cui
2022	A*	`conf`	Transfer Learning based Search Space Design for Hyperparameter Tuning. KDD Yang Li, Yu Shen, Huaijun Jiang, Tianyi Bai, Wentao Zhang, Ce Zhang, Bin Cui
2022	J	`jnl`	Transfer Learning based Search Space Design for Hyperparameter Tuning. CoRR Yang Li, Yu Shen, Huaijun Jiang, Tianyi Bai, Wentao Zhang, Ce Zhang, Bin Cui
2022	—	`conf`	User-Centered Information Architecture of Vehicle AR-HUD Interface. HCI (34) Han Zhang, Zhefan Yu, Ce Zhang, Ruotian Zhang, Yuyang Liu, Seung Hee Lee
2022	A*	`conf`	VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely? NeurIPS Jiawei Jiang, Lukas Burkhalter, Fangcheng Fu, Bolin Ding, Bo Du, Anwar Hithnawi, Bo Li, Ce Zhang
2022	A*	`conf`	Which Model to Transfer? Finding the Needle in the Growing Haystack. CVPR Cédric Renggli, André Susano Pinto, Luka Rimanic, Joan Puigcerver, Carlos Riquelme, Ce Zhang, Mario Lucic
2022	—	`conf`	dcbench: a benchmark for data-centric AI systems. DEEM@SIGMOD Sabri Eyuboglu, Bojan Karlas, Christopher Ré, Ce Zhang, James Zou
2022	A*	`conf`	iFlood: A Stable and Effective Regularizer. ICLR Yuexiang Xie, Zhen Wang, Yaliang Li, Ce Zhang, Jingren Zhou, Bolin Ding
2021	A*	`conf`	1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed. ICML Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He
2021	J	`jnl`	1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed. CoRR Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He
2021	J	`jnl`	A Data Quality-Driven View of MLOps. CoRR Cédric Renggli, Luka Rimanic, Nezihe Merve Gürel, Bojan Karlas, Wentao Wu, Ce Zhang
2021	J	`jnl`	A Data Quality-Driven View of MLOps. IEEE Data Eng. Bull. Cédric Renggli, Luka Rimanic, Nezihe Merve Gürel, Bojan Karlas, Wentao Wu, Ce Zhang
2021	J	`jnl`	A Large-Scale Study of Android Malware Development Phenomenon on Public Malware Submission and Scanning Platform. IEEE Trans. Big Data Heqing Huang, Cong Zheng, Junyuan Zeng, Wu Zhou, Sencun Zhu, Peng Liu, Ian M. Molloy, Suresh Chari, Ce Zhang, Quanlong Guan
2021	A*	`conf`	AutoML: A Perspective where Industry Meets Academy. KDD Yaliang Li, Zhen Wang, Bolin Ding, Ce Zhang
2021	A	`conf`	AutoML: From Methodology to Application. CIKM Yaliang Li, Zhen Wang, Yuexiang Xie, Bolin Ding, Kai Zeng, Ce Zhang
2021	J	`jnl`	BAGUA: Scaling up Distributed Learning with System Relaxations. CoRR Shaoduo Gan, Xiangru Lian, Rui Wang, Jianbin Chang, Chengjun Liu, Hongmei Shi, Shengzhuo Zhang, Xianghong Li, Tengxu Sun, Jiawei Jiang, Binhang Yuan, Sen Yang, Ji Liu, Ce Zhang
2021	J	`jnl`	BAGUA: Scaling up Distributed Learning with System Relaxations. Proc. VLDB Endow. Shaoduo Gan, Xiangru Lian, Rui Wang, Jianbin Chang, Chengjun Liu, Hongmei Shi, Shengzhuo Zhang, Xianghong Li, Tengxu Sun, Jiawei Jiang, Binhang Yuan, Sen Yang, Ji Liu, Ce Zhang
2021	A*	`conf`	CleanML: A Study for Evaluating the Impact of Data Cleaning on ML Classification Tasks. ICDE Peng Li, Xi Rao, Jennifer Blase, Yue Zhang, Xu Chu, Ce Zhang
2021	A*	`conf`	DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation. CCS Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li
2021	J	`jnl`	DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation. CoRR Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li
2021	A*	`conf`	DeGNN: Improving Graph Neural Networks with Graph Decomposition. KDD Xupeng Miao, Nezihe Merve Gürel, Wentao Zhang, Zhichao Han, Bo Li, Wei Min, Susie Xi Rao, Hansheng Ren, Yinan Shan, Yingxia Shao, Yujie Wang, Fan Wu, Hui Xue, Yaming Yang, Zitao Zhang, Yang Zhao, Shuai Zhang, Yujing Wang, Bin Cui, Ce Zhang
2021	J	`jnl`	Decoding EEG Brain Activity for Multi-Modal Natural Language Processing. CoRR Nora Hollenstein, Cédric Renggli, Benjamin Glaus, Maria Barrett, Marius Troendle, Nicolas Langer, Ce Zhang
2021	J	`jnl`	Distributed Learning Systems with First-order Methods. CoRR Ji Liu, Ce Zhang
2021	A*	`conf`	DocParser: Hierarchical Document Structure Parsing from Renderings. AAAI Johannes Rausch, Octavio Martinez, Fabian Bissig, Ce Zhang, Stefan Feuerriegel
2021	J	`jnl`	Dynamic Human Evaluation for Relative Model Comparisons. CoRR Thórhildur Thorleiksdóttir, Cédric Renggli, Nora Hollenstein, Ce Zhang
2021	A	`conf`	Ease.ML: A Lifecycle Management System for Machine Learning. CIDR Leonel Aguilar Melgar, David Dao, Shaoduo Gan, Nezihe Merve Gürel, Nora Hollenstein, Jiawei Jiang, Bojan Karlas, Thomas Lemmin, Tian Li, Yang Li, Susie Xi Rao, Johannes Rausch, Cédric Renggli, Luka Rimanic, Maurice Weber, Shuai Zhang, Zhikuan Zhao, Kevin Schawinski, Wentao Wu, Ce Zhang
2021	J	`jnl`	Evaluating Bayes Error Estimators on Read-World Datasets with FeeBee. CoRR Cédric Renggli, Luka Rimanic, Nora Hollenstein, Ce Zhang
2021	—	`conf`	Evaluating Bayes Error Estimators on Real-World Datasets with FeeBee. NeurIPS Datasets and Benchmarks Cédric Renggli, Luka Rimanic, Nora Hollenstein, Ce Zhang
