Technology
On the Hardness of Robust Classification
Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell
Neural Information Processing Systems http://nips.cc/
Nonparametric Density Estimation under Adversarial Losses
Shashank Singh, Ananya Uppal, Boyue Li, Chun-Liang Li, Manzil Zaheer, Barnabas Poczos
Neural Information Processing Systems http://nips.cc/
GAMA: GenerativeAdversarialMulti-Object SceneAttacks
On the other hand, natural scenes include multiple dominant objects that are semantically related.
A Simple Remedy for Dataset Bias via Self-Influence: A Mislabeled Sample Perspective Y eonsung Jung
However, spurious correlation remains an ongoing challenge, primarily due to the difficulty in precisely detecting these samples.
Checklist
When drawing 1,000 z from the priorp(z)of the latent space learned by PLAS, only4%of the samples are decoded as high-return actions, while inLAPO,45%ofthedecoded actions arehigh-return actions.
LAPO: Latent-VariableAdvantage-WeightedPolicy OptimizationforOfflineReinforcementLearning
But in practice, it requires querying the behavior policy which is unknown, and using an erroneous approximation of the behavior policy can negatively affect the performance ([39]).
Maximizing acquisition functions for Bayesian optimization
James Wilson, Frank Hutter, Marc Deisenroth
Neural Information Processing Systems http://nips.cc/
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle
Dinghuai Zhang, Tianyuan Zhang, Yiping Lu, Zhanxing Zhu, Bin Dong
Neural Information Processing Systems http://nips.cc/
