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교수소개

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  • 소프트웨어학과

교수소개

전임교수 -

소프트웨어학과

  • 부교수 데이터마이닝
  • 이종욱 홈페이지 바로가기

관심분야

추천시스템 
정보검색
자연어처리
기계학습

학력

  • (Ph.D.) 2012 포항공과대학교 컴퓨터공학과
  • (B.S.) 2006 성균관대학교 정보통신공학부

약력/경력

  • 2016.09 – 현재 성균관대학교 소프트웨어학과 교수
  • 2014.09 – 2016.08 한국외국어대학교 컴퓨터공학과 교수
  • 2012.12 – 2014.8 The Pensylvania State University, 박사 후 연구원
  • 2012.03 – 2014.11 포항공과대학교, 박사 후 연구원

학술지 논문

  • (2023)  Saliency as Pseudo-Pixel Supervision for Weakly and Semi-Supervised Semantic Segmentation.  IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE.  45,  10
  • (2023)  Your lottery ticket is damaged: Towards all-alive pruning for extremely sparse networks.  INFORMATION SCIENCES.  634, 
  • (2023)  CoMix: Collaborative filtering with mixup for implicit datasets.  INFORMATION SCIENCES.  628, 
  • (2022)  Knowledge distillation meets recommendation: collaborative distillation for top-N recommendation.  KNOWLEDGE AND INFORMATION SYSTEMS.  64,  5
  • (2021)  Distilling from professors: Enhancing the knowledge distillation of teachers.  INFORMATION SCIENCES.  576,  1

학술회의논문

  • (2023)  GLEN: Generative Retrieval via Lexical Index Learning.  Empirical Methods in Natural Language Processing.  싱가포르
  • (2023)  It Ain’t Over: A Multi-aspect Diverse MathWord Problem Dataset.  Empirical Methods in Natural Language Processing.  싱가포르
  • (2023)  Forgetting-aware Linear Bias for Attentive Knowledge Tracing.  ACM Conference on Information and Knowledge Management.  영국
  • (2023)  Toward a Better Understanding of Loss Functions for Collaborative Filtering.  ACM Conference on Information and Knowledge Management.  영국
  • (2023)  ConQueR: Contextualized Query Reduction using Search Logs.  ACM SIGIR Conference on Information Retrieval.  중국
  • (2023)  It’s Enough: Relaxing Diagonal Constraints in Linear Autoencoders for Recommendation.  ACM SIGIR Conference on Information Retrieval.  중국
  • (2023)  uCTRL: Unbiased Contrastive Representation Learning via Alignment and Uniformity for Collaborative Filtering.  ACM SIGIR Conference on Information Retrieval.  중국
  • (2022)  Long-tail Mixup for Extreme Multi-label Classification.  ACM Conference on Information and Knowledge Management.  미국
  • (2022)  SpaDE: Improving Sparse Representations using a Dual Document Encoder for First-stage Retrieval.  ACM Conference on Information and Knowledge Management.  미국
  • (2022)  Logit Mixing Training for More Reliable and Accurate Prediction.  International Joint Conference on Artificial Intelligence.  미국
  • (2022)  Bilateral Self-unbiased Learning from Biased Implicit Feedback.  ACM SIGIR Conference on Information Retrieval.  대한민국
  • (2022)  S-Walk: Accurate and Scalable Session-based Recommendation with Random Walks.  ACM International Conference on Web Search and Data Mining.  미국
  • (2021)  Dual Unbiased Recommender Learning for Implicit Feedback.  ACM SIGIR Conference on Information Retrieval.  미국
  • (2021)  Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic Segmentation.  Conference on Computer Vision and Pattern Recognition.  미국
  • (2021)  MelBERT: Metaphor Detection via Contextualized Late Interaction using Metaphorical Identification Theories.  Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.  미국