Zhewei Yao - RankMe

110 papers A* 25A 1C 1Misc 1Journal 71Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Agent World Model: Infinity Synthetic Environments for Agentic Reinforcement Learning. CoRR Zhaoyang Wang, Canwen Xu, Boyi Liu, Yite Wang, Siwei Han, Zhewei Yao, Huaxiu Yao, Yuxiong He
2026	J	`jnl`	DARE-bench: Evaluating Modeling and Instruction Fidelity of LLMs in Data Science. CoRR Fan Shu, Yite Wang, Ruofan Wu, Boyi Liu, Zhewei Yao, Yuxiong He, Feng Yan
2026	J	`jnl`	Learning to Self-Evolve. CoRR Xiaoyin Chen, Canwen Xu, Yite Wang, Boyi Liu, Zhewei Yao, Yuxiong He
2026	—	`conf`	TAGQuant: Token-Aware Clustering for Group-Wise Quantization. EACL (Industry Track) Jaeseong Lee, Seung-won Hwang, Aurick Qiao, Zhewei Yao, Yuxiong He
2026	J	`jnl`	Training a Large Language Model for Medical Coding Using Privacy-Preserving Synthetic Clinical Data. CoRR John Cook, Michael Wyatt, Peng Wei, Iris Chin, Santosh Gupta, Van Zyl Van Vuuren, Richie Siburian, Amanda Spicer, Kristen Viviano, Alda Cami, Raunaq Malhotra, Zhewei Yao, Jeff Rasley, Gaurav Kaushik
2025	J	`jnl`	Agentic Verification for Ambiguous Query Disambiguation. CoRR Youngwon Lee, Seung-won Hwang, Ruofan Wu, Feng Yan, Danmei Xu, Moutasem Akkad, Zhewei Yao, Yuxiong He
2025	J	`jnl`	Arctic Long Sequence Training: Scalable And Efficient Training For Multi-Million Token Sequences. CoRR Stas Bekman, Samyam Rajbhandari, Michael Wyatt, Jeff Rasley, Tunji Ruwase, Zhewei Yao, Aurick Qiao, Yuxiong He
2025	J	`jnl`	Arctic-Text2SQL-R1: Simple Rewards, Strong Reasoning in Text-to-SQL. CoRR Zhewei Yao, Guoheng Sun, Lukasz Borchmann, Zheyu Shen, Minghang Deng, Bohan Zhai, Hao Zhang, Ang Li, Yuxiong He
2025	—	`conf`	CORD: Balancing COnsistency and Rank Distillation for Robust Retrieval-Augmented Generation. NAACL (Short Papers) Youngwon Lee, Seung-won Hwang, Daniel F. Campos, Filip Gralinski, Zhewei Yao, Yuxiong He
2025	J	`jnl`	ComposeRAG: A Modular and Composable RAG for Corpus-Grounded Multi-Hop Question Answering. CoRR Ruofan Wu, Youngwon Lee, Fan Shu, Danmei Xu, Seung-won Hwang, Zhewei Yao, Yuxiong He, Feng Yan
2025	J	`jnl`	ExCoT: Optimizing Reasoning for Text-to-SQL with Execution Feedback. CoRR Bohan Zhai, Canwen Xu, Yuxiong He, Zhewei Yao
2025	—	`conf`	Inference Scaling for Bridging Retrieval and Augmented Generation. NAACL (Findings) Youngwon Lee, Seung-won Hwang, Daniel F. Campos, Filip Gralinski, Zhewei Yao, Yuxiong He
2025	J	`jnl`	MedOrch: Medical Diagnosis with Tool-Augmented Reasoning Agents for Flexible Extensibility. CoRR Yexiao He, Ang Li, Boyi Liu, Zhewei Yao, Yuxiong He
2025	—	`conf`	Optimizing Reasoning for Text-to-SQL with Execution Feedback. ACL (Findings) Bohan Zhai, Canwen Xu, Yuxiong He, Zhewei Yao
2025	J	`jnl`	ReFoRCE: A Text-to-SQL Agent with Self-Refinement, Format Restriction, and Column Exploration. CoRR Minghang Deng, Ashwin Ramachandran, Canwen Xu, Lanxiang Hu, Zhewei Yao, Anupam Datta, Hao Zhang
