Chiyuan Zhang - RankMe

123 papers A* 36A 4B 1C 2Misc 1Journal 68Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	High Precision Parameter Estimator for Calibrating the Sine Wave Signals in Industrial Inspection. IEEE Trans. Ind. Informatics Junhao Zhang, Xiong Hu, Chiyuan Zhang, Jian Song, Guangze Shi, Xuesong Xu, He Wen
2025	A	`conf`	Balls-and-Bins Sampling for DP-SGD. AISTATS Lynn Chua, Badih Ghazi, Charlie Harrison, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2025	A*	`conf`	Empirical Privacy Variance. ICML Yuzheng Hu, Fan Wu, Ruicheng Xian, Yuhang Liu, Lydia Zakynthinou, Pritish Kamath, Chiyuan Zhang, David A. Forsyth
2025	J	`jnl`	Empirical Privacy Variance. CoRR Yuzheng Hu, Fan Wu, Ruicheng Xian, Yuhang Liu, Lydia Zakynthinou, Pritish Kamath, Chiyuan Zhang, David A. Forsyth
2025	A*	`conf`	Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards. ICML Yangsibo Huang, Milad Nasr, Anastasios Nikolas Angelopoulos, Nicholas Carlini, Wei-Lin Chiang, Christopher A. Choquette-Choo, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Ken Liu, Ion Stoica, Florian Tramèr, Chiyuan Zhang
2025	J	`jnl`	Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards. CoRR Yangsibo Huang, Milad Nasr, Anastasios Angelopoulos, Nicholas Carlini, Wei-Lin Chiang, Christopher A. Choquette-Choo, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Ken Ziyu Liu, Ion Stoica, Florian Tramèr, Chiyuan Zhang
2025	A*	`conf`	Fantastic Copyrighted Beasts and How (Not) to Generate Them. ICLR Luxi He, Yangsibo Huang, Weijia Shi, Tinghao Xie, Haotian Liu, Yue Wang, Luke Zettlemoyer, Chiyuan Zhang, Danqi Chen, Peter Henderson
2025	A*	`conf`	MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations. ICML Kaixuan Huang, Jiacheng Guo, Zihao Li, Xiang Ji, Jiawei Ge, Wenzhe Li, Yingqing Guo, Tianle Cai, Hui Yuan, Runzhe Wang, Yue Wu, Ming Yin, Shange Tang, Yangsibo Huang, Chi Jin, Xinyun Chen, Chiyuan Zhang, Mengdi Wang
2025	J	`jnl`	MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations. CoRR Kaixuan Huang, Jiacheng Guo, Zihao Li, Xiang Ji, Jiawei Ge, Wenzhe Li, Yingqing Guo, Tianle Cai, Hui Yuan, Runzhe Wang, Yue Wu, Ming Yin, Shange Tang, Yangsibo Huang, Chi Jin, Xinyun Chen, Chiyuan Zhang, Mengdi Wang
2025	A*	`conf`	MUSE: Machine Unlearning Six-Way Evaluation for Language Models. ICLR Weijia Shi, Jaechan Lee, Yangsibo Huang, Sadhika Malladi, Jieyu Zhao, Ari Holtzman, Daogao Liu, Luke Zettlemoyer, Noah A. Smith, Chiyuan Zhang
2025	—	`conf`	On Memorization of Large Language Models in Logical Reasoning. IJCNLP-AACL (long papers) Chulin Xie, Yangsibo Huang, Chiyuan Zhang, Da Yu, Xinyun Chen, Bill Yuchen Lin, Bo Li, Badih Ghazi, Ravi Kumar
2025	J	`jnl`	Private Hyperparameter Tuning with Ex-Post Guarantee. CoRR Badih Ghazi, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
2025	J	`jnl`	Quantifying Cross-Modality Memorization in Vision-Language Models. CoRR Yuxin Wen, Yangsibo Huang, Tom Goldstein, Ravi Kumar, Badih Ghazi, Chiyuan Zhang
2025	J	`jnl`	Scaling Embedding Layers in Language Models. CoRR Da Yu, Edith Cohen, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Daogao Liu, Chiyuan Zhang
2025	A*	`conf`	Scaling Laws for Differentially Private Language Models. ICML Ryan McKenna, Yangsibo Huang, Amer Sinha, Borja Balle, Zachary Charles, Christopher A. Choquette-Choo, Badih Ghazi, Georgios Kaissis, Ravi Kumar, Ruibo Liu, Da Yu, Chiyuan Zhang
