Skip to yearly menu bar Skip to main content


Search All 2024 Events
 

32 Results

<<   <   Page 1 of 3   >   >>
Poster
Fri 11:00 Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization
Dang Nguyen · Paymon Haddad · Eric Gan · Baharan Mirzasoleiman
Tutorial
Tue 13:30 Out-of-Distribution Generalization: Shortcuts, Spuriousness, and Stability
Maggie Makar · Aahlad Manas Puli · Yoav Wald
Poster
Thu 11:00 Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift
Jiayun Wu · Jiashuo Liu · Peng Cui · Steven Wu
Poster
Wed 16:30 AHA: Human-Assisted Out-of-Distribution Generalization and Detection
Haoyue Bai · Jifan Zhang · Robert Nowak
Poster
Thu 16:30 Hierarchical Hybrid Sliced Wasserstein: A Scalable Metric for Heterogeneous Joint Distributions
Khai Nguyen · Nhat Ho
Workshop
Sun 9:30 Lightning Talk: Compositional Generalization Across Distributional Shifts with Sparse Tree Operations
Poster
Wed 16:30 Vision Transformer Neural Architecture Search for Out-of-Distribution Generalization: Benchmark and Insights
Sy-Tuyen Ho · Tuan Van Vo · Somayeh Ebrahimkhani · Ngai-Man (Man) Cheung
Workshop
Benign Overfitting in Out-of-Distribution Generalization of Linear Models
Shange Tang · Jiayun Wu · Jianqing Fan · Chi Jin
Workshop
Improving out-of-distribution generalization by mimicking the human visual diet.
Spandan Madan · You Li · Mengmi Zhang · Hanspeter Pfister · Gabriel Kreiman
Poster
Fri 11:00 What Variables Affect Out-of-Distribution Generalization in Pretrained Models?
Md Yousuf Harun · Kyungbok Lee · Gianmarco Gallardo · Giri Krishnan · Christopher Kanan
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
Thu 11:00 Exponential Quantum Communication Advantage in Distributed Inference and Learning
Dar Gilboa · Hagay Michaeli · Daniel Soudry · Jarrod McClean