19 citations · 44 across the 13 of their papers we have counts for
6 papers · 1 filter
Optimal Algorithms for Stochastic Multi-Armed Bandits with Heavy Tailed Rewards
Kyungjae Lee, Hongjun Yang, Sungbin Lim +1
In this paper, we consider stochastic multi-armed bandits (MABs) with heavy-tailed rewards, whose -th moment is bounded by a constant for . First, we propose a…
Generative Autoregressive Networks for 3D Dancing Move Synthesis from Music
Hyemin Ahn, Jaehun Kim, Kihyun Kim +1
This paper proposes a framework which is able to generate a sequence of three-dimensional human dance poses for a given music. The proposed framework consists of three components:…
Tsallis Reinforcement Learning: A Unified Framework for Maximum Entropy Reinforcement Learning
Kyungjae Lee, Sungyub Kim, Sungbin Lim +2
In this paper, we present a new class of Markov decision processes (MDPs), called Tsallis MDPs, with Tsallis entropy maximization, which generalizes existing maximum entropy reinfo…
Maximum Causal Tsallis Entropy Imitation Learning
Kyungjae Lee, Sungjoon Choi, Songhwai Oh
In this paper, we propose a novel maximum causal Tsallis entropy (MCTE) framework for imitation learning which can efficiently learn a sparse multi-modal policy distribution from d…
Text2Action: Generative Adversarial Synthesis from Language to Action
Hyemin Ahn, Timothy Ha, Yunho Choi +2
In this paper, we propose a generative model which learns the relationship between language and human action in order to generate a human action sequence given a sentence describin…
Sparse Markov Decision Processes with Causal Sparse Tsallis Entropy Regularization for Reinforcement Learning
Kyungjae Lee, Sungjoon Choi, Songhwai Oh
In this paper, a sparse Markov decision process (MDP) with novel causal sparse Tsallis entropy regularization is proposed.The proposed policy regularization induces a sparse and mu…