카이스트 전기및전자공학부는 활발한 인공지능 및 머신러닝 연구와 그 성과로, 인공지능 및 머신러닝 TOP Conferecne인 ICML 2019에 인공지능 및 머신러닝의 다양한 분야에서 9편의 논문을 게재 및 발표하는 훌륭한 성과를 거두었다. 발표된 논문의 목록은 다음과 같다.
TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning
Sung Whan Yoon, Jun Seo and Jaekyun Moon
Dimension-Wise Importance Sampling Weight Clipping for Sample-Efficient Reinforcement Learning
Seungyul Han and Youngchul Sung
Weak Detection of Signal in the Spiked Wigner Model
Hye Won Chung and Ji Oon Lee
QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
Kyunghwan Son, Daewoo Kim, Wan Ju Kang, David Earl Hostallero and Yung Yi
Learning What and Where to Transfer
Yunhun Jang, Hankook Lee, Sung Ju Hwang and Jinwoo Shin
Training CNNs with Selective Allocation of Channels
Jongheon Jeong and Jinwoo Shin
Robust Inference via Generative Classifiers for Handling Noisy Labels
Kimin Lee , Sukmin Yun, Kibok Lee, Honglak Lee, Bo Li and Jinwoo Shin
Using Pre-Training Can Improve Model Robustness and Uncertainty
Dan Hendrycks, Kimin Lee and Mantas Mazeika
Spectral Approximate Inference
Sejun Park, Eunho Yang, Se-Young Yun and Jinwoo Shin