2025	J	`jnl`	RenAIssance: A Survey Into AI Text-to-Image Generation in the Era of Large Model. IEEE Trans. Pattern Anal. Mach. Intell. Fengxiang Bie, Yibo Yang, Zhongzhu Zhou, Adam Ghanem, Minjia Zhang, Zhewei Yao, Xiaoxia Wu, Connor Holmes, Pareesa Ameneh Golnari, David A. Clifton, Yuxiong He, Dacheng Tao, Shuaiwen Leon Song
2025	—	`conf`	STUN: Structured-Then-Unstructured Pruning for Scalable MoE Pruning. ACL (1) Jaeseong Lee, Seung-won Hwang, Aurick Qiao, Daniel F. Campos, Zhewei Yao, Yuxiong He
2025	A*	`conf`	SwiftKV: Fast Prefill-Optimized Inference with Knowledge-Preserving Model Transformation. EMNLP Aurick Qiao, Zhewei Yao, Samyam Rajbhandari, Yuxiong He
2025	J	`jnl`	TALE: Token-Adaptive Low-Rank KVCache Approximation with Reconstruction Elimination. Trans. Assoc. Comput. Linguistics Jaeseong Lee, Seung-won Hwang, Aurick Qiao, Daniel F. Campos, Zhewei Yao, Yuxiong He
2024	J	`jnl`	AI and Memory Wall. CoRR Amir Gholami, Zhewei Yao, Sehoon Kim, Coleman Hooper, Michael W. Mahoney, Kurt Keutzer
2024	J	`jnl`	AI and Memory Wall. IEEE Micro Amir Gholami, Zhewei Yao, Sehoon Kim, Coleman Hooper, Michael W. Mahoney, Kurt Keutzer
2024	J	`jnl`	CORD: Balancing COnsistency and Rank Distillation for Robust Retrieval-Augmented Generation. CoRR Youngwon Lee, Seung-won Hwang, Daniel F. Campos, Filip Gralinski, Zhewei Yao, Yuxiong He
2024	A*	`conf`	DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routing. AAAI Conglong Li, Zhewei Yao, Xiaoxia Wu, Minjia Zhang, Connor Holmes, Cheng Li, Yuxiong He
2024	A*	`conf`	Exploring Post-training Quantization in LLMs from Comprehensive Study to Low Rank Compensation. AAAI Zhewei Yao, Xiaoxia Wu, Cheng Li, Stephen Youn, Yuxiong He
2024	J	`jnl`	FP6-LLM: Efficiently Serving Large Language Models Through FP6-Centric Algorithm-System Co-Design. CoRR Haojun Xia, Zhen Zheng, Xiaoxia Wu, Shiyang Chen, Zhewei Yao, Stephen Youn, Arash Bakhtiari, Michael Wyatt, Donglin Zhuang, Zhongzhu Zhou, Olatunji Ruwase, Yuxiong He, Shuaiwen Leon Song
2024	A*	`conf`	Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding. NeurIPS Zhenyu Zhang, Runjin Chen, Shiwei Liu, Zhewei Yao, Olatunji Ruwase, Beidi Chen, Xiaoxia Wu, Zhangyang Wang
2024	J	`jnl`	Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding. CoRR Zhenyu Zhang, Runjin Chen, Shiwei Liu, Zhewei Yao, Olatunji Ruwase, Beidi Chen, Xiaoxia Wu, Zhangyang Wang
2024	J	`jnl`	Inference Scaling for Bridging Retrieval and Augmented Generation. CoRR Youngwon Lee, Seung-won Hwang, Daniel F. Campos, Filip Gralinski, Zhewei Yao, Yuxiong He
2024	—	`conf`	Quant-LLM: Accelerating the Serving of Large Language Models via FP6-Centric Algorithm-System Co-Design on Modern GPUs. USENIX ATC Haojun Xia, Zhen Zheng, Xiaoxia Wu, Shiyang Chen, Zhewei Yao, Stephen Youn, Arash Bakhtiari, Michael Wyatt, Donglin Zhuang, Zhongzhu Zhou, Olatunji Ruwase, Yuxiong He, Shuaiwen Leon Song
