서울대학교가 오는 2월 2일부터 8일간 열리는 제35회 인공지능선도학회(Association for the Advancement of Artificial Intelligence - AAAI) 2021에서 10편의 논문을 발표한다. 

김건희 교수(컴퓨터공학부)와 최진영 교수(전기정보공학부) 연구팀에서 2편을 발표하며, 곽노준 교수(융합과학기술대학원 지능정보융합학과), 이재욱 교수(산업공학과), 장병탁 교수(컴퓨터공학부), 정교민 교수(전기정보공학부), 조명희 교수(자연과학대학 통계학과)이 각 한편씩 발표한다. 

AAAI 2021

• Neural Sequence-to-grid Module for Learning Symbolic Rules (Segwang Kim, Hyoungwook Nam, Joonyoung Kim, and Kyomin Jung) #정교민 #전기정보공학부
• Self-supervised pre-training and contrastive representation learning for multiple-choice video QA (Seonhoon Kim, Seohyeong Jeong, Eunbyul Kim, Inho Kang, Nojun Kwak) #곽노준 #지능정보융합학과
• Class-Attentive Diffusion Network for Semi-Supervised Classification (Jongin Lim, Daeho Um, Hyung Jin Chang, Dae Ung Jo, Jin Young Choi) #최진영 #전기정보공학부
• AutoLR: Layer-wise Pruning and Auto-tuning of Learning Rates in Fine-tuning of Deep Networks (Youngmin Ro, Jin Young Choi) #최진영 #전기정보공학부
• Dual Compositional Learning in Interactive Image Retrieval (Jongseok Kim, Youngjae Yu, Hoeseong Kim, Gunhee Kim) #김건희 #컴퓨터공학부
• IB-GAN: Disengangled Representation Learning with Information Bottleneck Generative Adversarial Networks (Insu Jeon, Wonkwang Lee, Myeongjang Pyeon and Gunhee Kim) #김건희 #컴퓨터공학부
• Understanding Catastrophic Overfitting in Single-Step Adversarial Training (Hoki Kim, Woojin Lee, Jaewook Lee) #이재욱 #산업공학과
• DramaQA: Character-Centered Video Story Understanding with Hierarchical QA (Seongho Choi, Kyoung-Woon On, Yu-Jung Heo, Ahjeong Seo, Youwon Jang, Minsu Lee, Byoung-Tak Zhang) #장병탁 #컴퓨터공학부
• Kernel-Convoluted Deep Neural Networks with Data Augmentation (Minjin Kim, Young-geun Kim, Dongha Kim, Yongdai Kim, Myunghee Cho Paik) #조명희 #통계학과
• Image-to-Image Retrieval by Learning Similarity between Scene Graphs (Sangwoong Yoon, Woo Young Kang, Sungwook Jeon, SeongEun Lee, Changjin Han, Jonghun Park, Eun-Sol Kim)