firstbacksecondback
72 Results
Workshop
|
Genetic Curriculum Learning for Distribution Generalization on the Travelling Salesman Problem Michael Li · Christopher Haberland · Natasha Jaques |
||
Poster
|
Thu 16:30 |
Improving Generalization in Federated Learning with Model-Data Mutual Information Regularization: A Posterior Inference Approach Hao Zhang · Chenglin Li · Nuowen Kan · Ziyang Zheng · Wenrui Dai · Junni Zou · Hongkai Xiong |
|
Poster
|
Fri 16:30 |
Optimizing over Multiple Distributions under Generalized Quasar-Convexity Condition Ding Shihong · Long Yang · Luo Luo · Cong Fang |
|
Workshop
|
Can Bayesian Neural Networks Make Confident Predictions? Katharine Fisher |
||
Workshop
|
Compositional Risk Minimization Divyat Mahajan · Mohammad Pezeshki · Ioannis Mitliagkas · Kartik Ahuja · Pascal Vincent |
||
Workshop
|
Sat 17:27 |
Multi-Output Distributional Fairness via Post-Processing Gang Li · Qihang Lin · Ayush Ghosh · Tianbao Yang |
|
Workshop
|
Multi-Output Distributional Fairness via Post-Processing Gang Li · Qihang Lin · Ayush Ghosh · Tianbao Yang |
||
Poster
|
Thu 16:30 |
Generalize or Detect? Towards Robust Semantic Segmentation Under Multiple Distribution Shifts Zhitong Gao · Bingnan Li · Mathieu Salzmann · Xuming He |
|
Workshop
|
Compositional Generalization Across Distributional Shifts with Sparse Tree Operations Paul Soulos · Henry Conklin · Mattia Opper · Paul Smolensky · Jianfeng Gao · Roland Fernandez |
||
Poster
|
Wed 11:00 |
Compositional Generalization Across Distributional Shifts with Sparse Tree Operations Paul Soulos · Henry Conklin · Mattia Opper · Paul Smolensky · Jianfeng Gao · Roland Fernandez |
|
Workshop
|
Dynamics of Concept Learning and Compositional Generalization Yongyi Yang · Core Francisco Park · Ekdeep S Lubana · Maya Okawa · Wei Hu · Hidenori Tanaka |
||
Poster
|
Wed 16:30 |
Near-Optimal Distributionally Robust Reinforcement Learning with General Lp Norms Pierre Clavier · Laixi Shi · Erwan Le Pennec · Eric Mazumdar · Adam Wierman · Matthieu Geist |