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2020 – today
- 2024
[c42]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang:
On Convex Optimization with Semi-Sensitive Features. COLT 2024: 1916-1938- [c41]Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang:
LabelDP-Pro: Learning with Label Differential Privacy via Projections. ICLR 2024 - [c40]Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang:
How Private are DP-SGD Implementations? ICML 2024 - [c39]Chiyuan Zhang, Nan Chen, Douming Hu, Fang Zhu, Yuesheng Pu, Libin Yao:
A 0.002-mm2, 2.9-μW Pulse-Frequency-Modulation based Temperature Sensor with 40-mK Resolution. ISCAS 2024: 1-4 - [i46]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:
Training Differentially Private Ad Prediction Models with Semi-Sensitive Features. CoRR abs/2401.15246 (2024) - [i45]Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang:
How Private is DP-SGD? CoRR abs/2403.17673 (2024) - [i44]Niklas Stoehr, Mitchell Gordon, Chiyuan Zhang, Owen Lewis:
Localizing Paragraph Memorization in Language Models. CoRR abs/2403.19851 (2024) - [i43]Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Daogao Liu, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang:
Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning. CoRR abs/2406.14322 (2024) - [i42]Luxi He, Yangsibo Huang, Weijia Shi, Tinghao Xie, Haotian Liu, Yue Wang, Luke Zettlemoyer, Chiyuan Zhang, Danqi Chen, Peter Henderson:
Fantastic Copyrighted Beasts and How (Not) to Generate Them. CoRR abs/2406.14526 (2024) - [i41]Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chulin Xie, Chiyuan Zhang:
Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models. CoRR abs/2406.16135 (2024) - [i40]Boyi Wei, Weijia Shi, Yangsibo Huang, Noah A. Smith, Chiyuan Zhang, Luke Zettlemoyer, Kai Li, Peter Henderson:
Evaluating Copyright Takedown Methods for Language Models. CoRR abs/2406.18664 (2024) - [i39]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang:
On Convex Optimization with Semi-Sensitive Features. CoRR abs/2406.19040 (2024) - [i38]Weijia Shi, Jaechan Lee, Yangsibo Huang, Sadhika Malladi, Jieyu Zhao, Ari Holtzman, Daogao Liu, Luke Zettlemoyer, Noah A. Smith, Chiyuan Zhang:
MUSE: Machine Unlearning Six-Way Evaluation for Language Models. CoRR abs/2407.06460 (2024) - 2023
- [c38]Carson Denison, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang:
Private Ad Modeling with DP-SGD. AdKDD@KDD 2023 - [c37]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang:
Ticketed Learning-Unlearning Schemes. COLT 2023: 5110-5139 - [c36]Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramèr, Chiyuan Zhang:
Quantifying Memorization Across Neural Language Models. ICLR 2023 - [c35]Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang:
Regression with Label Differential Privacy. ICLR 2023 - [c34]Matthew Jagielski, Om Thakkar, Florian Tramèr, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Guha Thakurta, Nicolas Papernot, Chiyuan Zhang:
Measuring Forgetting of Memorized Training Examples. ICLR 2023 - [c33]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang:
On User-Level Private Convex Optimization. ICML 2023: 11283-11299 - [c32]Pratyush Maini, Michael Curtis Mozer, Hanie Sedghi, Zachary Chase Lipton, J. Zico Kolter, Chiyuan Zhang:
Can Neural Network Memorization Be Localized? ICML 2023: 23536-23557 - [c31]Daphne Ippolito, Florian Tramèr, Milad Nasr, Chiyuan Zhang, Matthew Jagielski, Katherine Lee, Christopher A. Choquette-Choo, Nicholas Carlini:
Preventing Generation of Verbatim Memorization in Language Models Gives a False Sense of Privacy. INLG 2023: 28-53 - [c30]Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang:
Sparsity-Preserving Differentially Private Training of Large Embedding Models. NeurIPS 2023 - [c29]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang:
User-Level Differential Privacy With Few Examples Per User. NeurIPS 2023 - [c28]Ashwinkumar Badanidiyuru Varadaraja, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang:
