14 citations · 23 across the 11 of their papers we have counts for
3 papers · 1 filter
Rethinking State Disentanglement in Causal Reinforcement Learning
Haiyao Cao, Zhen Zhang, Panpan Cai +7
One of the significant challenges in reinforcement learning (RL) when dealing with noise is estimating latent states from observations. Causality provides rigorous theoretical supp…
Bayesian Learned Models Can Detect Adversarial Malware For Free
Bao Gia Doan, Dang Quang Nguyen, Paul Montague +6
The vulnerability of machine learning-based malware detectors to adversarial attacks has prompted the need for robust solutions. Adversarial training is an effective method but is…
Premonition: Using Generative Models to Preempt Future Data Changes in Continual Learning
Mark D. McDonnell, Dong Gong, Ehsan Abbasnejad +1
Continual learning requires a model to adapt to ongoing changes in the data distribution, and often to the set of tasks to be performed. It is rare, however, that the data and task…