2024	J	`jnl`	STUN: Structured-Then-Unstructured Pruning for Scalable MoE Pruning. CoRR Jaeseong Lee, Seung-won Hwang, Aurick Qiao, Daniel F. Campos, Zhewei Yao, Yuxiong He
2024	J	`jnl`	SwiftKV: Fast Prefill-Optimized Inference with Knowledge-Preserving Model Transformation. CoRR Aurick Qiao, Zhewei Yao, Samyam Rajbhandari, Yuxiong He
2024	A*	`conf`	ZeRO++: Extremely Efficient Collective Communication for Large Model Training. ICLR Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Xiaoxia Wu, Connor Holmes, Zhewei Yao, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He
2023	J	`jnl`	A Comprehensive Study on Post-Training Quantization for Large Language Models. CoRR Zhewei Yao, Cheng Li, Xiaoxia Wu, Stephen Youn, Yuxiong He
2023	J	`jnl`	DeepSpeed-Chat: Easy, Fast and Affordable RLHF Training of ChatGPT-like Models at All Scales. CoRR Zhewei Yao, Reza Yazdani Aminabadi, Olatunji Ruwase, Samyam Rajbhandari, Xiaoxia Wu, Ammar Ahmad Awan, Jeff Rasley, Minjia Zhang, Conglong Li, Connor Holmes, Zhongzhu Zhou, Michael Wyatt, Molly Smith, Lev Kurilenko, Heyang Qin, Masahiro Tanaka, Shuai Che, Shuaiwen Leon Song, Yuxiong He
2023	J	`jnl`	DeepSpeed-VisualChat: Multi-Round Multi-Image Interleave Chat via Multi-Modal Causal Attention. CoRR Zhewei Yao, Xiaoxia Wu, Conglong Li, Minjia Zhang, Heyang Qin, Olatunji Ruwase, Ammar Ahmad Awan, Samyam Rajbhandari, Yuxiong He
2023	A*	`conf`	DySR: Adaptive Super-Resolution via Algorithm and System Co-design. ICLR Syed Zawad, Cheng Li, Zhewei Yao, Elton Zheng, Yuxiong He, Feng Yan
2023	J	`jnl`	RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Model. CoRR Fengxiang Bie, Yibo Yang, Zhongzhu Zhou, Adam Ghanem, Minjia Zhang, Zhewei Yao, Xiaoxia Wu, Connor Holmes, Pareesa Ameneh Golnari, David A. Clifton, Yuxiong He, Dacheng Tao, Shuaiwen Leon Song
2023	—	`conf`	Scaling Vision-Language Models with Sparse Mixture of Experts. EMNLP (Findings) Sheng Shen, Zhewei Yao, Chunyuan Li, Trevor Darrell, Kurt Keutzer, Yuxiong He
2023	J	`jnl`	Scaling Vision-Language Models with Sparse Mixture of Experts. CoRR Sheng Shen, Zhewei Yao, Chunyuan Li, Trevor Darrell, Kurt Keutzer, Yuxiong He
2023	J	`jnl`	Selective Guidance: Are All the Denoising Steps of Guided Diffusion Important? CoRR Pareesa Ameneh Golnari, Zhewei Yao, Yuxiong He
2023	J	`jnl`	Understanding INT4 Quantization for Transformer Models: Latency Speedup, Composability, and Failure Cases. CoRR Xiaoxia Wu, Cheng Li, Reza Yazdani Aminabadi, Zhewei Yao, Yuxiong He
2023	A*	`conf`	Understanding Int4 Quantization for Language Models: Latency Speedup, Composability, and Failure Cases. ICML Xiaoxia Wu, Cheng Li, Reza Yazdani Aminabadi, Zhewei Yao, Yuxiong He
2023	J	`jnl`	ZeroQuant(4+2): Redefining LLMs Quantization with a New FP6-Centric Strategy for Diverse Generative Tasks. CoRR Xiaoxia Wu, Haojun Xia, Stephen Youn, Zhen Zheng, Shiyang Chen, Arash Bakhtiari, Michael Wyatt, Reza Yazdani Aminabadi, Yuxiong He, Olatunji Ruwase, Leon Song, Zhewei Yao
