In reinforcement learning (RL), a reward function is often assumed at th...
Most existing works consider direct perturbations of victim's state/acti...
Our work focuses on the challenge of detecting outputs generated by Larg...
Reinforcement learning-based policies for continuous control robotic
nav...
Directed Exploration is a crucial challenge in reinforcement learning (R...
We present a novel approach to improve the performance of deep reinforce...
In this paper, we present a novel Heavy-Tailed Stochastic Policy Gradien...
In this work, we propose a novel Kernelized Stein
Discrepancy-based Post...
We focus on parameterized policy search for reinforcement learning over
...
Representation Learning in a heterogeneous space with mixed variables of...
In the realms of computer vision, it is evident that deep neural network...
Representation of data on mixed variables, numerical and categorical typ...
Feature learning in the presence of a mixed type of variables, numerical...