Optimal Unbiased Randomizers for Regression with Label Differential Privacy. NeurIPS 2023 - [c27]Chiyuan Zhang, Daphne Ippolito, Katherine Lee, Matthew Jagielski, Florian Tramèr, Nicholas Carlini:
Counterfactual Memorization in Neural Language Models. NeurIPS 2023 - [i37]Badih Ghazi, Pritish Kamath, Ravi Kumar, Raghu Meka, Pasin Manurangsi, Chiyuan Zhang:
On User-Level Private Convex Optimization. CoRR abs/2305.04912 (2023) - [i36]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang:
Ticketed Learning-Unlearning Schemes. CoRR abs/2306.15744 (2023) - [i35]Pratyush Maini, Michael C. Mozer, Hanie Sedghi, Zachary C. Lipton, J. Zico Kolter, Chiyuan Zhang:
Can Neural Network Memorization Be Localized? CoRR abs/2307.09542 (2023) - [i34]Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang:
User-Level Differential Privacy With Few Examples Per User. CoRR abs/2309.12500 (2023) - [i33]Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang:
Sparsity-Preserving Differentially Private Training of Large Embedding Models. CoRR abs/2311.08357 (2023) - [i32]Ashwinkumar Badanidiyuru, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang:
Optimal Unbiased Randomizers for Regression with Label Differential Privacy. CoRR abs/2312.05659 (2023) - 2022
- [j8]Chiyuan Zhang, Samy Bengio, Yoram Singer:
Are All Layers Created Equal? J. Mach. Learn. Res. 23: 67:1-67:28 (2022) - [c26]Katherine Lee
, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, Nicholas Carlini:
Deduplicating Training Data Makes Language Models Better. ACL (1) 2022: 8424-8445 - [c25]Weiyan Shi, Ryan Shea, Si Chen, Chiyuan Zhang, Ruoxi Jia, Zhou Yu:
Just Fine-tune Twice: Selective Differential Privacy for Large Language Models. EMNLP 2022: 6327-6340 - [c24]Emmanuel Abbe, Samy Bengio, Elisabetta Cornacchia, Jon M. Kleinberg, Aryo Lotfi, Maithra Raghu, Chiyuan Zhang:
Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures. NeurIPS 2022 - [c23]Nicholas Carlini, Matthew Jagielski, Chiyuan Zhang, Nicolas Papernot, Andreas Terzis, Florian Tramèr:
The Privacy Onion Effect: Memorization is Relative. NeurIPS 2022 - [c22]Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang:
Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation. NeurIPS 2022 - [i31]Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramèr, Chiyuan Zhang:
Quantifying Memorization Across Neural Language Models. CoRR abs/2202.07646 (2022) - [i30]Weiyan Shi, Si Chen, Chiyuan Zhang, Ruoxi Jia, Zhou Yu:
Just Fine-tune Twice: Selective Differential Privacy for Large Language Models. CoRR abs/2204.07667 (2022) - [i29]Emmanuel Abbe, Samy Bengio, Elisabetta Cornacchia, Jon M. Kleinberg, Aryo Lotfi, Maithra Raghu, Chiyuan Zhang:
Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures. CoRR abs/2205.13647 (2022) - [i28]Nicholas Carlini, Matthew Jagielski, Chiyuan Zhang, Nicolas Papernot, Andreas Terzis, Florian Tramèr:
The Privacy Onion Effect: Memorization is Relative. CoRR abs/2206.10469 (2022) - [i27]Matthew Jagielski, Om Thakkar, Florian Tramèr, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Thakurta, Nicolas Papernot, Chiyuan Zhang:
Measuring Forgetting of Memorized Training Examples. CoRR abs/2207.00099 (2022) - [i26]Daphne Ippolito, Florian Tramèr, Milad Nasr, Chiyuan Zhang, Matthew Jagielski, Katherine Lee, Christopher A. Choquette-Choo, Nicholas Carlini:
Preventing Verbatim Memorization in Language Models Gives a False Sense of Privacy. CoRR abs/2210.17546 (2022) - [i25]Carson Denison, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang:
Private Ad Modeling with DP-SGD. CoRR abs/2211.11896 (2022) - [i24]Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang:
Regression with Label Differential Privacy. CoRR abs/2212.06074 (2022) - 2021
- [j7]Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, Oriol Vinyals:
Understanding deep learning (still) requires rethinking generalization. Commun. ACM 64(3): 107-115 (2021) - [c21]Ziheng Jiang, Chiyuan Zhang, Kunal Talwar, Michael C. Mozer:
Characterizing Structural Regularities of Labeled Data in Overparameterized Models. ICML 2021: 5034-5044 - [c20]Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Michael C. Mozer:
Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers. ICML 2021: 10225-10235 - [c19]Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, Alexey Dosovitskiy:
Do Vision Transformers See Like Convolutional Neural Networks? NeurIPS 2021: 12116-12128 - [c18]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang:
Deep Learning with Label Differential Privacy. NeurIPS 2021: 27131-27145 - [i23]Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang:
On Deep Learning with Label Differential Privacy. CoRR abs/2102.06062 (2021) - [i22]Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Michael C. Mozer:
Understanding invariance via feedforward inversion of discriminatively trained classifiers. CoRR abs/2103.07470 (2021) - [i21]Katherine Lee, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, Nicholas Carlini:
Deduplicating Training Data Makes Language Models Better. CoRR abs/2107.06499 (2021) - [i20]Chiyuan Zhang, Maithra Raghu, Jon M. Kleinberg, Samy Bengio:
Pointer Value Retrieval: A new benchmark for understanding the limits of neural network generalization. CoRR abs/2107.12580 (2021) - [i19]Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, Alexey Dosovitskiy:
Do Vision Transformers See Like Convolutional Neural Networks? CoRR abs/2108.08810 (2021) - [i18]Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang:
Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation. CoRR abs/2110.07858 (2021) - [i17]Chiyuan Zhang, Daphne Ippolito, Katherine Lee, Matthew Jagielski, Florian Tramèr, Nicholas Carlini:
Counterfactual Memorization in Neural Language Models. CoRR abs/2112.12938 (2021) - 2020
- [c17]Chiyuan Zhang, Samy Bengio, Moritz Hardt, Michael C. Mozer, Yoram Singer:
Identity Crisis: Memorization and Generalization Under Extreme Overparameterization. ICLR 2020 - [c16]Vitaly Feldman, Chiyuan Zhang:
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation. NeurIPS 2020 - [c15]Behnam Neyshabur, Hanie Sedghi, Chiyuan Zhang:
What is being transferred in transfer learning? NeurIPS 2020 - [i16]Ziheng Jiang, Chiyuan Zhang, Kunal Talwar, Michael C. Mozer:
Exploring the Memorization-Generalization Continuum in Deep Learning. CoRR abs/2002.03206 (2020) - [i15]Vitaly Feldman, Chiyuan Zhang:
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation. CoRR abs/2008.03703 (2020) - [i14]Behnam Neyshabur, Hanie Sedghi, Chiyuan Zhang:
What is being transferred in transfer learning? CoRR abs/2008.11687 (2020)
2010 – 2019
- 2019
- [c14]Qihao Wan, Jiaxin Zhao, Jianru Xue, Chiyuan Zhang, Bin He, Heming Zhang:
A Novel Hierarchical Collaborative Method Based on Multi-objective Optimization for Modularization of Product Platform. CSCWD 2019: 215-220 - [c13]Maithra Raghu, Chiyuan Zhang, Jon M. Kleinberg, Samy Bengio:
Transfusion: Understanding Transfer Learning for Medical Imaging. NeurIPS 2019: 3342-3352 - [i13]Chiyuan Zhang, Samy Bengio, Yoram Singer:
Are All Layers Created Equal? CoRR abs/1902.01996 (2019) - [i12]Chiyuan Zhang, Samy Bengio, Moritz Hardt, Yoram Singer:
Identity Crisis: Memorization and Generalization under Extreme Overparameterization. CoRR abs/1902.04698 (2019) - [i11]Maithra Raghu, Chiyuan Zhang, Jon M. Kleinberg, Samy Bengio:
Transfusion: Understanding Transfer Learning with Applications to Medical Imaging. CoRR abs/1902.07208 (2019) - 2018
- [b1]Chiyuan Zhang:
Deep learning and structured data. Massachusetts Institute of Technology, Cambridge, USA, 2018 - [c12]Neil C. Rabinowitz, Frank Perbet, H. Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew M. Botvinick:
Machine Theory of Mind. ICML 2018: 4215-4224 - [i10]Chiyuan Zhang, Qianli Liao, Alexander Rakhlin, Brando Miranda, Noah Golowich, Tomaso A. Poggio:
Theory of Deep Learning IIb: Optimization Properties of SGD. CoRR abs/1801.02254 (2018) - [i9]Neil C. Rabinowitz, Frank Perbet, H. Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew M. Botvinick:
Machine Theory of Mind. CoRR abs/1802.07740 (2018) - [i8]Chiyuan Zhang, Oriol Vinyals, Rémi Munos, Samy Bengio:
A Study on Overfitting in Deep Reinforcement Learning. CoRR abs/1804.06893 (2018) - [i7]Tom B. Brown, Nicholas Carlini, Chiyuan Zhang, Catherine Olsson, Paul F. Christiano, Ian J. Goodfellow:
Unrestricted Adversarial Examples. CoRR abs/1809.08352 (2018) - 2017
- [j6]Yuqi Guo, Yangzhou Chen, Chiyuan Zhang:
Decentralized State-Observer-Based Traffic Density Estimation of Large-Scale Urban Freeway Network by Dynamic Model. Inf. 8(3): 95 (2017) - [c11]Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, Oriol Vinyals:
Understanding deep learning requires rethinking generalization. ICLR 2017 - [c10]Yuqi Guo, Yangzhou Chen, Wei Li, Chiyuan Zhang:
Distributed state-observer-based traffic density estimation of urban freeway network. ITSC 2017: 1177-1182 - 2016
- [j5]Xiaofei He, Chiyuan Zhang, Lijun Zhang, Xuelong Li:
A-Optimal Projection for Image Representation. IEEE Trans. Pattern Anal. Mach. Intell. 38(5): 1009-1015 (2016) - [i6]Tianqi Chen, Bing Xu, Chiyuan Zhang, Carlos Guestrin:
Training Deep Nets with Sublinear Memory Cost. CoRR abs/1604.06174 (2016) - [i5]Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, Oriol Vinyals:
Understanding deep learning requires rethinking generalization. CoRR abs/1611.03530 (2016) - 2015
- [c9]Chiyuan Zhang, Stephen Voinea, Georgios Evangelopoulos, Lorenzo Rosasco, Tomaso A. Poggio:
Discriminative template learning in group-convolutional networks for invariant speech representations. INTERSPEECH 2015: 3229-3233 - [c8]Charlie Frogner, Chiyuan Zhang, Hossein Mobahi, Mauricio Araya-Polo, Tomaso A. Poggio:
Learning with a Wasserstein Loss. NIPS 2015: 2053-2061 - [i4]Charlie Frogner, Chiyuan Zhang, Hossein Mobahi, Mauricio Araya-Polo, Tomaso A. Poggio:
Learning with a Wasserstein Loss. CoRR abs/1506.05439 (2015) - [i3]Tianqi Chen, Mu Li, Yutian Li, Min Lin, Naiyan Wang, Minjie Wang, Tianjun Xiao, Bing Xu, Chiyuan Zhang, Zheng Zhang:
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems. CoRR abs/1512.01274 (2015) - 2014
- [c7]Chiyuan Zhang, Georgios Evangelopoulos, Stephen Voinea, Lorenzo Rosasco, Tomaso A. Poggio:
A deep representation for invariance and music classification. ICASSP 2014: 6984-6988 - [c6]Chiyuan Zhang, Stephen Voinea, Georgios Evangelopoulos, Lorenzo Rosasco, Tomaso A. Poggio:
Phone classification by a hierarchy of invariant representation layers. INTERSPEECH 2014: 2346-2350 - [c5]Stephen Voinea, Chiyuan Zhang, Georgios Evangelopoulos, Lorenzo Rosasco, Tomaso A. Poggio:
Word-level invariant representations from acoustic waveforms. INTERSPEECH 2014: 2385-2389 - [i2]Chiyuan Zhang, Georgios Evangelopoulos, Stephen Voinea, Lorenzo Rosasco, Tomaso A. Poggio:
A Deep Representation for Invariance And Music Classification. CoRR abs/1404.0400 (2014) - [i1]Georgios Evangelopoulos, Stephen Voinea, Chiyuan Zhang, Lorenzo Rosasco, Tomaso A. Poggio:
Learning An Invariant Speech Representation. CoRR abs/1406.3884 (2014) - 2013
- [j4]Chiyuan Zhang, Ming Ji:
Combining Active and Semi-Supervised Learning for Video Compression. Int. J. Softw. Informatics 7(3): 453-468 (2013) - [j3]Binbin Lin, Xiaofei He, Chiyuan Zhang, Ming Ji:
Parallel vector field embedding. J. Mach. Learn. Res. 14(1): 2945-2977 (2013) - [j2]Chiyuan Zhang, Xiaofei He:
Image Compression by Learning to Minimize the Total Error. IEEE Trans. Circuits Syst. Video Technol. 23(4): 565-576 (2013) - 2012
- [c4]Binbin Lin, Sen Yang, Chiyuan Zhang, Jieping Ye, Xiaofei He:
Multi-task Vector Field Learning. NIPS 2012: 296-304 - 2011
- [j1]Xiaofei He, Ming Ji, Chiyuan Zhang, Hujun Bao:
A Variance Minimization Criterion to Feature Selection Using Laplacian Regularization. IEEE Trans. Pattern Anal. Mach. Intell. 33(10): 2013-2025 (2011) - [c3]Binbin Lin, Chiyuan Zhang, Xiaofei He:
Orthogonal Projection Analysis. IScIDE 2011: 1-8 - [c2]Binbin Lin, Chiyuan Zhang, Xiaofei He:
Semi-supervised Regression via Parallel Field Regularization. NIPS 2011: 433-441 - 2010
- [c1]Deng Cai, Chiyuan Zhang, Xiaofei He:
Unsupervised feature selection for multi-cluster data. KDD 2010: 333-342
Coauthor Index
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