Niladri S. Chatterji

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 42

Top Topics

Stochastic Gradient

Top Venues

J. Mach. Learn. Res.

Publications

Yonatan Oren, Nicole Meister, Niladri S. Chatterji, Faisal Ladhak, Tatsunori Hashimoto
Proving Test Set Contamination in Black-Box Language Models. ICLR (2024)
Yonatan Oren, Nicole Meister, Niladri S. Chatterji, Faisal Ladhak, Tatsunori B. Hashimoto
Proving Test Set Contamination in Black Box Language Models. CoRR (2023)
Niladri S. Chatterji, Saminul Haque, Tatsunori Hashimoto
Undersampling is a Minimax Optimal Robustness Intervention in Nonparametric Classification. Trans. Mach. Learn. Res. 2023 (2023)
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
Holistic Evaluation of Language Models. Trans. Mach. Learn. Res. 2023 (2023)
Niladri S. Chatterji, Philip M. Long
Deep linear networks can benignly overfit when shallow ones do. J. Mach. Learn. Res. 24 (2023)
Niladri S. Chatterji, Philip M. Long
Foolish Crowds Support Benign Overfitting. J. Mach. Learn. Res. 23 (2022)
Niladri S. Chatterji, Philip M. Long, Peter L. Bartlett
The Interplay Between Implicit Bias and Benign Overfitting in Two-Layer Linear Networks. J. Mach. Learn. Res. 23 (2022)
Spencer Frei, Niladri S. Chatterji, Peter L. Bartlett
Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data. COLT (2022)
Spencer Frei, Niladri S. Chatterji, Peter L. Bartlett
Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data. CoRR (2022)
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
Holistic Evaluation of Language Models. CoRR (2022)
Spencer Frei, Niladri S. Chatterji, Peter L. Bartlett
Random Feature Amplification: Feature Learning and Generalization in Neural Networks. CoRR (2022)
Niladri S. Chatterji, Philip M. Long
Deep Linear Networks can Benignly Overfit when Shallow Ones Do. CoRR (2022)
Niladri S. Chatterji, Saminul Haque, Tatsunori Hashimoto
Undersampling is a Minimax Optimal Robustness Intervention in Nonparametric Classification. CoRR (2022)
Niladri S. Chatterji, Philip M. Long, Peter L. Bartlett
When does gradient descent with logistic loss interpolate using deep networks with smoothed ReLU activations? CoRR (2021)
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.
On the Opportunities and Risks of Foundation Models. CoRR (2021)
Niladri S. Chatterji, Philip M. Long
Finite-sample Analysis of Interpolating Linear Classifiers in the Overparameterized Regime. J. Mach. Learn. Res. 22 (2021)
Ke Alexander Wang, Niladri S. Chatterji, Saminul Haque, Tatsunori Hashimoto
Is Importance Weighting Incompatible with Interpolating Classifiers? CoRR (2021)
Niladri S. Chatterji, Aldo Pacchiano, Peter L. Bartlett, Michael I. Jordan
On the Theory of Reinforcement Learning with Once-per-Episode Feedback. CoRR (2021)
Niladri S. Chatterji, Philip M. Long
Foolish Crowds Support Benign Overfitting. CoRR (2021)
Niladri S. Chatterji, Philip M. Long, Peter L. Bartlett
The Interplay Between Implicit Bias and Benign Overfitting in Two-Layer Linear Networks. CoRR (2021)
Niladri S. Chatterji, Philip M. Long, Peter L. Bartlett
When Does Gradient Descent with Logistic Loss Find Interpolating Two-Layer Networks? J. Mach. Learn. Res. 22 (2021)
Niladri S. Chatterji, Philip M. Long, Peter L. Bartlett
When does gradient descent with logistic loss interpolate using deep networks with smoothed ReLU activations? COLT (2021)
Niladri S. Chatterji, Aldo Pacchiano, Peter L. Bartlett, Michael I. Jordan
On the Theory of Reinforcement Learning with Once-per-Episode Feedback. NeurIPS (2021)
Niladri S. Chatterji, Philip M. Long, Peter L. Bartlett
When does gradient descent with logistic loss find interpolating two-layer networks? CoRR (2020)
Niladri S. Chatterji, Jelena Diakonikolas, Michael I. Jordan, Peter L. Bartlett
Langevin Monte Carlo without smoothness. AISTATS (2020)
Niladri S. Chatterji, Behnam Neyshabur, Hanie Sedghi
The intriguing role of module criticality in the generalization of deep networks. ICLR (2020)
Niladri S. Chatterji, Peter L. Bartlett, Philip M. Long
Oracle lower bounds for stochastic gradient sampling algorithms. CoRR (2020)
Niladri S. Chatterji, Vidya Muthukumar, Peter L. Bartlett
OSOM: A simultaneously optimal algorithm for multi-armed and linear contextual bandits. AISTATS (2020)
Niladri S. Chatterji, Philip M. Long
Finite-sample analysis of interpolating linear classifiers in the overparameterized regime. CoRR (2020)
Niladri S. Chatterji, Jelena Diakonikolas, Michael I. Jordan, Peter L. Bartlett
Langevin Monte Carlo without Smoothness. CoRR (2019)
Niladri S. Chatterji, Behnam Neyshabur, Hanie Sedghi
The intriguing role of module criticality in the generalization of deep networks. CoRR (2019)
Niladri S. Chatterji, Vidya Muthukumar, Peter L. Bartlett
OSOM: A Simultaneously Optimal Algorithm for Multi-Armed and Linear Contextual Bandits. CoRR (2019)
Yi-An Ma, Niladri S. Chatterji, Xiang Cheng, Nicolas Flammarion, Peter L. Bartlett, Michael I. Jordan
Is There an Analog of Nesterov Acceleration for MCMC? CoRR (2019)
Niladri S. Chatterji, Aldo Pacchiano, Peter L. Bartlett
Online learning with kernel losses. ICML (2019)
Aldo Pacchiano, Niladri S. Chatterji, Peter L. Bartlett
Online learning with kernel losses. CoRR (2018)
Niladri S. Chatterji, Nicolas Flammarion, Yi-An Ma, Peter L. Bartlett, Michael I. Jordan
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo. ICML (2018)
Xiang Cheng, Niladri S. Chatterji, Peter L. Bartlett, Michael I. Jordan
Underdamped Langevin MCMC: A non-asymptotic analysis. COLT (2018)
Xiang Cheng, Niladri S. Chatterji, Yasin Abbasi-Yadkori, Peter L. Bartlett, Michael I. Jordan
Sharp Convergence Rates for Langevin Dynamics in the Nonconvex Setting. CoRR (2018)
Niladri S. Chatterji, Nicolas Flammarion, Yi-An Ma, Peter L. Bartlett, Michael I. Jordan
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo. CoRR (2018)
Niladri S. Chatterji, Peter L. Bartlett
Alternating minimization for dictionary learning with random initialization. NIPS (2017)
Xiang Cheng, Niladri S. Chatterji, Peter L. Bartlett, Michael I. Jordan
Underdamped Langevin MCMC: A non-asymptotic analysis. CoRR (2017)
Niladri S. Chatterji, Peter L. Bartlett
Alternating minimization for dictionary learning with random initialization. CoRR (2017)