2021	A*	`conf`	Evolving Attention with Residual Convolutions. ICML Yujing Wang, Yaming Yang, Jiangang Bai, Mingliang Zhang, Jing Bai, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong
2021	J	`jnl`	Evolving Attention with Residual Convolutions. CoRR Yujing Wang, Yaming Yang, Jiangang Bai, Mingliang Zhang, Jing Bai, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong
2021	A*	`conf`	FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data. KDD Yuexiang Xie, Zhen Wang, Yaliang Li, Bolin Ding, Nezihe Merve Gürel, Ce Zhang, Minlie Huang, Wei Lin, Jingren Zhou
2021	J	`jnl`	Federated Matrix Factorization with Privacy Guarantee. Proc. VLDB Endow. Zitao Li, Bolin Ding, Ce Zhang, Ninghui Li, Jingren Zhou
2021	A*	`conf`	FleetRec: Large-Scale Recommendation Inference on Hybrid GPU-FPGA Clusters. KDD Wenqi Jiang, Zhenhao He, Shuai Zhang, Kai Zeng, Liang Feng, Jiansong Zhang, Tongxuan Liu, Yong Li, Jingren Zhou, Ce Zhang, Gustavo Alonso
2021	A*	`conf`	Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks. ICML Nezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang, Bo Li
2021	J	`jnl`	Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks. CoRR Nezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang, Bo Li
2021	—	`conf`	Knowledge Router: Learning Disentangled Representations for Knowledge Graphs. NAACL-HLT Shuai Zhang, Xi Rao, Yi Tay, Ce Zhang
2021	A	`conf`	Learning User Representations with Hypercuboids for Recommender Systems. WSDM Shuai Zhang, Huoyu Liu, Aston Zhang, Yue Hu, Ce Zhang, Yumeng Li, Tanchao Zhu, Shaojian He, Wenwu Ou
2021	J	`jnl`	LinkTeller: Recovering Private Edges from Graph Neural Networks via Influence Analysis. CoRR Fan Wu, Yunhui Long, Ce Zhang, Bo Li
2021	A*	`conf`	MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements. AAAI Yang Li, Yu Shen, Jiawei Jiang, Jinyang Gao, Ce Zhang, Bin Cui
2021	—	`conf`	MicroRec: Efficient Recommendation Inference by Hardware and Data Structure Solutions. MLSys Wenqi Jiang, Zhenhao He, Shuai Zhang, Thomas B. Preußer, Kai Zeng, Liang Feng, Jiansong Zhang, Tongxuan Liu, Yong Li, Jingren Zhou, Ce Zhang, Gustavo Alonso
2021	J	`jnl`	Model averaging in distributed machine learning: a case study with Apache Spark. VLDB J. Yunyan Guo, Zhipeng Zhang, Jiawei Jiang, Wentao Wu, Ce Zhang, Bin Cui, Jianzhong Li
2021	—	`conf`	Multilingual Language Models Predict Human Reading Behavior. NAACL-HLT Nora Hollenstein, Federico Pirovano, Ce Zhang, Lena A. Jäger, Lisa Beinborn
2021	J	`jnl`	Multilingual Language Models Predict Human Reading Behavior. CoRR Nora Hollenstein, Federico Pirovano, Ce Zhang, Lena A. Jäger, Lisa Beinborn
2021	A	`conf`	Online Active Model Selection for Pre-trained Classifiers. AISTATS Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlas, Johannes Rausch, Ce Zhang, Andreas Krause
2021	A*	`conf`	OpenBox: A Generalized Black-box Optimization Service. KDD Yang Li, Yu Shen, Wentao Zhang, Yuanwei Chen, Huaijun Jiang, Mingchao Liu, Jiawei Jiang, Jinyang Gao, Wentao Wu, Zhi Yang, Ce Zhang, Bin Cui
2021	J	`jnl`	OpenBox: A Generalized Black-box Optimization Service. CoRR Yang Li, Yu Shen, Wentao Zhang, Yuanwei Chen, Huaijun Jiang, Mingchao Liu, Jiawei Jiang, Jinyang Gao, Wentao Wu, Zhi Yang, Ce Zhang, Bin Cui
2021	J	`jnl`	Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters. CoRR Xiangru Lian, Binhang Yuan, Xuefeng Zhu, Yulong Wang, Yongjun He, Honghuan Wu, Lei Sun, Haodong Lyu, Chengjun Liu, Xing Dong, Yiqiao Liao, Mingnan Luo, Congfei Zhang, Jingru Xie, Haonan Li, Lei Chen, Renjie Huang, Jianying Lin, Chengchun Shu, Xuezhong Qiu, Zhishan Liu, Dongying Kong, Lei Yuan, Hai Yu, Sen Yang, Ce Zhang, Ji Liu
2021	J	`jnl`	RumbleML: program the lakehouse with JSONiq. CoRR Ghislain Fourny, David Dao, Can Berker Cikis, Ce Zhang, Gustavo Alonso
2021	A*	`conf`	Scalability vs. Utility: Do We Have To Sacrifice One for the Other in Data Importance Quantification? CVPR Ruoxi Jia, Fan Wu, Xuehui Sun, Jiacen Xu, David Dao, Bhavya Kailkhura, Ce Zhang, Bo Li, Dawn Song
2021	J	`jnl`	Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting. CoRR Defu Cao, Yujing Wang, Juanyong Duan, Ce Zhang, Xia Zhu, Congrui Huang, Yunhai Tong, Bixiong Xu, Jing Bai, Jie Tong, Qi Zhang
2021	J	`jnl`	Switch Spaces: Learning Product Spaces with Sparse Gating. CoRR Shuai Zhang, Yi Tay, Wenqi Jiang, Da-Cheng Juan, Ce Zhang
2021	J	`jnl`	TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothness. CoRR Zhuolin Yang, Linyi Li, Xiaojun Xu, Shiliang Zuo, Qian Chen, Benjamin I. P. Rubinstein, Ce Zhang, Bo Li
2021	A*	`conf`	TRS: Transferability Reduced Ensemble via Promoting Gradient Diversity and Model Smoothness. NeurIPS Zhuolin Yang, Linyi Li, Xiaojun Xu, Shiliang Zuo, Qian Chen, Pan Zhou, Benjamin I. P. Rubinstein, Ce Zhang, Bo Li
2021	A*	`conf`	TSS: Transformation-Specific Smoothing for Robustness Certification. CCS Linyi Li, Maurice Weber, Xiaojun Xu, Luka Rimanic, Bhavya Kailkhura, Tao Xie, Ce Zhang, Bo Li
