Qing kai guo jing ji fa zhan shi

von Zhao, Duo
Veröffentlicht 1992

EFFICIENT APPROXIMATION OF DEEP RELU NETWORKS FOR FUNCTIONS ON LOW DIMENSIONAL MANIFOLDS

von Chen, Minshuo
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 11 of 20 (2020)

BESOV FUNCTION APPROXIMATION AND BINARY CLASSIFICATION ON LOW-DIMENSIONAL MANIFOLDS USING CONVOLUTIONAL RESIDUAL NETWORKS

von LIU, HAO
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 9 of 16 (2022)

bai qiu en dai fu

von zhang jun xiang
Veröffentlicht 1978

WHY DO DEEP RESIDUAL NETWORKS GENERALIZE BETTER THAN DEEP FEEDFORWARD NETWORKS? – A NEURAL TANGENT KERNEL PERSPECTIVE

von Huang, Kaixuan
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 4 of 27 (2021)

DEEP REINFORCEMENT LEARNING WITH ROBUST AND SMOOTH POLICY

von Shen, Qianli
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 12 of 15 (2021)

chang jiang san xia

von zhao duo duo
Veröffentlicht 19916

META LEARNING WITH RELATIONAL INFORMATION FOR SHORT SEQUENCES

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

zhe xue de yan jiu

von zeng zhao duo
Veröffentlicht

On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds

von Dahal, Biraj
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 14 of 50 (2023)

Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL

von Chen, Minshuo
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 22 of 36 (2022)

Benefits of Overparameterized Convolutional Residual Networks: Function Approximation Under Smoothness Constraint

von Liu, Hao
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 17 of 33 (2023)

TOWARDS UNDERSTANDING THE IMPORTANCE OF SHORTCUT CONNECTIONS IN RESIDUAL NETWORKS

von Liu, Tianyi
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 10 of 20 (2020)

PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance

von Zhang, Qingru
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 32 of 33 (2023)

TOWARDS UNDERSTANDING HIERARCHICAL LEARNING: BENEFITS OF NEURAL REPRESETATIONS

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

DIFFERENTIABLE TOP-K WITH OPTIMAL TRANSPORT

von Xie, Yujia
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 25 of 27 (2021)

HOW IMPORTANT IS THE TRAIN-VALIDATION SPLIT IN META-LEARNING?

von BAI, YU
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 1 of 16 (2022)