연구 성과

Prof. Namhoon Lee’s collaborative work to be published at NeurIPS 2021

“Meta-Learning Sparse Implicit Neural Representations” by {Jaeho Lee*, Jihoon Tack*}, Namhoon Lee, Jinwoo Shin Abstract: Implicit neural representations are a promising new avenue of representing general signals by learning a continuous function that, parameterized as a neural network, maps the domain of a signal to its...

VIP Lab’s (Prof. Jae-Young Sim) paper presented at ICCV 2021

Visual Information Processing (VIP) lab’s paper has been presented at International Conference on Computer Vision (ICCV) 2021, one of the top conferences in computer vision. Person search suffers from the conflicting objectives of commonness and uniqueness between the two sub-tasks of person detection and re-identification that...

SDM Lab’s (Prof. Gi-Soo Kim) collaborative work to be published at NeurIPS 2021

Statistical Decision Making (SDM) lab’s paper is accepted to 35th Conference on Neural Information Processing Systems (NeurIPS) 2021, one of the top-3 conferences for artificial intelligence and machine learning. A challenging aspect of the bandit problem is that a stochastic reward is observed only for the...

LIM Lab’s (Prof. Sungbin Lim) paper accepted to NeurIPS 2021

Learning Intelligent Machine (LIM) lab’s paper is accepted to 35th Conference on Neural Information Processing Systems (NeurIPS) 2021, one of the top-3 conferences for artificial intelligence and machine learning. Bootstrapping has been a primary tool for ensemble and uncertainty quantification in machine learning and statistics. However, due...

Stereo Object Matching Network(Prof. Kyungdon Joo)

저 자 {Jaesung Choe, Kyungdon Joo}*, Francois Rameau, and In So Kweon 학 회 IEEE International Conference on Robotics and Automation (ICRA) 논문일시(Year) 2021 논문일시(Month) 06   Abstract This paper presents a stereo object matching method that exploits both 2D contextual information from images as well as 3D object-level information. Unlike existing stereo matching methods that...

“Architecture-accuracy co-optimization of reram-based low-cost neural network processor” (Prof. Lee, Jong-Eun)

Architecture-Accuracy Co-optimization of ReRAM-based Low-cost Neural Network Processor Authors: Segi Lee, Sugil Lee, Jongeun Lee, Jong-Moon Choi, Do-Wan Kwon, Seung-Kwang Hong, Kee-Won Kwon Authors Info & Affiliations Publication:GLSVLSI '20: Proceedings of the 2020 on Great Lakes Symposium on VLSISeptember 2020 Pages 427–432https://doi.org/10.1145/3386263.3406954   Abstract Resistive RAM (ReRAM)...