2025	J	`jnl`	Scaling Laws for Differentially Private Language Models. CoRR Ryan McKenna, Yangsibo Huang, Amer Sinha, Borja Balle, Zachary Charles, Christopher A. Choquette-Choo, Badih Ghazi, Georgios Kaissis, Ravi Kumar, Ruibo Liu, Da Yu, Chiyuan Zhang
2025	A*	`conf`	Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy. ICLR Yangsibo Huang, Daogao Liu, Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Milad Nasr, Amer Sinha, Chiyuan Zhang
2025	J	`jnl`	Urania: Differentially Private Insights into AI Use. CoRR Daogao Liu, Edith Cohen, Badih Ghazi, Peter Kairouz, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Adam Sealfon, Da Yu, Chiyuan Zhang
2025	J	`jnl`	VaultGemma: A Differentially Private Gemma Model. CoRR Amer Sinha, Thomas Mesnard, Ryan McKenna, Daogao Liu, Christopher A. Choquette-Choo, Yangsibo Huang, Da Yu, Georgios Kaissis, Zachary Charles, Ruibo Liu, Lynn Chua, Pritish Kamath, Pasin Manurangsi, Steve He, Chiyuan Zhang, Badih Ghazi, Borja de Balle Pigem, Prem Eruvbetine, Tris Warkentin, Armand Joulin, Ravi Kumar
2024	C	`conf`	A 0.002-mm ISCAS Chiyuan Zhang, Nan Chen, Douming Hu, Fang Zhu, Yuesheng Pu, Libin Yao
2024	J	`jnl`	Balls-and-Bins Sampling for DP-SGD. CoRR Lynn Chua, Badih Ghazi, Charlie Harrison, Ethan Leeman, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	J	`jnl`	Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models. CoRR Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chulin Xie, Chiyuan Zhang
2024	A*	`conf`	Evaluating Copyright Takedown Methods for Language Models. NeurIPS Boyi Wei, Weijia Shi, Yangsibo Huang, Noah A. Smith, Chiyuan Zhang, Luke Zettlemoyer, Kai Li, Peter Henderson
2024	J	`jnl`	Evaluating Copyright Takedown Methods for Language Models. CoRR Boyi Wei, Weijia Shi, Yangsibo Huang, Noah A. Smith, Chiyuan Zhang, Luke Zettlemoyer, Kai Li, Peter Henderson
2024	J	`jnl`	Fantastic Copyrighted Beasts and How (Not) to Generate Them. CoRR Luxi He, Yangsibo Huang, Weijia Shi, Tinghao Xie, Haotian Liu, Yue Wang, Luke Zettlemoyer, Chiyuan Zhang, Danqi Chen, Peter Henderson
2024	A*	`conf`	How Private are DP-SGD Implementations? ICML Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	J	`jnl`	How Private is DP-SGD? CoRR Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	A*	`conf`	LabelDP-Pro: Learning with Label Differential Privacy via Projections. ICLR Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
2024	J	`jnl`	Localizing Paragraph Memorization in Language Models. CoRR Niklas Stoehr, Mitchell Gordon, Chiyuan Zhang, Owen Lewis
2024	J	`jnl`	MUSE: Machine Unlearning Six-Way Evaluation for Language Models. CoRR Weijia Shi, Jaechan Lee, Yangsibo Huang, Sadhika Malladi, Jieyu Zhao, Ari Holtzman, Daogao Liu, Luke Zettlemoyer, Noah A. Smith, Chiyuan Zhang
2024	J	`jnl`	Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning. CoRR Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Daogao Liu, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	A*	`conf`	On Convex Optimization with Semi-Sensitive Features. COLT Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
2024	J	`jnl`	On Convex Optimization with Semi-Sensitive Features. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
2024	J	`jnl`	On Memorization of Large Language Models in Logical Reasoning. CoRR Chulin Xie, Yangsibo Huang, Chiyuan Zhang, Da Yu, Xinyun Chen, Bill Yuchen Lin, Bo Li, Badih Ghazi, Ravi Kumar