2023	J	`jnl`	ZeroQuant-FP: A Leap Forward in LLMs Post-Training W4A8 Quantization Using Floating-Point Formats. CoRR Xiaoxia Wu, Zhewei Yao, Yuxiong He
2023	J	`jnl`	ZeroQuant-HERO: Hardware-Enhanced Robust Optimized Post-Training Quantization Framework for W8A8 Transformers. CoRR Zhewei Yao, Reza Yazdani Aminabadi, Stephen Youn, Xiaoxia Wu, Elton Zheng, Yuxiong He
2022	J	`jnl`	BiFeat: Supercharge GNN Training via Graph Feature Quantization. CoRR Yuxin Ma, Ping Gong, Jun Yi, Zhewei Yao, Minjie Wang, Cheng Li, Yuxiong He, Feng Yan
2022	J	`jnl`	DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routing. CoRR Conglong Li, Zhewei Yao, Xiaoxia Wu, Minjia Zhang, Connor Holmes, Cheng Li, Yuxiong He
2022	A*	`conf`	DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale. ICML Samyam Rajbhandari, Conglong Li, Zhewei Yao, Minjia Zhang, Reza Yazdani Aminabadi, Ammar Ahmad Awan, Jeff Rasley, Yuxiong He
2022	J	`jnl`	DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale. CoRR Samyam Rajbhandari, Conglong Li, Zhewei Yao, Minjia Zhang, Reza Yazdani Aminabadi, Ammar Ahmad Awan, Jeff Rasley, Yuxiong He
2022	J	`jnl`	Extreme Compression for Pre-trained Transformers Made Simple and Efficient. CoRR Xiaoxia Wu, Zhewei Yao, Minjia Zhang, Conglong Li, Yuxiong He
2022	A	`conf`	Hessian-Aware Pruning and Optimal Neural Implant. WACV Shixing Yu, Zhewei Yao, Amir Gholami, Zhen Dong, Sehoon Kim, Michael W. Mahoney, Kurt Keutzer
2022	A*	`conf`	How Much Can CLIP Benefit Vision-and-Language Tasks? ICLR Sheng Shen, Liunian Harold Li, Hao Tan, Mohit Bansal, Anna Rohrbach, Kai-Wei Chang, Zhewei Yao, Kurt Keutzer
2022	Misc	`conf`	Integer-Only Zero-Shot Quantization for Efficient Speech Recognition. ICASSP Sehoon Kim, Amir Gholami, Zhewei Yao, Nicholas Lee, Patrick Wang, Aniruddha Nrusimha, Bohan Zhai, Tianren Gao, Michael W. Mahoney, Kurt Keutzer
2022	J	`jnl`	Random-LTD: Random and Layerwise Token Dropping Brings Efficient Training for Large-scale Transformers. CoRR Zhewei Yao, Xiaoxia Wu, Conglong Li, Connor Holmes, Minjia Zhang, Cheng Li, Yuxiong He
2022	A*	`conf`	XTC: Extreme Compression for Pre-trained Transformers Made Simple and Efficient. NeurIPS Xiaoxia Wu, Zhewei Yao, Minjia Zhang, Conglong Li, Yuxiong He
2022	A*	`conf`	ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers. NeurIPS Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, Xiaoxia Wu, Conglong Li, Yuxiong He
2022	J	`jnl`	ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers. CoRR Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, Xiaoxia Wu, Conglong Li, Yuxiong He
2021	J	`jnl`	A Survey of Quantization Methods for Efficient Neural Network Inference. CoRR Amir Gholami, Sehoon Kim, Zhen Dong, Zhewei Yao, Michael W. Mahoney, Kurt Keutzer
