Search Results for author:
Found 6 papers, 2 papers with code
Variational Inference for Sequential Data with Future Likelihood Estimates
The estimated future likelihoods form the core of our new low-variance gradient estimator.
LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation
We consider the problem of learning from observation (LfO), in which the agent aims to mimic the expert's behavior from the state-only demonstrations by experts.
Multi-View Representation Learning via Total Correlation Objective
Multi-View Representation Learning (MVRL) aims to discover a shared representation of observations from different views with the complex underlying correlation.
DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations
We consider offline imitation learning (IL), which aims to mimic the expert's behavior from its demonstration without further interaction with the environment.
Variational Interaction Information Maximization for Cross-domain Disentanglement
Grounded in information theory, we cast the simultaneous learning of domain-invariant and domain-specific representations as a joint objective of multiple information constraints, which does not require adversarial training or gradient reversal layers.
Monte-Carlo Tree Search for Constrained POMDPs
In this paper, we present CC-POMCP (Cost-Constrained POMCP), an online MCTS algorithm for large CPOMDPs that leverages the optimization of LP-induced parameters and only requires a black-box simulator of the environment.