2024	A*	`conf`	Scalable DP-SGD: Shuffling vs. Poisson Subsampling. NeurIPS Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	J	`jnl`	Scalable DP-SGD: Shuffling vs. Poisson Subsampling. CoRR Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	—	`conf`	Training Differentially Private Ad Prediction Models With Semi-Sensitive Features. AdKDD@KDD Lynn Chua, Qiliang Cui, Badih Ghazi, Charlie Harrison, Pritish Kamath, Walid Krichene, Ravi Kumar, Pasin Manurangsi, Nicolas Mayoraz, Hema Venkata Krishna Giri Narra, Steffen Rendle, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang
2024	J	`jnl`	Training Differentially Private Ad Prediction Models with Semi-Sensitive Features. CoRR Lynn Chua, Qiliang Cui, Badih Ghazi, Charlie Harrison, Pritish Kamath, Walid Krichene, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang
2024	J	`jnl`	Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy. CoRR Yangsibo Huang, Daogao Liu, Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Milad Nasr, Amer Sinha, Chiyuan Zhang
2023	A*	`conf`	Can Neural Network Memorization Be Localized? ICML Pratyush Maini, Michael Curtis Mozer, Hanie Sedghi, Zachary Chase Lipton, J. Zico Kolter, Chiyuan Zhang
2023	J	`jnl`	Can Neural Network Memorization Be Localized? CoRR Pratyush Maini, Michael C. Mozer, Hanie Sedghi, Zachary C. Lipton, J. Zico Kolter, Chiyuan Zhang
2023	A*	`conf`	Counterfactual Memorization in Neural Language Models. NeurIPS Chiyuan Zhang, Daphne Ippolito, Katherine Lee, Matthew Jagielski, Florian Tramèr, Nicholas Carlini
2023	A*	`conf`	Measuring Forgetting of Memorized Training Examples. ICLR Matthew Jagielski, Om Thakkar, Florian Tramèr, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Guha Thakurta, Nicolas Papernot, Chiyuan Zhang
2023	A*	`conf`	On User-Level Private Convex Optimization. ICML Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
2023	J	`jnl`	On User-Level Private Convex Optimization. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Raghu Meka, Pasin Manurangsi, Chiyuan Zhang
2023	A*	`conf`	Optimal Unbiased Randomizers for Regression with Label Differential Privacy. NeurIPS Ashwinkumar Badanidiyuru Varadaraja, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang
2023	J	`jnl`	Optimal Unbiased Randomizers for Regression with Label Differential Privacy. CoRR Ashwinkumar Badanidiyuru, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang
2023	B	`conf`	Preventing Generation of Verbatim Memorization in Language Models Gives a False Sense of Privacy. INLG Daphne Ippolito, Florian Tramèr, Milad Nasr, Chiyuan Zhang, Matthew Jagielski, Katherine Lee, Christopher A. Choquette-Choo, Nicholas Carlini
2023	—	`conf`	Private Ad Modeling with DP-SGD. AdKDD@KDD Carson Denison, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang
2023	A*	`conf`	Quantifying Memorization Across Neural Language Models. ICLR Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramèr, Chiyuan Zhang
2023	A*	`conf`	Regression with Label Differential Privacy. ICLR Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang
2023	A*	`conf`	Sparsity-Preserving Differentially Private Training of Large Embedding Models. NeurIPS Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2023	J	`jnl`	Sparsity-Preserving Differentially Private Training of Large Embedding Models. CoRR Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2023	A*	`conf`	Ticketed Learning-Unlearning Schemes. COLT Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang
2023	J	`jnl`	Ticketed Learning-Unlearning Schemes. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang
2023	A*	`conf`	User-Level Differential Privacy With Few Examples Per User. NeurIPS Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
2023	J	`jnl`	User-Level Differential Privacy With Few Examples Per User. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
2022	J	`jnl`	Are All Layers Created Equal? J. Mach. Learn. Res. Chiyuan Zhang, Samy Bengio, Yoram Singer
2022	—	`conf`	Deduplicating Training Data Makes Language Models Better. ACL (1) Katherine Lee, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, Nicholas Carlini
2022	A*	`conf`	Just Fine-tune Twice: Selective Differential Privacy for Large Language Models. EMNLP Weiyan Shi, Ryan Shea, Si Chen, Chiyuan Zhang, Ruoxi Jia, Zhou Yu
2022	J	`jnl`	Just Fine-tune Twice: Selective Differential Privacy for Large Language Models. CoRR Weiyan Shi, Si Chen, Chiyuan Zhang, Ruoxi Jia, Zhou Yu
2022	A*	`conf`	Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures. NeurIPS Emmanuel Abbe, Samy Bengio, Elisabetta Cornacchia, Jon M. Kleinberg, Aryo Lotfi, Maithra Raghu, Chiyuan Zhang
2022	J	`jnl`	Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures. CoRR Emmanuel Abbe, Samy Bengio, Elisabetta Cornacchia, Jon M. Kleinberg, Aryo Lotfi, Maithra Raghu, Chiyuan Zhang
2022	J	`jnl`	Measuring Forgetting of Memorized Training Examples. CoRR Matthew Jagielski, Om Thakkar, Florian Tramèr, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Thakurta, Nicolas Papernot, Chiyuan Zhang
2022	J	`jnl`	Preventing Verbatim Memorization in Language Models Gives a False Sense of Privacy. CoRR Daphne Ippolito, Florian Tramèr, Milad Nasr, Chiyuan Zhang, Matthew Jagielski, Katherine Lee, Christopher A. Choquette-Choo, Nicholas Carlini
2022	J	`jnl`	Private Ad Modeling with DP-SGD. CoRR Carson Denison, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang
2022	J	`jnl`	Quantifying Memorization Across Neural Language Models. CoRR Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramèr, Chiyuan Zhang
2022	J	`jnl`	Regression with Label Differential Privacy. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang
2022	A*	`conf`	The Privacy Onion Effect: Memorization is Relative. NeurIPS Nicholas Carlini, Matthew Jagielski, Chiyuan Zhang, Nicolas Papernot, Andreas Terzis, Florian Tramèr
2022	J	`jnl`	The Privacy Onion Effect: Memorization is Relative. CoRR Nicholas Carlini, Matthew Jagielski, Chiyuan Zhang, Nicolas Papernot, Andreas Terzis, Florian Tramèr
2022	A*	`conf`	Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation. NeurIPS Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang
2021	A*	`conf`	Characterizing Structural Regularities of Labeled Data in Overparameterized Models. ICML Ziheng Jiang, Chiyuan Zhang, Kunal Talwar, Michael C. Mozer
2021	J	`jnl`	Counterfactual Memorization in Neural Language Models. CoRR Chiyuan Zhang, Daphne Ippolito, Katherine Lee, Matthew Jagielski, Florian Tramèr, Nicholas Carlini
2021	J	`jnl`	Deduplicating Training Data Makes Language Models Better. CoRR Katherine Lee, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, Nicholas Carlini
2021	A*	`conf`	Deep Learning with Label Differential Privacy. NeurIPS Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
2021	A*	`conf`	Do Vision Transformers See Like Convolutional Neural Networks? NeurIPS Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, Alexey Dosovitskiy