2021	J	`jnl`	Tackling the Overestimation of Forest Carbon with Deep Learning and Aerial Imagery. CoRR Gyri Reiersen, David Dao, Björn Lütjens, Konstantin Klemmer, Xiaoxiang Zhu, Ce Zhang
2021	—	`conf`	Towards Demystifying Serverless Machine Learning Training. SIGMOD Conference Jiawei Jiang, Shaoduo Gan, Yue Liu, Fanlin Wang, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Ce Zhang
2021	J	`jnl`	Towards Demystifying Serverless Machine Learning Training. CoRR Jiawei Jiang, Shaoduo Gan, Yue Liu, Fanlin Wang, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Ce Zhang
2021	—	`conf`	Towards understanding end-to-end learning in the context of data: machine learning dancing over semirings & Codd's table. DEEM@SIGMOD Wentao Wu, Ce Zhang
2021	J	`jnl`	VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition. CoRR Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Bolin Ding, Yaliang Li, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui
2021	J	`jnl`	VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition. Proc. VLDB Endow. Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Yaliang Li, Bolin Ding, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui
2021	J	`jnl`	WindTunnel: Towards Differentiable ML Pipelines Beyond a Single Modele. Proc. VLDB Endow. Gyeong-In Yu, Saeed Amizadeh, Sehoon Kim, Artidoro Pagnoni, Ce Zhang, Byung-Gon Chun, Markus Weimer, Matteo Interlandi
2021	J	`jnl`	xFraud: Explainable Fraud Transaction Detection. Proc. VLDB Endow. Susie Xi Rao, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Zhiyao Chen, Yinan Shan, Yang Zhao, Ce Zhang
2020	J	`jnl`	A Principled Approach to Data Valuation for Federated Learning. CoRR Tianhao Wang, Johannes Rausch, Ce Zhang, Ruoxi Jia, Dawn Song
2020	—	`ch.`	A Principled Approach to Data Valuation for Federated Learning. Federated Learning Tianhao Wang, Johannes Rausch, Ce Zhang, Ruoxi Jia, Dawn Song
2020	J	`jnl`	APMSqueeze: A Communication Efficient Adam-Preconditioned Momentum SGD Algorithm. CoRR Hanlin Tang, Shaoduo Gan, Samyam Rajbhandari, Xiangru Lian, Ji Liu, Yuxiong He, Ce Zhang
2020	A*	`conf`	Building Continuous Integration Services for Machine Learning. KDD Bojan Karlas, Matteo Interlandi, Cédric Renggli, Wentao Wu, Ce Zhang, Deepak Mukunthu Iyappan Babu, Jordan Edwards, Chris Lauren, Andy Xu, Markus Weimer
2020	A*	`conf`	C olumnSGD: A Column-oriented Framework for Distributed Stochastic Gradient Descent. ICDE Zhipeng Zhang, Wentao Wu, Jiawei Jiang, Lele Yu, Bin Cui, Ce Zhang
2020	—	`conf`	CogniVal in Action: An Interface for Customizable Cognitive Word Embedding Evaluation. COLING (Demonstrations) Nora Hollenstein, Adrian Van der Lek, Ce Zhang
2020	J	`jnl`	Compressive Sensing Using Iterative Hard Thresholding With Low Precision Data Representation: Theory and Applications. IEEE Trans. Signal Process. Nezihe Merve Gürel, Kaan Kara, Alen Stojanov, Tyler M. Smith, Thomas Lemmin, Dan Alistarh, Markus Püschel, Ce Zhang
2020	—	`conf`	Control, Generate, Augment: A Scalable Framework for Multi-Attribute Text Generation. EMNLP (Findings) Giuseppe Russo, Nora Hollenstein, Claudiu Cristian Musat, Ce Zhang
2020	J	`jnl`	Control, Generate, Augment: A Scalable Framework for Multi-Attribute Text Generation. CoRR Giuseppe Russo, Nora Hollenstein, Claudiu Musat, Ce Zhang
2020	J	`jnl`	Distributed Learning Systems with First-Order Methods. Found. Trends Databases Ji Liu, Ce Zhang
2020	A*	`conf`	Don't Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript. ICML Fangcheng Fu, Yuzheng Hu, Yihan He, Jiawei Jiang, Yingxia Shao, Ce Zhang, Bin Cui
2020	J	`jnl`	Ease.ml/snoopy in Action: Towards Automatic Feasibility Analysis for Machine Learning Application Development. Proc. VLDB Endow. Cédric Renggli, Luka Rimanic, Luka Kolar, Wentao Wu, Ce Zhang
2020	A*	`conf`	Efficient Automatic CASH via Rising Bandits. AAAI Yang Li, Jiawei Jiang, Jinyang Gao, Yingxia Shao, Ce Zhang, Bin Cui
2020	J	`jnl`	Efficient Automatic CASH via Rising Bandits. CoRR Yang Li, Jiawei Jiang, Jinyang Gao, Yingxia Shao, Ce Zhang, Bin Cui
2020	J	`jnl`	End-to-end Robustness for Sensing-Reasoning Machine Learning Pipelines. CoRR Zhuolin Yang, Zhikuan Zhao, Hengzhi Pei, Boxin Wang, Bojan Karlas, Ji Liu, Heng Guo, Bo Li, Ce Zhang
2020	J	`jnl`	Improving BERT with Self-Supervised Attention. CoRR Xiaoyu Kou, Yaming Yang, Yujing Wang, Ce Zhang, Yiren Chen, Yunhai Tong, Yan Zhang, Jing Bai
2020	J	`jnl`	Interactive Feature Generation via Learning Adjacency Tensor of Feature Graph. CoRR Yuexiang Xie, Zhen Wang, Yaliang Li, Bolin Ding, Nezihe Merve Gürel, Ce Zhang, Minlie Huang, Wei Lin, Jingren Zhou
2020	J	`jnl`	Learning User Representations with Hypercuboids for Recommender Systems. CoRR Shuai Zhang, Huoyu Liu, Aston Zhang, Yue Hu, Ce Zhang, Yumeng Li, Tanchao Zhu, Shaojian He, Wenwu Ou
