Unraveling the reasons behind the remarkable success and exceptional
gen...
Out-of-Distribution (OOD) detection, i.e., identifying whether an input ...
Recent advances on large-scale pre-training have shown great potentials ...
Out-of-distribution (OOD) detection is a critical task for ensuring the
...
Cooperative multi-agent reinforcement learning (MARL) is making rapid
pr...
Deep neural networks are susceptible to adversarially crafted, small and...
Fine-tuning from pre-trained ImageNet models has been a simple, effectiv...
Generalization to out-of-distribution (OOD) data, or domain generalizati...
The mismatch between training and target data is one major challenge for...
Automated data augmentation has shown superior performance in image
reco...
This paper investigates the finite-sample prediction risk of the
high-di...
Learning under multi-environments often requires the ability of
out-of-d...