ICML 2019 카이스트 전기및전자공학부 게재 성과

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 거두었습니다. 발표된 논문의 목록은 다음과 같습니다.


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