3 citations · 4 across the 5 of their papers we have counts for
5 papers
Skills Regularized Task Decomposition for Multi-task Offline Reinforcement Learning
Minjong Yoo, Sangwoo Cho, Honguk Woo
Reinforcement learning (RL) with diverse offline datasets can have the advantage of leveraging the relation of multiple tasks and the common skills learned across those tasks, henc…
One-shot Imitation in a Non-Stationary Environment via Multi-Modal Skill
Sangwoo Shin, Daehee Lee, Minjong Yoo +2
One-shot imitation is to learn a new task from a single demonstration, yet it is a challenging problem to adopt it for complex tasks with the high domain diversity inherent in a no…
An Efficient Combinatorial Optimization Model Using Learning-to-Rank Distillation
Honguk Woo, Hyunsung Lee, Sangwoo Cho
Recently, deep reinforcement learning (RL) has proven its feasibility in solving combinatorial optimization problems (COPs). The learning-to-rank techniques have been studied in th…
Fixed Priority Global Scheduling from a Deep Learning Perspective
Hyunsung Lee, Michael Wang, Honguk Woo
Deep Learning has been recently recognized as one of the feasible solutions to effectively address combinatorial optimization problems, which are often considered important yet cha…
A Differentiable Ranking Metric Using Relaxed Sorting Operation for Top-K Recommender Systems
Hyunsung Lee, Yeongjae Jang, Jaekwang Kim +1
A recommender system generates personalized recommendations for a user by computing the preference score of items, sorting the items according to the score, and filtering top-K ite…