2020	A*	`conf`	Learning to Mutate with Hypergradient Guided Population. NeurIPS Zhiqiang Tao, Yaliang Li, Bolin Ding, Ce Zhang, Jingren Zhou, Yun Fu
2020	J	`jnl`	MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements. CoRR Yang Li, Yu Shen, Jiawei Jiang, Jinyang Gao, Ce Zhang, Bin Cui
2020	J	`jnl`	MicroRec: Accelerating Deep Recommendation Systems to Microseconds by Hardware and Data Structure Solutions. CoRR Wenqi Jiang, Zhenhao He, Shuai Zhang, Thomas B. Preußer, Kai Zeng, Liang Feng, Jiansong Zhang, Tongxuan Liu, Yong Li, Jingren Zhou, Ce Zhang, Gustavo Alonso
2020	J	`jnl`	Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions. CoRR Bojan Karlas, Peng Li, Renzhi Wu, Nezihe Merve Gürel, Xu Chu, Wentao Wu, Ce Zhang
2020	J	`jnl`	Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions. Proc. VLDB Endow. Bojan Karlas, Peng Li, Renzhi Wu, Nezihe Merve Gürel, Xu Chu, Wentao Wu, Ce Zhang
2020	J	`jnl`	Neural dynamics of sentiment processing during naturalistic sentence reading. NeuroImage Christian Pfeiffer, Nora Hollenstein, Ce Zhang, Nicolas Langer
2020	—	`conf`	Observer Dependent Lossy Image Compression. GCPR Maurice Weber, Cédric Renggli, Helmut Grabner, Ce Zhang
2020	J	`jnl`	On Automatic Feasibility Study for Machine Learning Application Development with ease.ml/snoopy. CoRR Cédric Renggli, Luka Rimanic, Luka Kolar, Nora Hollenstein, Wentao Wu, Ce Zhang
2020	A*	`conf`	On Convergence of Nearest Neighbor Classifiers over Feature Transformations. NeurIPS Luka Rimanic, Cédric Renggli, Bo Li, Ce Zhang
2020	J	`jnl`	On Convergence of Nearest Neighbor Classifiers over Feature Transformations. CoRR Luka Rimanic, Cédric Renggli, Bo Li, Ce Zhang
2020	J	`jnl`	Online Active Model Selection for Pre-trained Classifiers. CoRR Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlas, Johannes Rausch, Ce Zhang, Andreas Krause
2020	J	`jnl`	Optimal Provable Robustness of Quantum Classification via Quantum Hypothesis Testing. CoRR Maurice Weber, Nana Liu, Bo Li, Ce Zhang, Zhikuan Zhao
2020	J	`jnl`	Provable Robust Learning Based on Transformation-Specific Smoothing. CoRR Linyi Li, Maurice Weber, Xiaojun Xu, Luka Rimanic, Tao Xie, Ce Zhang, Bo Li
2020	J	`jnl`	RAB: Provable Robustness Against Backdoor Attacks. CoRR Maurice Weber, Xiaojun Xu, Bojan Karlas, Ce Zhang, Bo Li
2020	J	`jnl`	RosENet: Improving Binding Affinity Prediction by Leveraging Molecular Mechanics Energies with an Ensemble of 3D Convolutional Neural Networks. J. Chem. Inf. Model. Hussein Hassan-Harrirou, Ce Zhang, Thomas Lemmin
2020	A*	`conf`	Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting. NeurIPS Defu Cao, Yujing Wang, Juanyong Duan, Ce Zhang, Xia Zhu, Congrui Huang, Yunhai Tong, Bixiong Xu, Jing Bai, Jie Tong, Qi Zhang
2020	J	`jnl`	Suspicious Massive Registration Detection via Dynamic Heterogeneous Graph Neural Networks. CoRR Susie Xi Rao, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Mo Cheng, Yinan Shan, Yang Zhao, Ce Zhang
2020	A*	`conf`	TextNAS: A Neural Architecture Search Space Tailored for Text Representation. AAAI Yujing Wang, Yaming Yang, Yiren Chen, Jing Bai, Ce Zhang, Guinan Su, Xiaoyu Kou, Yunhai Tong, Mao Yang, Lidong Zhou
2020	J	`jnl`	TrueBranch: Metric Learning-based Verification of Forest Conservation Projects. CoRR Simona Santamaria, David Dao, Björn Lütjens, Ce Zhang
2020	J	`jnl`	Which Model to Transfer? Finding the Needle in the Growing Haystack. CoRR Cédric Renggli, André Susano Pinto, Luka Rimanic, Joan Puigcerver, Carlos Riquelme, Ce Zhang, Mario Lucic
2020	B	`conf`	ZuCo 2.0: A Dataset of Physiological Recordings During Natural Reading and Annotation. LREC Nora Hollenstein, Marius Troendle, Ce Zhang, Nicolas Langer
2020	J	`jnl`	xFraud: Explainable Fraud Transaction Detection on Heterogeneous Graphs. CoRR Susie Xi Rao, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Zhiyao Chen, Yinan Shan, Yang Zhao, Ce Zhang
2019	J	`jnl`	Accelerating Generalized Linear Models with MLWeaving: A One-Size-Fits-All System for Any-precision Learning (Technical Report). CoRR Zeke Wang, Kaan Kara, Hantian Zhang, Gustavo Alonso, Onur Mutlu, Ce Zhang
2019	J	`jnl`	Accelerating Generalized Linear Models with MLWeaving: A One-Size-Fits-All System for Any-precision Learning. Proc. VLDB Endow. Zeke Wang, Kaan Kara, Hantian Zhang, Gustavo Alonso, Ce Zhang, Onur Mutlu
2019	J	`jnl`	Advancing NLP with Cognitive Language Processing Signals. CoRR Nora Hollenstein, Maria Barrett, Marius Troendle, Francesco Bigiolli, Nicolas Langer, Ce Zhang
2019	J	`jnl`	An Anatomy of Graph Neural Networks Going Deep via the Lens of Mutual Information: Exponential Decay vs. Full Preservation. CoRR Nezihe Merve Gürel, Hansheng Ren, Yujing Wang, Hui Xue, Yaming Yang, Ce Zhang
2019	J	`jnl`	An Empirical and Comparative Analysis of Data Valuation with Scalable Algorithms. CoRR Ruoxi Jia, Xuehui Sun, Jiacen Xu, Ce Zhang, Bo Li, Dawn Song
