226 citations · 603 across the 11 of their papers we have counts for
3 papers · 1 filter
PAC-Net: A Model Pruning Approach to Inductive Transfer Learning
Sanghoon Myung, In Huh, Wonik Jang +5
Inductive transfer learning aims to learn from a small amount of training data for the target task by utilizing a pre-trained model from the source task. Most strategies that invol…
Augment & Valuate : A Data Enhancement Pipeline for Data-Centric AI
Youngjune Lee, Oh Joon Kwon, Haeju Lee +3
Data scarcity and noise are important issues in industrial applications of machine learning. However, it is often challenging to devise a scalable and generalized approach to addre…
Learning to Cooperate via Policy Search
Leonid Peshkin, Kee-Eung Kim, Nicolas Meuleau +1
Cooperative games are those in which both agents share the same payoff structure. Value-based reinforcement-learning algorithms, such as variants of Q-learning, have been applied t…