2021	A*	`conf`	ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning. AAAI Zhewei Yao, Amir Gholami, Sheng Shen, Mustafa Mustafa, Kurt Keutzer, Michael W. Mahoney
2021	A*	`conf`	ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training. ICML Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael W. Mahoney, Joseph Gonzalez
2021	J	`jnl`	ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training. CoRR Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael W. Mahoney, Joseph E. Gonzalez
2021	A*	`conf`	HAWQ-V3: Dyadic Neural Network Quantization. ICML Zhewei Yao, Zhen Dong, Zhangcheng Zheng, Amir Gholami, Jiali Yu, Eric Tan, Leyuan Wang, Qijing Huang, Yida Wang, Michael W. Mahoney, Kurt Keutzer
2021	J	`jnl`	Hessian-Aware Pruning and Optimal Neural Implant. CoRR Shixing Yu, Zhewei Yao, Amir Gholami, Zhen Dong, Michael W. Mahoney, Kurt Keutzer
2021	J	`jnl`	How Much Can CLIP Benefit Vision-and-Language Tasks? CoRR Sheng Shen, Liunian Harold Li, Hao Tan, Mohit Bansal, Anna Rohrbach, Kai-Wei Chang, Zhewei Yao, Kurt Keutzer
2021	A*	`conf`	I-BERT: Integer-only BERT Quantization. ICML Sehoon Kim, Amir Gholami, Zhewei Yao, Michael W. Mahoney, Kurt Keutzer
2021	J	`jnl`	I-BERT: Integer-only BERT Quantization. CoRR Sehoon Kim, Amir Gholami, Zhewei Yao, Michael W. Mahoney, Kurt Keutzer
2021	—	`conf`	Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models. IEEE BigData Zhengming Zhang, Yaoqing Yang, Zhewei Yao, Yujun Yan, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney
2021	J	`jnl`	Inexact Nonconvex Newton-Type Methods. INFORMS J. Optim. Zhewei Yao, Peng Xu, Fred Roosta, Michael W. Mahoney
2021	J	`jnl`	MLPruning: A Multilevel Structured Pruning Framework for Transformer-based Models. CoRR Zhewei Yao, Linjian Ma, Sheng Shen, Kurt Keutzer, Michael W. Mahoney
2021	J	`jnl`	Q-ASR: Integer-only Zero-shot Quantization for Efficient Speech Recognition. CoRR Sehoon Kim, Amir Gholami, Zhewei Yao, Aniruddha Nrusimha, Bohan Zhai, Tianren Gao, Michael W. Mahoney, Kurt Keutzer
2021	—	`conf`	What's Hidden in a One-layer Randomly Weighted Transformer? EMNLP (1) Sheng Shen, Zhewei Yao, Douwe Kiela, Kurt Keutzer, Michael W. Mahoney
2021	J	`jnl`	What's Hidden in a One-layer Randomly Weighted Transformer? CoRR Sheng Shen, Zhewei Yao, Douwe Kiela, Kurt Keutzer, Michael W. Mahoney
2020	A*	`conf`	A Statistical Framework for Low-bitwidth Training of Deep Neural Networks. NeurIPS Jianfei Chen, Yu Gai, Zhewei Yao, Michael W. Mahoney, Joseph E. Gonzalez
2020	J	`jnl`	A Statistical Framework for Low-bitwidth Training of Deep Neural Networks. CoRR Jianfei Chen, Yu Gai, Zhewei Yao, Michael W. Mahoney, Joseph E. Gonzalez
2020	J	`jnl`	ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning. CoRR Zhewei Yao, Amir Gholami, Sheng Shen, Kurt Keutzer, Michael W. Mahoney
2020	J	`jnl`	Benchmarking Semi-supervised Federated Learning. CoRR Zhengming Zhang, Zhewei Yao, Yaoqing Yang, Yujun Yan, Joseph E. Gonzalez, Michael W. Mahoney