2019	A	`conf`	AutoML from Service Provider's Perspective: Multi-device, Multi-tenant Model Selection with GP-EI. AISTATS Chen Yu, Bojan Karlas, Jie Zhong, Ce Zhang, Ji Liu
2019	J	`jnl`	CleanML: A Benchmark for Joint Data Cleaning and Machine Learning [Experiments and Analysis]. CoRR Peng Li, Xi Rao, Jennifer Blase, Yue Zhang, Xu Chu, Ce Zhang
2019	B	`conf`	CogniVal: A Framework for Cognitive Word Embedding Evaluation. CoNLL Nora Hollenstein, Antonio de la Torre, Nicolas Langer, Ce Zhang
2019	J	`jnl`	CogniVal: A Framework for Cognitive Word Embedding Evaluation. CoRR Nora Hollenstein, Antonio de la Torre, Nicolas Langer, Ce Zhang
2019	—	`conf`	Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment. SysML Cédric Renggli, Bojan Karlas, Bolin Ding, Feng Liu, Kevin Schawinski, Wentao Wu, Ce Zhang
2019	J	`jnl`	Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment. CoRR Cédric Renggli, Bojan Karlas, Bolin Ding, Feng Liu, Kevin Schawinski, Wentao Wu, Ce Zhang
2019	A*	`conf`	DL2: Training and Querying Neural Networks with Logic. ICML Marc Fischer, Mislav Balunovic, Dana Drachsler-Cohen, Timon Gehr, Ce Zhang, Martin T. Vechev
2019	J	`jnl`	Data Science through the looking glass and what we found there. CoRR Fotis Psallidas, Yiwen Zhu, Bojan Karlas, Matteo Interlandi, Avrilia Floratou, Konstantinos Karanasos, Wentao Wu, Ce Zhang, Subru Krishnan, Carlo Curino, Markus Weimer
2019	J	`jnl`	DeepSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression. CoRR Hanlin Tang, Xiangru Lian, Shuang Qiu, Lei Yuan, Ce Zhang, Tong Zhang, Ji Liu
2019	A*	`conf`	Distributed Learning over Unreliable Networks. ICML Chen Yu, Hanlin Tang, Cédric Renggli, Simon Kassing, Ankit Singla, Dan Alistarh, Ce Zhang, Ji Liu
2019	J	`jnl`	DocParser: Hierarchical Structure Parsing of Document Renderings. CoRR Johannes Rausch, Octavio Martinez, Fabian Bissig, Ce Zhang, Stefan Feuerriegel
2019	J	`jnl`	Ease.ml/ci and Ease.ml/meter in Action: Towards Data Management for Statistical Generalization. Proc. VLDB Endow. Cédric Renggli, Frances Ann Hubis, Bojan Karlas, Kevin Schawinski, Wentao Wu, Ce Zhang
2019	J	`jnl`	Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms. CoRR Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nezihe Merve Gürel, Bo Li, Ce Zhang, Costas J. Spanos, Dawn Song
2019	J	`jnl`	Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms. Proc. VLDB Endow. Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nezihe Merve Gürel, Bo Li, Ce Zhang, Costas J. Spanos, Dawn Song
2019	—	`conf`	Entity Recognition at First Sight: Improving NER with Eye Movement Information. NAACL-HLT (1) Nora Hollenstein, Ce Zhang
2019	J	`jnl`	Entity Recognition at First Sight: Improving NER with Eye Movement Information. CoRR Nora Hollenstein, Ce Zhang
2019	Misc	`conf`	Is advance knowledge of flow sizes a plausible assumption? NSDI Vojislav Dukic, Sangeetha Abdu Jyothi, Bojan Karlas, Muhsen Owaida, Ce Zhang, Ankit Singla
2019	J	`jnl`	Lossy Image Compression with Recurrent Neural Networks: from Human Perceived Visual Quality to Classification Accuracy. CoRR Maurice Weber, Cédric Renggli, Helmut Grabner, Ce Zhang
2019	A*	`conf`	MLlib*: Fast Training of GLMs Using Spark MLlib. ICDE Zhipeng Zhang, Jiawei Jiang, Wentao Wu, Ce Zhang, Lele Yu, Bin Cui
2019	J	`jnl`	Opportunities for Data Management Research in the Era of Horizontal AI/ML. Proc. VLDB Endow. Theodoros Rekatsinas, Sudeepa Roy, Manasi Vartak, Ce Zhang, Neoklis Polyzotis
2019	J	`jnl`	Quantitative Overfitting Management for Human-in-the-loop ML Application Development with ease.ml/meter. CoRR Frances Ann Hubis, Wentao Wu, Ce Zhang
2019	—	`conf`	Sensing Social Media Signals for Cryptocurrency News. WWW (Companion Volume) Johannes Beck, Roberta Huang, David Lindner, Tian Guo, Ce Zhang, Dirk Helbing, Nino Antulov-Fantulin
2019	J	`jnl`	Sensing Social Media Signals for Cryptocurrency News. CoRR Johannes Beck, Roberta Huang, David Lindner, Tian Guo, Ce Zhang, Dirk Helbing, Nino Antulov-Fantulin
2019	J	`jnl`	SysML: The New Frontier of Machine Learning Systems. CoRR Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar
2019	J	`jnl`	TextNAS: A Neural Architecture Search Space tailored for Text Representation. CoRR Yujing Wang, Yaming Yang, Yiren Chen, Jing Bai, Ce Zhang, Guinan Su, Xiaoyu Kou, Yunhai Tong, Mao Yang, Lidong Zhou
2019	A	`conf`	Towards Efficient Data Valuation Based on the Shapley Value. AISTATS Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nick Hynes, Nezihe Merve Gürel, Bo Li, Ce Zhang, Dawn Song, Costas J. Spanos
2019	J	`jnl`	Towards Efficient Data Valuation Based on the Shapley Value. CoRR Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nick Hynes, Nezihe Merve Gürel, Bo Li, Ce Zhang, Dawn Song, Costas J. Spanos
2019	J	`jnl`	ZuCo 2.0: A Dataset of Physiological Recordings During Natural Reading and Annotation. CoRR Nora Hollenstein, Marius Troendle, Ce Zhang, Nicolas Langer
