Learning Graphical Models
Reconciling λ-Returns with Experience Replay
Brett Daley, Christopher Amato
A unique benefit to this approach is that each transition's TD error can be
Causal Inference via Kernel Deviance Measures
Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh
Neural Information Processing Systems http://nips.cc/
Generative Well-intentioned Networks
An essential aspect of any machine learning system is understanding what the model does not know.
Learning to Play With Intrinsically-Motivated, Self-Aware Agents
Nick Haber, Damian Mrowca, Stephanie Wang, Li F. Fei-Fei, Daniel L. Yamins
Neural Information Processing Systems http://nips.cc/
State Regularized Policy Optimization on Data with Dynamics Shift
We then demonstrate a lower-bound performance guarantee on policies regularized by the stationary state distribution. In practice, SRPO can be an add-on module to context-based algorithms in both online and offline RL settings.
Multi-domain Causal Structure Learning in Linear Systems
AmirEmad Ghassami, Negar Kiyavash, Biwei Huang, Kun Zhang
Neural Information Processing Systems http://nips.cc/
A Bayes-Sard Cubature Method
Toni Karvonen, Chris J. Oates, Simo Sarkka
Neural Information Processing Systems http://nips.cc/
Causal Component Analysis
Independent Component Analysis (ICA) aims to recover independent latent variables from observed mixtures thereof.