Information and Learning Theory Lab.17
Overview
ILT Lab. (Information and Learning Theory Lab.) led by Daewon Seo at DGIST explores a broad area of machine learning and data science from a theoretic perspective. In particular, we investigate the learning process in social networks and deep neural networks from a lens of statistical inference, information theory, and learning theory.
Advisor Professor : Seo, Daewon
Information and Learning Theory Lab. Homepage
ILT Lab. (Information and Learning Theory Lab.) led by Daewon Seo at DGIST explores a broad area of machine learning and data science from a theoretic perspective. In particular, we investigate the learning process in social networks and deep neural networks from a lens of statistical inference, information theory, and learning theory.
Advisor Professor : Seo, Daewon
Information and Learning Theory Lab. Homepage
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Co-Author(s)
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Recent Submissions
- Feature Importance-Aware Deep Joint Source-Channel Coding for Computationally Efficient and Adjustable Image Transmission
- Activity recognition and user identification using mmWave radar with a shared-backbone graph network and task-specific heads
- On the Fundamental Tradeoff of Joint Communication and QCD: The Monostatic Case
- Region-of-Interest-Guided Deep Joint Source-Channel Coding for Image Transmission
- 특징 중요도 인식 기반 이미지 전송을 위한 심층-통합 소스 채널 코딩 시스템 및 방법