2019	J	`jnl`	doppioDB 2.0: Hardware Techniques for Improved Integration of Machine Learning into Databases. Proc. VLDB Endow. Kaan Kara, Zeke Wang, Ce Zhang, Gustavo Alonso
2018	A*	`conf`	Asynchronous Decentralized Parallel Stochastic Gradient Descent. ICML Xiangru Lian, Wei Zhang, Ce Zhang, Ji Liu
2018	J	`jnl`	ColumnML: Column-Store Machine Learning with On-The-Fly Data Transformation. Proc. VLDB Endow. Kaan Kara, Ken Eguro, Ce Zhang, Gustavo Alonso
2018	A*	`conf`	Communication Compression for Decentralized Training. NeurIPS Hanlin Tang, Shaoduo Gan, Ce Zhang, Tong Zhang, Ji Liu
2018	J	`jnl`	Compressive Sensing with Low Precision Data Representation: Radio Astronomy and Beyond. CoRR Nezihe Merve Gürel, Kaan Kara, Dan Alistarh, Ce Zhang
2018	A*	`conf`	D ICML Hanlin Tang, Xiangru Lian, Ming Yan, Ce Zhang, Ji Liu
2018	J	`jnl`	D CoRR Hanlin Tang, Xiangru Lian, Ming Yan, Ce Zhang, Ji Liu
2018	J	`jnl`	DataBright: Towards a Global Exchange for Decentralized Data Ownership and Trusted Computation. CoRR David Dao, Dan Alistarh, Claudiu Musat, Ce Zhang
2018	J	`jnl`	Decentralization Meets Quantization. CoRR Hanlin Tang, Ce Zhang, Shaoduo Gan, Tong Zhang, Ji Liu
2018	—	`conf`	DimBoost: Boosting Gradient Boosting Decision Tree to Higher Dimensions. SIGMOD Conference Jiawei Jiang, Bin Cui, Ce Zhang, Fangcheng Fu
2018	J	`jnl`	Distributed Learning over Unreliable Networks. CoRR Hanlin Tang, Chen Yu, Cédric Renggli, Simon Kassing, Ankit Singla, Dan Alistarh, Ji Liu, Ce Zhang
2018	—	`conf`	ETH-DS3Lab at SemEval-2018 Task 7: Effectively Combining Recurrent and Convolutional Neural Networks for Relation Classification and Extraction. SemEval@NAACL-HLT Jonathan Rotsztejn, Nora Hollenstein, Ce Zhang
2018	J	`jnl`	ETH-DS3Lab at SemEval-2018 Task 7: Effectively Combining Recurrent and Convolutional Neural Networks for Relation Classification and Extraction. CoRR Jonathan Rotsztejn, Nora Hollenstein, Ce Zhang
2018	J	`jnl`	Ease.ml in Action: Towards Multi-tenant Declarative Learning Services. Proc. VLDB Endow. Bojan Karlas, Ji Liu, Wentao Wu, Ce Zhang
2018	J	`jnl`	Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads. Proc. VLDB Endow. Tian Li, Jie Zhong, Ji Liu, Wentao Wu, Ce Zhang
2018	J	`jnl`	Exploring galaxy evolution with generative models. CoRR Kevin Schawinski, M. Dennis Turp, Ce Zhang
2018	—	`conf`	Inferring Short-Term Volatility Indicators from the Bitcoin Blockchain. COMPLEX NETWORKS (2) Nino Antulov-Fantulin, Dijana Tolic, Matija Piskorec, Ce Zhang, Irena Vodenska
2018	J	`jnl`	Inferring short-term volatility indicators from Bitcoin blockchain. CoRR Nino Antulov-Fantulin, Dijana Tolic, Matija Piskorec, Ce Zhang, Irena Vodenska
2018	A	`conf`	Layerwise Systematic Scan: Deep Boltzmann Machines and Beyond. AISTATS Heng Guo, Kaan Kara, Ce Zhang
2018	J	`jnl`	MLBench: Benchmarking Machine Learning Services Against Human Experts. Proc. VLDB Endow. Yu Liu, Hantian Zhang, Luyuan Zeng, Wentao Wu, Ce Zhang
2018	J	`jnl`	Multi-device, Multi-tenant Model Selection with GP-EI. CoRR Chen Yu, Bojan Karlas, Jie Zhong, Ce Zhang, Ji Liu
2018	—	`conf`	Network Scheduling in the Dark. SoCC Vojislav Dukic, Sangeetha Abdu Jyothi, Bojan Karlas, Muhsen Owaida, Ce Zhang, Ankit Singla
2018	—	`conf`	Patient Risk Assessment and Warning Symptom Detection Using Deep Attention-Based Neural Networks. Louhi@EMNLP Ivan Girardi, Pengfei Ji, An-phi Nguyen, Nora Hollenstein, Adam Ivankay, Lorenz Kuhn, Chiara Marchiori, Ce Zhang
2018	J	`jnl`	Patient Risk Assessment and Warning Symptom Detection Using Deep Attention-Based Neural Networks. CoRR Ivan Girardi, Pengfei Ji, An-phi Nguyen, Nora Hollenstein, Adam Ivankay, Lorenz Kuhn, Chiara Marchiori, Ce Zhang
2018	B	`conf`	Synchronous Multi-GPU Training for Deep Learning with Low-Precision Communications: An Empirical Study. EDBT Demjan Grubic, Leo Tam, Dan Alistarh, Ce Zhang
2018	J	`jnl`	Using transfer learning to detect galaxy mergers. CoRR Sandro Ackermann, Kevin Schawinski, Ce Zhang, Anna K. Weigel, M. Dennis Turp
2017	J	`jnl`	An Experimental Evaluation of SimRank-based Similarity Search Algorithms. Proc. VLDB Endow. Zhipeng Zhang, Yingxia Shao, Bin Cui, Ce Zhang
2017	—	`conf`	An Overreaction to the Broken Machine Learning Abstraction: The ease.ml Vision. HILDA@SIGMOD Ce Zhang, Wentao Wu, Tian Li
2017	J	`jnl`	Asynchronous Decentralized Parallel Stochastic Gradient Descent. CoRR Xiangru Lian, Wei Zhang, Ce Zhang, Ji Liu
2017	—	`conf`	Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent. NIPS Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, Ji Liu
2017	J	`jnl`	Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent. CoRR Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, Ji Liu
2017	J	`jnl`	DeepDive: declarative knowledge base construction. Commun. ACM Ce Zhang, Christopher Ré, Michael J. Cafarella, Jaeho Shin, Feiran Wang, Sen Wu
