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  • Seoul National University - Machine Intelligence Lab @SNUEE
    Seoul National University - Machine Intelligence Lab @SNUEE
  • Relevance Similarity Scorer and Entity Guided Reranking for Knowledge . . .
    fhkbae, minwoolee, ahhyeon kim, wanted1007, kjungg@snu ac kr flcj8004, cheoneum park, donghyeon kimg@hyundai com Abstract This paper describes our system for the Ninth Dialogue Sys-tem Technology Challenge (DSTC9) Track1, which aims to generate the response for the given dialog using the proper external knowledge Our system focuses on
  • MiLab Diagnostics
    MiLab Diagnostics Where Veterinary Practice Laboratory Come Together Forgot? Log In
  • People - MLLAB at SNU - Seoul National University
    MLLAB, Computer Science and Engineering, Seoul National University Location Samsung Electronics-Seoul National University Research Center (Building 944), 1, Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea
  • Learning to Detect Incongruence in News Headline and Body Text via a . . .
    Corresponding author: Kyomin Jung (kjung@snu ac kr) The work of Taegyun Kim and Meeyoung Cha was supported in part by the Institute for Basic Science in South Korea under Grant IBS-R029-C2, and in part by the Basic Science Research Program through the National Research Foundation of Korea under Grant NRF-2017R1E1A1A01076400
  • 연구실소개 - 서울대학교 공과대학 전기∙정보공학부
    연구실소개 및 연구분야; 본 연구실의 주요 연구 분야는 머신 러닝이며, 딥 러닝 기반의 기술을 다양한 분야에 적용하고 있다
  • Minimizing Expected Losses in Perturbation Models with Multidimensional . . .
    fadkim955, kjungg@snu ac kr Yongsub Lim KAIST Daejeon, South Korea ddiyong@kaist ac kr Daniel Tarlow, Pushmeet Kohli Microsoft Research Cambridge, UK fdtarlow, pkohlig@microsoft com Abstract We consider the problem of learning perturbation-based probabilistic models by computing and differentiating expected losses This is a challenging
  • Improving Context-Aware Neural Machine Translation Using Self …milab . . .
    Improving Context-Aware Neural Machine Translation Using Self-Attentive Sentence Embedding Hyeongu Yun 1 * , Yongkeun Hwang 1 * , and Kyomin Jung 12 1 Seoul National University, Seoul, Korea 2 Automation and Systems Research Institute, Seoul National University, Seoul, Korea {youaredead, wangcho2k, kjung} @snu ac kr Abstract Fully Attentional Networks (FAN) like Transformer (Vaswani et al
  • Automatic Question Answering System for Consumer Products - milab. snu. ac. kr
    Automatic Question Answering System for Consumer Products Seunghyun Yoon1,3(B), Mohan Sundar2, Abhishek Gupta2, and Kyomin Jung1,4 1 Dt of E and Computer E, S National Universit, S, K {mysmilesh,kjung}@snu ac kr2 S R D Institute I, B, I {sundar,abhishek gu}@samsung com3 S Sware R D Cen, S, K 4 A and Systems Rh I, S National Universit, S, K
  • 서울대학교 전기·정보공학부 정교민 - 김박사넷
    김박사넷에서 제공하는 서울대학교 전기·정보공학부 정교민 연구실 상세 정보입니다
  • Stability of the Max-Weight Protocol in Adversarial Wireless Networks
    IEEE ACM TRANSACTIONS ON NETWORKING, VOL 22, NO 6, DECEMBER 2014 1859 Stability of the Max-Weight Protocol in Adversarial Wireless Networks Sungsu Lim,StudentMember,IEEE, Kyomin Jung, Member, IEEE, and Matthew Andrews, Senior Member, IEEE Abstract—In this paper, we consider the MAX-WEIGHT protocol for routing and scheduling in wireless networks under an adver-
  • Surf at MEDIQA 2019: Improving Performance of Natural Language . . .
    the proposed methods by achieving 90 6% ac-curacy in medical domain natural language in-ference task Furthermore, we inspect the inde-pendent strengths of the proposed approaches in quantitative and qualitative manners This analysis will help researchers to select neces-sary components in building models for the medical domain 1 Introduction
  • Efficient Energy Minimization for Enforcing Label Statistics
    Efficient Energy Minimization for Enforcing Label Statistics Yongsub Lim, Kyomin Jung, and Pushmeet Kohli Abstract—Energy minimization algorithms, such as graph cuts, enable the
  • CrossAug: A Contrastive Data Augmentation Method for Debiasing Fact . . .
    CrossAug: A Contrastive Data Augmentation Method for Debiasing Fact Verification Models MinwooLee1, SeungpilWon 1, JuaeKim2, HwanheeLee, CheoneumPark2, KyominJung1 1 Dept of Electrical and Computer Engineering, Seoul National University 2 AIRS Company, Hyundai Motor Group
  • LNCS 8238 - Aspects of Rumor Spreading on a Microblog Network
    Aspects of Rumor Spreading on a Microblog Network Sejeong Kwon 1, Meeyoung Cha , Kyomin Jung2, Wei Chen 3,andYajunWang 1 Korea Advanced Institue of Science and Technology, Republic of Korea {gsj1029,meeyoungcha}@kaist ac kr2 Seoul National University, Republic of Korea kjung@snu ac kr 3 Microsoft Research Asia, China {weic,yajunw}@microsoft comAbstract Rumors have been studied for several





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