2020	A*	`conf`	HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks. NeurIPS Zhen Dong, Zhewei Yao, Daiyaan Arfeen, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
2020	J	`jnl`	HAWQV3: Dyadic Neural Network Quantization. CoRR Zhewei Yao, Zhen Dong, Zhangcheng Zheng, Amir Gholami, Jiali Yu, Eric Tan, Leyuan Wang, Qijing Huang, Yida Wang, Michael W. Mahoney, Kurt Keutzer
2020	A*	`conf`	Inefficiency of K-FAC for Large Batch Size Training. AAAI Linjian Ma, Gabe Montague, Jiayu Ye, Zhewei Yao, Amir Gholami, Kurt Keutzer, Michael W. Mahoney
2020	C	`conf`	JumpReLU: A Retrofit Defense Strategy for Adversarial Attacks. ICPRAM N. Benjamin Erichson, Zhewei Yao, Michael W. Mahoney
2020	—	`conf`	MAF: Multimodal Alignment Framework for Weakly-Supervised Phrase Grounding. EMNLP (1) Qinxin Wang, Hao Tan, Sheng Shen, Michael W. Mahoney, Zhewei Yao
2020	J	`jnl`	MAF: Multimodal Alignment Framework for Weakly-Supervised Phrase Grounding. CoRR Qinxin Wang, Hao Tan, Sheng Shen, Michael W. Mahoney, Zhewei Yao
2020	A*	`conf`	PowerNorm: Rethinking Batch Normalization in Transformers. ICML Sheng Shen, Zhewei Yao, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
2020	—	`conf`	PyHessian: Neural Networks Through the Lens of the Hessian. IEEE BigData Zhewei Yao, Amir Gholami, Kurt Keutzer, Michael W. Mahoney
2020	A*	`conf`	Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT. AAAI Sheng Shen, Zhen Dong, Jiayu Ye, Linjian Ma, Zhewei Yao, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
2020	J	`jnl`	Rethinking Batch Normalization in Transformers. CoRR Sheng Shen, Zhewei Yao, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
2020	A*	`conf`	ZeroQ: A Novel Zero Shot Quantization Framework. CVPR Yaohui Cai, Zhewei Yao, Zhen Dong, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
2020	J	`jnl`	ZeroQ: A Novel Zero Shot Quantization Framework. CoRR Yaohui Cai, Zhewei Yao, Zhen Dong, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
2019	J	`jnl`	ANODEV2: A Coupled Neural ODE Evolution Framework. CoRR Tianjun Zhang, Zhewei Yao, Amir Gholami, Kurt Keutzer, Joseph Gonzalez, George Biros, Michael W. Mahoney
2019	A*	`conf`	ANODEV2: A Coupled Neural ODE Framework. NeurIPS Tianjun Zhang, Zhewei Yao, Amir Gholami, Joseph E. Gonzalez, Kurt Keutzer, Michael W. Mahoney, George Biros
2019	J	`jnl`	HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks. CoRR Zhen Dong, Zhewei Yao, Yaohui Cai, Daiyaan Arfeen, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
2019	A*	`conf`	HAWQ: Hessian AWare Quantization of Neural Networks With Mixed-Precision. ICCV Zhen Dong, Zhewei Yao, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
2019	J	`jnl`	HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precision. CoRR Zhen Dong, Zhewei Yao, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
