DO WE REALLY NEED TO ACCESS THE SOURCE DATA? SOURCE HYPOTHESIS TRANSFER FOR UNSUPERVISED DOMAIN ADAPTATION

von Liang, Jian
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 8 of 15 (2021)

INFERENCE STAGE OPTIMIZATION FOR CROSS-SCENARIO 3D HUMAN POSE ESTIMATION

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

Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning

von Lian, Dongze
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 1 of 50 (2023)

Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition

von Zhang, Yifan
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 44 of 50 (2023)

IMPROVING GENERALIZATION IN REINFORCEMENT LEARNING WITH MIXTURE REGULARIZATION

von Wang, Kaixin
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 10 of 27 (2021)

A Balanced and Uncertainty-Aware Approach for Partial Domain Adaptation

von Liang, Jian
Veröffentlicht in ECCV (16. : 2020 : Online) Computer vision - ECCV 2020 ; Part 11 (2020)

Direct Multi-view Multi-person 3D Pose Estimation

von wang, tao
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 16 of 36 (2022)

Towards Understanding Why Lookahead Generalizes Better Than SGD and Beyond

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

Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning

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

EFFICIENT META LEARNING VIA MINIBATCH PROXIMAL UPDATE

von Zhou, Pan
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 2 of 20 (2020)

Rethinking Bottleneck Structure for Efficient Mobile Network Design

von Zhou, Daquan
Veröffentlicht in ECCV (16. : 2020 : Online) Computer vision - ECCV 2020 ; Part 3 (2020)

Sharpness-Aware Training for Free

von DU, JIAWEI
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 31 of 50 (2023)

Adversarial Self-supervised Learning for Semi-supervised 3D Action Recognition

von Si, Chenyang
Veröffentlicht in ECCV (16. : 2020 : Online) Computer vision - ECCV 2020 ; Part 7 (2020)

No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data

von Luo, Mi
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 8 of 36 (2022)

The Geometry of Robust Value Functions

von Wang, Kaixin
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 28 of 33 (2023)

TOWARDS BETTER LAPLACIAN REPRESENTATION IN REINFORCEMENT LEARNING WITH GENERALIZED GRAPH DRAWING

von WANG, KAIXIN
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 14 of 16 (2022)

Slim Scissors: Segmenting Thin Object from Synthetic Background

von Han, Kunyang
Veröffentlicht in ECCV (17. : 2022 : Tel Aviv; Online) Computer vision – ECCV 2022 ; Part 29 (2022)

ConvBERT: Improving BERT with Span-based Dynamic Convolution

von Jiang, Zi-Hang
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 16 of 27 (2021)

TASK SIMILARITY AWARE META LEARNING: THEORY-INSPIRED IMPROVEMENT ON MAML

von Zhou, Pan
Veröffentlicht in Conference on Uncertainty in Artificial Intelligence (37. : 2021 : Online) 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021) ; Part 1 of 3 (2022)

TOWARDS THEORETICALLY UNDERSTANDING WHY SGD GENERALIZES BETTER THAN ADAM IN DEEP LEARNING

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