DATA-DEPENDENT SAMPLE COMPLEXITY OF DEEP NEURAL NETWORKS VIA LIPSCHITZ AUGMENTATION

von Wei, Colin
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 13 of 20 (2020)

FEDERATED ACCELERATED STOCHASTIC GRADIENT DESCENT

von Yuan, Honglin
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 7 of 27 (2021)

Learning Barrier Certificates: Towards Safe Reinforcement Learning with Zero Training-time Violations

von Luo, Yuping
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 31 of 36 (2022)

Near-Optimal Algorithms for Autonomous Exploration and Multi-Goal Stochastic Shortest Path

von Cai, Haoyuan
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 4 of 33 (2023)

Safe Reinforcement Learning by Imagining the Near Future

von Thomas, Garrett
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 17 of 36 (2022)

INDIVIDUAL CALIBRATION WITH RANDOMIZED FORECASTING

von Zhao, Shengjia
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 15 of 15 (2021)

Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers

von Wei, Colin
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 16 of 50 (2023)

Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual Curvature

von Dong, Kefan
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 31 of 36 (2022)

TOWARDS EXPLAINING THE REGULARIZATION EFFECT OF INITIAL LARGE LEARNING RATE IN TRAINING NEURAL NETWORKS

von Li, Yuanchi
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 15 of 20 (2020)

Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning

von Wei, Colin
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 20 of 36 (2022)

COMPOSED FINE-TUNING: FREEZING PRE-TRAINED DENOISING AUTOENCODERS FOR IMPROVED GENERALIZATION

von XIE, SANG MICHAEL
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 15 of 16 (2022)

Label Noise SGD Provably Prefers Flat Global Minimizers

von Damian, Alex
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 33 of 36 (2022)

VERIFIED UNCERTAINTY CALIBRATION

von Kumar, Ananya
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 5 of 20 (2020)

Optimal design of process flexibility for general production systems

von Chen, Xi
Veröffentlicht in Operations research (2019)

Robust and On-the-Fly Dataset Denoising for Image Classification

von Song, Jiaming
Veröffentlicht in ECCV (16. : 2020 : Online) Computer vision - ECCV 2020 ; Part 29 (2020)

SELF-TRAINING AVOIDS USING SPURIOUS FEATURES UNDER DOMAIN SHIFT

von Chen, Yining
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 26 of 27 (2021)

Plan Better Amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification

von Pan, Ling
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 21 of 33 (2023)

MODEL-BASED ADVERSARIAL META-REINFORCEMENT LEARNING

von Lin, Zichuan
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 13 of 27 (2021)

Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss

von HaoChen, Jeff Z.
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 7 of 36 (2022)

Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations

von HaoChen, Jeff Z.
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 35 of 50 (2023)