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03/12/2021
Discovering Diverse Solutions in Deep Reinforcement Learning
Reinforcement learning (RL) algorithms are typically limited to learning...
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10/20/2020
Robust Imitation Learning from Noisy Demonstrations
Learning from noisy demonstrations is a practical but highly challenging...
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06/04/2020
Meta-Model-Based Meta-Policy Optimization
Model-based reinforcement learning (MBRL) has been applied to meta-learn...
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09/15/2019
VILD: Variational Imitation Learning with Diverse-quality Demonstrations
The goal of imitation learning (IL) is to learn a good policy from high-...
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01/27/2019
Imitation Learning from Imperfect Demonstration
Imitation learning (IL) aims to learn an optimal policy from demonstrati...
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01/05/2019
Hierarchical Reinforcement Learning via Advantage-Weighted Information Maximization
Real-world tasks are often highly structured. Hierarchical reinforcement...
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12/19/2018
TD-Regularized Actor-Critic Methods
Actor-critic methods can achieve incredible performance on difficult rei...
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12/06/2018
Active Deep Q-learning with Demonstration
Recent research has shown that although Reinforcement Learning (RL) can ...
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06/13/2018
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Uncertainty computation in deep learning is essential to design robust a...
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12/04/2017
Vprop: Variational Inference using RMSprop
Many computationally-efficient methods for Bayesian deep learning rely o...
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11/15/2017
Variational Adaptive-Newton Method for Explorative Learning
We present the Variational Adaptive Newton (VAN) method which is a black...
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05/22/2017
Deep Reinforcement Learning with Relative Entropy Stochastic Search
Many reinforcement learning methods for continuous control tasks are bas...
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11/10/2016
Policy Search with High-Dimensional Context Variables
Direct contextual policy search methods learn to improve policy paramete...
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08/05/2015
Direct Estimation of the Derivative of Quadratic Mutual Information with Application in Supervised Dimension Reduction
A typical goal of supervised dimension reduction is to find a low-dimens...
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04/28/2014
Conditional Density Estimation with Dimensionality Reduction via Squared-Loss Conditional Entropy Minimization
Regression aims at estimating the conditional mean of output given input...
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07/19/2013
Model-Based Policy Gradients with Parameter-Based Exploration by Least-Squares Conditional Density Estimation
The goal of reinforcement learning (RL) is to let an agent learn an opti...
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01/17/2013
