Articles with public access mandates - Tengyu MALearn more
Available somewhere: 38
Toward L_∞ Recovery of Nonlinear Functions: A Polynomial Sample Complexity Bound for Gaussian Random Fields
K Dong, T Ma
The Thirty Sixth Annual Conference on Learning Theory, 2877-2918, 2023
Mandates: US National Science Foundation
Same pre-training loss, better downstream: Implicit bias matters for language models
H Liu, SM Xie, Z Li, T Ma
International Conference on Machine Learning, 22188-22214, 2023
Mandates: US National Science Foundation, US Department of Defense
How Sharpness-Aware Minimization Minimizes Sharpness?
K Wen, T Ma, Z Li
The Eleventh International Conference on Learning Representations, 2023
Mandates: US National Science Foundation
Statistically meaningful approximation: a case study on approximating turing machines with transformers
C Wei, Y Chen, T Ma
Advances in Neural Information Processing Systems 35, 12071-12083, 2022
Mandates: US National Science Foundation
Iterative feature matching: Toward provable domain generalization with logarithmic environments
Y Chen, E Rosenfeld, M Sellke, T Ma, A Risteski
Advances in Neural Information Processing Systems 35, 1725-1736, 2022
Mandates: US National Science Foundation
Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift
A Kumar, T Ma, P Liang, A Raghunathan
Uncertainty in Artificial Intelligence, 1041-1051, 2022
Mandates: US National Science Foundation
Near-optimal algorithms for autonomous exploration and multi-goal stochastic shortest path
H Cai, T Ma, S Du
International Conference on Machine Learning, 2434-2456, 2022
Mandates: US National Science Foundation
Connect, not collapse: Explaining contrastive learning for unsupervised domain adaptation
K Shen, RM Jones, A Kumar, SM Xie, JZ HaoChen, T Ma, P Liang
International conference on machine learning, 19847-19878, 2022
Mandates: US National Science Foundation, US Department of Defense
Sharp bounds for federated averaging (local sgd) and continuous perspective
MR Glasgow, H Yuan, T Ma
International Conference on Artificial Intelligence and Statistics, 9050-9090, 2022
Mandates: US National Science Foundation
Deep learning identifies robust gender differences in functional brain organization and their dissociable links to clinical symptoms in autism
K Supekar, C de Los Angeles, S Ryali, K Cao, T Ma, V Menon
The British Journal of Psychiatry 220 (4), 202-209, 2022
Mandates: US National Science Foundation, US National Institutes of Health
Safe reinforcement learning by imagining the near future
G Thomas, Y Luo, T Ma
Advances in Neural Information Processing Systems 34, 13859-13869, 2021
Mandates: US National Science Foundation, US Department of Defense
Learning barrier certificates: Towards safe reinforcement learning with zero training-time violations
Y Luo, T Ma
Advances in Neural Information Processing Systems 34, 25621-25632, 2021
Mandates: US National Science Foundation, US Department of Defense
Calibrating predictions to decisions: A novel approach to multi-class calibration
S Zhao, M Kim, R Sahoo, T Ma, S Ermon
Advances in Neural Information Processing Systems 34, 22313-22324, 2021
Mandates: US National Science Foundation, US Department of Defense
Why do pretrained language models help in downstream tasks? an analysis of head and prompt tuning
C Wei, SM Xie, T Ma
Advances in Neural Information Processing Systems 34, 16158-16170, 2021
Mandates: US National Science Foundation, US Department of Defense
Label noise sgd provably prefers flat global minimizers
A Damian, T Ma, JD Lee
Advances in Neural Information Processing Systems 34, 27449-27461, 2021
Mandates: US National Science Foundation, US Department of Defense
Provable guarantees for self-supervised deep learning with spectral contrastive loss
JZ HaoChen, C Wei, A Gaidon, T Ma
Advances in Neural Information Processing Systems 34, 5000-5011, 2021
Mandates: US National Science Foundation
Provable model-based nonlinear bandit and reinforcement learning: Shelve optimism, embrace virtual curvature
K Dong, J Yang, T Ma
Advances in neural information processing systems 34, 26168-26182, 2021
Mandates: US National Science Foundation
Shape matters: Understanding the implicit bias of the noise covariance
JZ HaoChen, C Wei, J Lee, T Ma
Conference on Learning Theory, 2315-2357, 2021
Mandates: US National Science Foundation, US Department of Defense
Composed fine-tuning: Freezing pre-trained denoising autoencoders for improved generalization
SM Xie, T Ma, P Liang
International Conference on Machine Learning, 11424-11435, 2021
Mandates: US National Science Foundation, US Department of Defense
Active online learning with hidden shifting domains
Y Chen, H Luo, T Ma, C Zhang
International Conference on Artificial Intelligence and Statistics, 2053-2061, 2021
Mandates: US National Science Foundation
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