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04/06/2023
Heavy-Tailed Regularization of Weight Matrices in Deep Neural Networks
Unraveling the reasons behind the remarkable success and exceptional gen...
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12/24/2022
Boosting Out-of-Distribution Detection with Multiple Pre-trained Models
Out-of-Distribution (OOD) detection, i.e., identifying whether an input ...
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10/17/2022
ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization
Recent advances on large-scale pre-training have shown great potentials ...
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10/09/2022
Boosting Out-of-distribution Detection with Typical Features
Out-of-distribution (OOD) detection is a critical task for ensuring the ...
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06/01/2022
Policy Diagnosis via Measuring Role Diversity in Cooperative Multi-agent RL
Cooperative multi-agent reinforcement learning (MARL) is making rapid pr...
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11/09/2021
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps
Deep neural networks are susceptible to adversarially crafted, small and...
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08/07/2021
NASOA: Towards Faster Task-oriented Online Fine-tuning with a Zoo of Models
Fine-tuning from pre-trained ImageNet models has been a simple, effectiv...
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06/08/2021
Towards a Theoretical Framework of Out-of-Distribution Generalization
Generalization to out-of-distribution (OOD) data, or domain generalizati...
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01/21/2021
Out-of-Distribution Generalization Analysis via Influence Function
The mismatch between training and target data is one major challenge for...
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12/22/2020
MetaAugment: Sample-Aware Data Augmentation Policy Learning
Automated data augmentation has shown superior performance in image reco...
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08/14/2020
Provable More Data Hurt in High Dimensional Least Squares Estimator
This paper investigates the finite-sample prediction risk of the high-di...
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06/13/2020