2019	J	`jnl`	Inefficiency of K-FAC for Large Batch Size Training. CoRR Linjian Ma, Gabe Montague, Jiayu Ye, Zhewei Yao, Amir Gholami, Kurt Keutzer, Michael W. Mahoney
2019	J	`jnl`	JumpReLU: A Retrofit Defense Strategy for Adversarial Attacks. CoRR N. Benjamin Erichson, Zhewei Yao, Michael W. Mahoney
2019	J	`jnl`	PyHessian: Neural Networks Through the Lens of the Hessian. CoRR Zhewei Yao, Amir Gholami, Kurt Keutzer, Michael W. Mahoney
2019	J	`jnl`	Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT. CoRR Sheng Shen, Zhen Dong, Jiayu Ye, Linjian Ma, Zhewei Yao, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
2019	J	`jnl`	Residual Networks as Nonlinear Systems: Stability Analysis using Linearization. CoRR Kai Rothauge, Zhewei Yao, Zixi Hu, Michael W. Mahoney
2019	J	`jnl`	Shallow Learning for Fluid Flow Reconstruction with Limited Sensors and Limited Data. CoRR N. Benjamin Erichson, Lionel Mathelin, Zhewei Yao, Steven L. Brunton, Michael W. Mahoney, J. Nathan Kutz
2019	A*	`conf`	Trust Region Based Adversarial Attack on Neural Networks. CVPR Zhewei Yao, Amir Gholami, Peng Xu, Kurt Keutzer, Michael W. Mahoney
2019	J	`jnl`	改进型循环生成对抗网络的血管内超声图像增强 (Improved CycleGANs for Intravascular Ultrasound Image Enhancement). 计算机科学 Zhewei Yao, Feng Yang, Jing Huang, Yaqin Liu
2018	A*	`conf`	Hessian-based Analysis of Large Batch Training and Robustness to Adversaries. NeurIPS Zhewei Yao, Amir Gholami, Qi Lei, Kurt Keutzer, Michael W. Mahoney
2018	J	`jnl`	Hessian-based Analysis of Large Batch Training and Robustness to Adversaries. CoRR Zhewei Yao, Amir Gholami, Qi Lei, Kurt Keutzer, Michael W. Mahoney
2018	J	`jnl`	Large batch size training of neural networks with adversarial training and second-order information. CoRR Zhewei Yao, Amir Gholami, Kurt Keutzer, Michael W. Mahoney
2018	J	`jnl`	On the Computational Inefficiency of Large Batch Sizes for Stochastic Gradient Descent. CoRR Noah Golmant, Nikita Vemuri, Zhewei Yao, Vladimir Feinberg, Amir Gholami, Kai Rothauge, Michael W. Mahoney, Joseph Gonzalez
2018	J	`jnl`	Parameter Re-Initialization through Cyclical Batch Size Schedules. CoRR Norman Mu, Zhewei Yao, Amir Gholami, Kurt Keutzer, Michael W. Mahoney
2018	J	`jnl`	Trust Region Based Adversarial Attack on Neural Networks. CoRR Zhewei Yao, Amir Gholami, Peng Xu, Kurt Keutzer, Michael W. Mahoney
2017	J	`jnl`	A Hybrid Adaptive MCMC Algorithm in Function Spaces. SIAM/ASA J. Uncertain. Quantification Qingping Zhou, Zixi Hu, Zhewei Yao, Jinglai Li
2017	J	`jnl`	Nonlocal total variation based on symmetric Kullback-Leibler divergence for the ultrasound image despeckling. BMC Medical Imaging Shujun Liang, Feng Yang, Tiexiang Wen, Zhewei Yao, Qinghua Huang, Chengke Ye
2017	J	`jnl`	On an adaptive preconditioned Crank-Nicolson MCMC algorithm for infinite dimensional Bayesian inference. J. Comput. Phys. Zixi Hu, Zhewei Yao, Jinglai Li