2021	J	`jnl`	Do Vision Transformers See Like Convolutional Neural Networks? CoRR Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, Alexey Dosovitskiy
2021	J	`jnl`	On Deep Learning with Label Differential Privacy. CoRR Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
2021	J	`jnl`	Pointer Value Retrieval: A new benchmark for understanding the limits of neural network generalization. CoRR Chiyuan Zhang, Maithra Raghu, Jon M. Kleinberg, Samy Bengio
2021	A*	`conf`	Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers. ICML Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Michael C. Mozer
2021	J	`jnl`	Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation. CoRR Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang
2021	J	`jnl`	Understanding deep learning (still) requires rethinking generalization. Commun. ACM Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, Oriol Vinyals
2021	J	`jnl`	Understanding invariance via feedforward inversion of discriminatively trained classifiers. CoRR Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Michael C. Mozer
2020	J	`jnl`	Exploring the Memorization-Generalization Continuum in Deep Learning. CoRR Ziheng Jiang, Chiyuan Zhang, Kunal Talwar, Michael C. Mozer
2020	A*	`conf`	Identity Crisis: Memorization and Generalization Under Extreme Overparameterization. ICLR Chiyuan Zhang, Samy Bengio, Moritz Hardt, Michael C. Mozer, Yoram Singer
2020	A*	`conf`	What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation. NeurIPS Vitaly Feldman, Chiyuan Zhang
2020	J	`jnl`	What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation. CoRR Vitaly Feldman, Chiyuan Zhang
2020	A*	`conf`	What is being transferred in transfer learning? NeurIPS Behnam Neyshabur, Hanie Sedghi, Chiyuan Zhang
2020	J	`jnl`	What is being transferred in transfer learning? CoRR Behnam Neyshabur, Hanie Sedghi, Chiyuan Zhang
2019	C	`conf`	A Novel Hierarchical Collaborative Method Based on Multi-objective Optimization for Modularization of Product Platform. CSCWD Qihao Wan, Jiaxin Zhao, Jianru Xue, Chiyuan Zhang, Bin He, Heming Zhang
2019	J	`jnl`	Are All Layers Created Equal? CoRR Chiyuan Zhang, Samy Bengio, Yoram Singer
2019	J	`jnl`	Identity Crisis: Memorization and Generalization under Extreme Overparameterization. CoRR Chiyuan Zhang, Samy Bengio, Moritz Hardt, Yoram Singer
2019	A*	`conf`	Transfusion: Understanding Transfer Learning for Medical Imaging. NeurIPS Maithra Raghu, Chiyuan Zhang, Jon M. Kleinberg, Samy Bengio
2019	J	`jnl`	Transfusion: Understanding Transfer Learning with Applications to Medical Imaging. CoRR Maithra Raghu, Chiyuan Zhang, Jon M. Kleinberg, Samy Bengio
2018	J	`jnl`	A Study on Overfitting in Deep Reinforcement Learning. CoRR Chiyuan Zhang, Oriol Vinyals, Rémi Munos, Samy Bengio
2018	—	`—`	Deep learning and structured data. Chiyuan Zhang
2018	A*	`conf`	Machine Theory of Mind. ICML Neil C. Rabinowitz, Frank Perbet, H. Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew M. Botvinick
2018	J	`jnl`	Machine Theory of Mind. CoRR Neil C. Rabinowitz, Frank Perbet, H. Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew M. Botvinick
2018	J	`jnl`	Theory of Deep Learning IIb: Optimization Properties of SGD. CoRR Chiyuan Zhang, Qianli Liao, Alexander Rakhlin, Brando Miranda, Noah Golowich, Tomaso A. Poggio
2018	J	`jnl`	Unrestricted Adversarial Examples. CoRR Tom B. Brown, Nicholas Carlini, Chiyuan Zhang, Catherine Olsson, Paul F. Christiano, Ian J. Goodfellow