2017	J	`jnl`	Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads. CoRR Tian Li, Jie Zhong, Ji Liu, Wentao Wu, Ce Zhang
2017	Misc	`conf`	FPGA-Accelerated Dense Linear Machine Learning: A Precision-Convergence Trade-Off. FCCM Kaan Kara, Dan Alistarh, Gustavo Alonso, Onur Mutlu, Ce Zhang
2017	J	`jnl`	Generative Adversarial Networks recover features in astrophysical images of galaxies beyond the deconvolution limit. CoRR Kevin Schawinski, Ce Zhang, Hantian Zhang, Lucas Fowler, Gokula Krishnan Santhanam
2017	—	`conf`	Heterogeneity-aware Distributed Parameter Servers. SIGMOD Conference Jiawei Jiang, Bin Cui, Ce Zhang, Lele Yu
2017	J	`jnl`	How Good Are Machine Learning Clouds for Binary Classification with Good Features? CoRR Hantian Zhang, Luyuan Zeng, Wentao Wu, Ce Zhang
2017	—	`conf`	How good are machine learning clouds for binary classification with good features?: extended abstract. SoCC Hantian Zhang, Luyuan Zeng, Wentao Wu, Ce Zhang
2017	J	`jnl`	Incremental knowledge base construction using DeepDive. VLDB J. Christopher De Sa, Alexander Ratner, Christopher Ré, Jaeho Shin, Feiran Wang, Sen Wu, Ce Zhang
2017	J	`jnl`	LDA*: A Robust and Large-scale Topic Modeling System. Proc. VLDB Endow. Lele Yu, Bin Cui, Ce Zhang, Yingxia Shao
2017	J	`jnl`	Layerwise Systematic Scan: Deep Boltzmann Machines and Beyond. CoRR Heng Guo, Kaan Kara, Ce Zhang
2017	J	`jnl`	MLog: Towards Declarative In-Database Machine Learning. Proc. VLDB Endow. Xupeng Li, Bin Cui, Yiru Chen, Wentao Wu, Ce Zhang
2017	Misc	`conf`	Predicting Non-Small Cell Lung Cancer Diagnosis and Prognosis by Fully Automated Microscopic Pathology Image Features. AMIA Kun-Hsing Yu, Ce Zhang, Gerald J. Berry, Russ B. Altman, Christopher Ré, Daniel L. Rubin, Michael Snyder
2017	B	`conf`	Scalable inference of decision tree ensembles: Flexible design for CPU-FPGA platforms. FPL Muhsen Owaida, Hantian Zhang, Ce Zhang, Gustavo Alonso
2017	A*	`conf`	TencentBoost: A Gradient Boosting Tree System with Parameter Server. ICDE Jie Jiang, Jiawei Jiang, Bin Cui, Ce Zhang
2017	A*	`conf`	ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning. ICML Hantian Zhang, Jerry Li, Kaan Kara, Dan Alistarh, Ji Liu, Ce Zhang
2016	—	`conf`	Android malware development on public malware scanning platforms: A large-scale data-driven study. IEEE BigData Heqing Huang, Cong Zheng, Junyuan Zeng, Wu Zhou, Sencun Zhu, Peng Liu, Suresh Chari, Ce Zhang
2016	J	`jnl`	Asynchrony begets Momentum, with an Application to Deep Learning. CoRR Ioannis Mitliagkas, Ce Zhang, Stefan Hadjis, Christopher Ré
2016	—	`conf`	Asynchrony begets momentum, with an application to deep learning. Allerton Ioannis Mitliagkas, Ce Zhang, Stefan Hadjis, Christopher Ré
2016	J	`jnl`	CYCLADES: Conflict-free Asynchronous Machine Learning. CoRR Xinghao Pan, Maximilian Lam, Stephen Tu, Dimitris S. Papailiopoulos, Ce Zhang, Michael I. Jordan, Kannan Ramchandran, Christopher Ré, Benjamin Recht
2016	J	`jnl`	DeepDive: Declarative Knowledge Base Construction. SIGMOD Rec. Christopher De Sa, Alexander Ratner, Christopher Ré, Jaeho Shin, Feiran Wang, Sen Wu, Ce Zhang
2016	—	`conf`	Extracting Databases from Dark Data with DeepDive. SIGMOD Conference Ce Zhang, Jaeho Shin, Christopher Ré, Michael J. Cafarella, Feng Niu
2016	J	`jnl`	Large-scale extraction of gene interactions from full-text literature using DeepDive. Bioinform. Emily K. Mallory, Ce Zhang, Christopher Ré, Russ B. Altman
2016	J	`jnl`	Materialization Optimizations for Feature Selection Workloads. ACM Trans. Database Syst. Ce Zhang, Arun Kumar, Christopher Ré
2016	J	`jnl`	Omnivore: An Optimizer for Multi-device Deep Learning on CPUs and GPUs. CoRR Stefan Hadjis, Ce Zhang, Ioannis Mitliagkas, Christopher Ré
2016	J	`jnl`	ZipML: An End-to-end Bitwise Framework for Dense Generalized Linear Models. CoRR Hantian Zhang, Kaan Kara, Jerry Li, Dan Alistarh, Ji Liu, Ce Zhang
2015	J	`jnl`	Building a Large-scale Multimodal Knowledge Base for Visual Question Answering. CoRR Yuke Zhu, Ce Zhang, Christopher Ré, Li Fei-Fei
2015	—	`conf`	Caffe con Troll: Shallow Ideas to Speed Up Deep Learning. DanaC@SIGMOD Stefan Hadjis, Firas Abuzaid, Ce Zhang, Christopher Ré
2015	J	`jnl`	Caffe con Troll: Shallow Ideas to Speed Up Deep Learning. CoRR Firas Abuzaid, Stefan Hadjis, Ce Zhang, Christopher Ré
2015	J	`jnl`	Incremental Knowledge Base Construction Using DeepDive. CoRR Sen Wu, Ce Zhang, Feiran Wang, Christopher Ré
2015	J	`jnl`	Incremental Knowledge Base Construction Using DeepDive. Proc. VLDB Endow. Jaeho Shin, Sen Wu, Feiran Wang, Christopher De Sa, Ce Zhang, Christopher Ré
2015	—	`conf`	Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width. NIPS Christopher De Sa, Ce Zhang, Kunle Olukotun, Christopher Ré
2015	J	`jnl`	Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width. CoRR Christopher De Sa, Ce Zhang, Kunle Olukotun, Christopher Ré
