영욱 선배 CVPR2023

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Recent Publication & News

  • [ICML 2025] paper accepted (spotlight poster) : “Policy-labeled Preference Learning: Is Preference Enough for RLHF?”, Taehyun Cho*, Seokhun Ju*, Seungyub Han, Dohyeong Kim, Kyungjae Lee, Jungwoo Lee

  • [ICML 2025] paper accepted : “Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation”, Taehyun Cho, Seungyub Han, Seokhun Ju, Dohyeong Kim, Kyungjae Lee, Jungwoo Lee

  • [AAAI 2025] paper accepted : “Constructing Fair Latent Space for Intersection of Fairness and Explainability”, Hyungjun Joo, Hyeonggeun Han, Sehwan Kim, Sangwoo Hong and Jungwoo Lee

  • NextQuantum IRC kicks off on Nov. 13, 2024, where CML is in charge of Quantum Machine Learning.

  • [NeurIPS 2024] paper accepted,  “Mitigating Spurious Correlations via Disagreement Probability”, Hyeonggeun Han, Sehwan Kim, Hyungjun Joo, Sangwoo Hong, and Jungwoo Lee

  • Prof. Jungwoo Lee will host a flagship information theory society conference, ISIT 2028 in Seoul as a general co-chair.

  • [AAAI 2024] paper accepted: “Domain-Aware Fine-Tuning: Enhancing Neural Network Adaptability” Seokhyun Ha and Jungwoo Lee

  • [NeurIPS 2023] paper accepted,  “SPQR: Controlling Q-ensemble Independence for Reinforcement Learning”,  Dohyeok Lee, Seungyub Han, Taehyun Cho, and Jungwoo Lee

  • [NeurIPS 2023] paper accepted,  “Pitfall of Optimism: Distributional Reinforcement Learning by Randomizing Risk Criterion”, Taehyun Cho, Seungyub Han, Heesoo Lee, Kyungjae Lee, and Jungwoo Lee

  • [UAI 2023] paper accepted,  “On the Convergence of Continual Learning with Adaptive Methods”,  Seungyub Han, Yeongmo Kim, Taehyun Cho, and Jungwoo Lee

  • [CVPR 2023] paper accepted: “Bridging the Gap between Model Explanations in Partially Annotated Multi-label Classification”, Youngwook Kim, Jae Myung Kim, Jieun Jeong, Cordelia Schmid, Zeynep Akata, and Jungwoo Lee

  • [CVPR 2022] paper accepted: “Large Loss Matters in Weakly Supervised Multi-Label Classification”,  Youngwook Kim*, Jae Myung Kim*, Zeynep Akata, and Jungwoo Lee

  • [ICML 2021] paper accepted: “Chebyshev Polynomial Codes: Task Entanglement-based Coding for Distributed Matrix Multiplication”, Sangwoo Hong, Heecheol Yang, Youngseok Yoon, Taehyun Cho, and Jungwoo Lee

  • [IEEE ISIT 2021] paper accepted: “Private and Secure Coded Computation in Straggler-Exploiting Distributed Matrix Multiplication”, Heecheol Yang, Sangwoo Hong, and Jungwoo Lee

  • [AAAI 2020] paper accepted: “REST: performance improvement of a black box model via RL based spatial transformation”, Jaemyung kim, Chanwoo Park, Hyungjin Kim and Jungwoo Lee. AAAI Conference on Artificial Intelligence, New York, USA, Feb 7-12, 2020.

Open Positions

  • [Notice] We are looking for postdocs in quantum machine learning as part of NextQuantum Innovation Research Center. Please contact Prof. Jungwoo Lee (junglee at snu.ac.kr).

  • 양자 머신러닝(Quantum Machine Learning) 연구에 관심 있는 신입생을 모집합니다.

    The CML at SNU invites applications from outstanding candidates for Postdoctoral Research Fellow positions in the areas of

    • Quantum Machine Learning

    • Distributed Computing and Federated Learning

    • AutoML and Neural Architecture Search (NAS)

    • AI Applications

    • Reinforcement Learning

Please contact Prof. Jungwoo Lee (email: junglee (at) snu.ac.kr) for more information.

To Prospective Students

If you want to join CML, please send Prof. Jungwoo Lee an email including CV. It might be impossible to respond to every application due to a large amount of email. Do not be offended.

Lectures NOTICE

  • 딥러닝 수강신청: 기초연합진공/부전공/복수전공자는 초안지 제출하면 모두 승인할 예정입니다.

  • 2022년 1학기부터 정보이론은 대학원 과목에서 동일 내용의 학부과목으로 변경되어 제공될 예정이니, 수강신청 시 참고 바랍니다.

Open Lecture Links

  • Introduction to Deep Learning: (Link)

  • Information Theory: (Link)

  • Introduction to Reinforcement Learning: (Link)

  • Information Theory and Quantum Computation

 News

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