2017	J	`jnl`	Decentralized State-Observer-Based Traffic Density Estimation of Large-Scale Urban Freeway Network by Dynamic Model. Inf. Yuqi Guo, Yangzhou Chen, Chiyuan Zhang
2017	—	`conf`	Distributed state-observer-based traffic density estimation of urban freeway network. ITSC Yuqi Guo, Yangzhou Chen, Wei Li, Chiyuan Zhang
2017	—	`conf`	Understanding deep learning requires rethinking generalization. ICLR Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, Oriol Vinyals
2016	J	`jnl`	A-Optimal Projection for Image Representation. IEEE Trans. Pattern Anal. Mach. Intell. Xiaofei He, Chiyuan Zhang, Lijun Zhang, Xuelong Li
2016	J	`jnl`	Training Deep Nets with Sublinear Memory Cost. CoRR Tianqi Chen, Bing Xu, Chiyuan Zhang, Carlos Guestrin
2016	J	`jnl`	Understanding deep learning requires rethinking generalization. CoRR Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, Oriol Vinyals
2015	A	`conf`	Discriminative template learning in group-convolutional networks for invariant speech representations. INTERSPEECH Chiyuan Zhang, Stephen Voinea, Georgios Evangelopoulos, Lorenzo Rosasco, Tomaso A. Poggio
2015	—	`conf`	Learning with a Wasserstein Loss. NIPS Charlie Frogner, Chiyuan Zhang, Hossein Mobahi, Mauricio Araya-Polo, Tomaso A. Poggio
2015	J	`jnl`	Learning with a Wasserstein Loss. CoRR Charlie Frogner, Chiyuan Zhang, Hossein Mobahi, Mauricio Araya-Polo, Tomaso A. Poggio
2015	J	`jnl`	MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems. CoRR Tianqi Chen, Mu Li, Yutian Li, Min Lin, Naiyan Wang, Minjie Wang, Tianjun Xiao, Bing Xu, Chiyuan Zhang, Zheng Zhang
2014	J	`jnl`	A Deep Representation for Invariance And Music Classification. CoRR Chiyuan Zhang, Georgios Evangelopoulos, Stephen Voinea, Lorenzo Rosasco, Tomaso A. Poggio
2014	Misc	`conf`	A deep representation for invariance and music classification. ICASSP Chiyuan Zhang, Georgios Evangelopoulos, Stephen Voinea, Lorenzo Rosasco, Tomaso A. Poggio
2014	J	`jnl`	Learning An Invariant Speech Representation. CoRR Georgios Evangelopoulos, Stephen Voinea, Chiyuan Zhang, Lorenzo Rosasco, Tomaso A. Poggio
2014	A	`conf`	Phone classification by a hierarchy of invariant representation layers. INTERSPEECH Chiyuan Zhang, Stephen Voinea, Georgios Evangelopoulos, Lorenzo Rosasco, Tomaso A. Poggio
2014	A	`conf`	Word-level invariant representations from acoustic waveforms. INTERSPEECH Stephen Voinea, Chiyuan Zhang, Georgios Evangelopoulos, Lorenzo Rosasco, Tomaso A. Poggio
2013	J	`jnl`	Combining Active and Semi-Supervised Learning for Video Compression. Int. J. Softw. Informatics Chiyuan Zhang, Ming Ji
2013	J	`jnl`	Image Compression by Learning to Minimize the Total Error. IEEE Trans. Circuits Syst. Video Technol. Chiyuan Zhang, Xiaofei He
2013	J	`jnl`	Parallel vector field embedding. J. Mach. Learn. Res. Binbin Lin, Xiaofei He, Chiyuan Zhang, Ming Ji
2012	—	`conf`	Multi-task Vector Field Learning. NIPS Binbin Lin, Sen Yang, Chiyuan Zhang, Jieping Ye, Xiaofei He
2011	J	`jnl`	A Variance Minimization Criterion to Feature Selection Using Laplacian Regularization. IEEE Trans. Pattern Anal. Mach. Intell. Xiaofei He, Ming Ji, Chiyuan Zhang, Hujun Bao
2011	—	`conf`	Orthogonal Projection Analysis. IScIDE Binbin Lin, Chiyuan Zhang, Xiaofei He
2011	—	`conf`	Semi-supervised Regression via Parallel Field Regularization. NIPS Binbin Lin, Chiyuan Zhang, Xiaofei He
2010	A*	`conf`	Unsupervised feature selection for multi-cluster data. KDD Deng Cai, Chiyuan Zhang, Xiaofei He