2015	J	`jnl`	Taming the Wild: A Unified Analysis of Hogwild!-Style Algorithms. CoRR Christopher De Sa, Ce Zhang, Kunle Olukotun, Christopher Ré
2015	—	`conf`	Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms. NIPS Christopher De Sa, Ce Zhang, Kunle Olukotun, Christopher Ré
2014	J	`jnl`	A machine-compiled macroevolutionary history of Phanerozoic life. CoRR Shanan Peters, Ce Zhang, Miron Livny, Christopher Ré
2014	J	`jnl`	DimmWitted: A Study of Main-Memory Statistical Analytics. CoRR Ce Zhang, Christopher Ré
2014	J	`jnl`	DimmWitted: A Study of Main-Memory Statistical Analytics. Proc. VLDB Endow. Ce Zhang, Christopher Ré
2014	J	`jnl`	Feature Engineering for Knowledge Base Construction. CoRR Ce Zhang, Christopher Ré, Amir Abbas Sadeghian, Zifei Shan, Jaeho Shin, Feiran Wang, Sen Wu
2014	J	`jnl`	Feature Engineering for Knowledge Base Construction. IEEE Data Eng. Bull. Christopher Ré, Amir Abbas Sadeghian, Zifei Shan, Jaeho Shin, Feiran Wang, Sen Wu, Ce Zhang
2014	—	`conf`	Materialization optimizations for feature selection workloads. SIGMOD Conference Ce Zhang, Arun Kumar, Christopher Ré
2014	—	`conf`	Parallel Feature Selection Inspired by Group Testing. NIPS Yingbo Zhou, Utkarsh Porwal, Ce Zhang, Hung Q. Ngo, XuanLong Nguyen, Christopher Ré, Venu Govindaraju
2014	—	`conf`	Tradeoffs in Main-Memory Statistical Analytics from Impala to DimmWitted. IMDM@VLDB Victor Bittorf, Marcel Kornacker, Christopher Ré, Ce Zhang
2013	B	`conf`	A Markov logic framework for recognizing complex events from multimodal data. ICMI Young Chol Song, Henry A. Kautz, James F. Allen, Mary D. Swift, Yuncheng Li, Jiebo Luo, Ce Zhang
2013	—	`conf`	An Approximate, Efficient LP Solver for LP Rounding. NIPS Srikrishna Sridhar, Stephen J. Wright, Christopher Ré, Ji Liu, Victor Bittorf, Ce Zhang
2013	J	`jnl`	An Approximate, Efficient Solver for LP Rounding. CoRR Srikrishna Sridhar, Victor Bittorf, Ji Liu, Ce Zhang, Christopher Ré, Stephen J. Wright
2013	—	`conf`	Bootstrapping Knowledge Base Acceleration. TREC Tushar Khot, Ce Zhang, Jude W. Shavlik, Sriraam Natarajan, Christopher Ré
2013	A	`conf`	Brainwash: A Data System for Feature Engineering. CIDR Michael R. Anderson, Dolan Antenucci, Victor Bittorf, Matthew Burgess, Michael J. Cafarella, Arun Kumar, Feng Niu, Yongjoo Park, Christopher Ré, Ce Zhang
2013	—	`conf`	Evaluating Stream Filtering for Entity Profile Updates for TREC 2013. TREC John R. Frank, Steven J. Bauer, Max Kleiman-Weiner, Daniel A. Roberts, Nilesh Tripuraneni, Ce Zhang, Christopher Ré, Ellen M. Voorhees, Ian Soboroff
2013	—	`conf`	GeoDeepDive: statistical inference using familiar data-processing languages. SIGMOD Conference Ce Zhang, Vidhya Govindaraju, Jackson Borchardt, Tim Foltz, Christopher Ré, Shanan Peters
2013	—	`conf`	Towards high-throughput gibbs sampling at scale: a study across storage managers. SIGMOD Conference Ce Zhang, Christopher Ré
2013	—	`conf`	Understanding Tables in Context Using Standard NLP Toolkits. ACL (2) Vidhya Govindaraju, Ce Zhang, Christopher Ré
2012	—	`conf`	Big Data versus the Crowd: Looking for Relationships in All the Right Places. ACL (1) Ce Zhang, Feng Niu, Christopher Ré, Jude W. Shavlik
2012	—	`conf`	Building an Entity-Centric Stream Filtering Test Collection for TREC 2012. TREC John R. Frank, Max Kleiman-Weiner, Daniel A. Roberts, Feng Niu, Ce Zhang, Christopher Ré, Ian Soboroff
2012	—	`conf`	DeepDive: Web-scale Knowledge-base Construction using Statistical Learning and Inference. VLDS Feng Niu, Ce Zhang, Christopher Ré, Jude W. Shavlik
2012	J	`jnl`	Elementary: Large-Scale Knowledge-Base Construction via Machine Learning and Statistical Inference. Int. J. Semantic Web Inf. Syst. Feng Niu, Ce Zhang, Christopher Ré, Jude W. Shavlik
2012	A*	`conf`	Scaling Inference for Markov Logic via Dual Decomposition. ICDM Feng Niu, Ce Zhang, Christopher Ré, Jude W. Shavlik
2011	J	`jnl`	Felix: Scaling Inference for Markov Logic with an Operator-based Approach CoRR Feng Niu, Ce Zhang, Christopher Ré, Jude W. Shavlik
2011	—	`conf`	Modeling User Expertise in Folksonomies by Fusing Multi-type Features. DASFAA (1) Junjie Yao, Bin Cui, Qiaosha Han, Ce Zhang, Yanhong Zhou
2010	A*	`conf`	Content-enriched classifier for web video classification. SIGIR Bin Cui, Ce Zhang, Gao Cong
2010	—	`conf`	Multiple feature fusion for social media applications. SIGMOD Conference Bin Cui, Anthony K. H. Tung, Ce Zhang, Zhe Zhao
2009	B	`conf`	A Revisit of Query Expansion with Different Semantic Levels. DASFAA Ce Zhang, Bin Cui, Gao Cong, Yu-Jing Wang
2009	A	`conf`	The use of categorization information in language models for question retrieval. CIKM Xin Cao, Gao Cong, Bin Cui, Christian S. Jensen, Ce Zhang
2009	B	`conf`	Video Annotation System Based on Categorizing and Keyword Labelling. DASFAA Bin Cui, Bei Pan, Heng Tao Shen, Ying Wang, Ce Zhang
2008	A*	`conf`	Semantic similarity based on compact concept ontology. WWW Ce Zhang, Yu-Jing Wang, Bin Cui, Gao Cong