Lectures/Talks

Lectures

2021 Spring @ UNIST: ITP117 AI Programming II

  • It covers from basic mathematics and programming to deep learning architectures such as CNN and RNN.

2021 Spring @ UNIST: EE233 Electrical Engineering Programming

  • It covers basic programming tools for electrical engineering (C++).

  • I will cover the second half of the course.

2020 Fall @ UNIST: ITP117 AI Programming II

  • It covers from basic mathematics and programming to deep learning architectures such as CNN and RNN.

  • I taught the first half of the course.

Talks

한국산업응용수학회(KISAM: Korean Society for Industrial and Applied Mathematics) "AI 대학원 스페셜 강좌(UNIST)", Dec. 2, 2021

"Review of Meta-Learning for Incremental Learning"

  • This talk is one of the special sessions of KIAM (20 min long).

  • The session held on Bexco Busan City.

한국통신학회(KICS: The Korean Institute of Communications and Information Sciences) "강화학습 기초 및 응용강좌(Reinforcement Learning: Basics and Applications", Jan. 27, 2021

"Incremental Few-Shot Learning"

  • This talk is one of the online tutorials of KICS (2 hour long).

  • Tutorial Website: [link]

  • *KICS is the largest ICT institute in Korea with over 26,000 members (KICS website [link])

AI Lectures for Ulsan Citizen @ Ulsan Institute for Talent & Lifelong Education Center, Oct. 28, 2020.

"5G와 AI가 만났을 때(5G Meets with Artificial Intelligence)"

  • This talk is for providing AI lectures for citizens in Ulsan as a collaboration between UNIST AIGS & Ulsan Institute for Talent & Lifelong Education Center.

  • Slides [link]

Workshop of Graduate School of AI @ UNIST, Sep. 18, 2020.

"Incremental Learning with A Few-Shot of Data Samples"

  • This talk is one of technical speeches in the opening workshop of AIGS in UNIST.

  • Given in Korean, video [link], slides [link]

ICML 2020 Paper Presentation @ Online Conference, Jul. 2020.

"XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning"

Poster Presentation & Won the Best Poster Award @ Samsung AI Forum 2019

  • Our ICML 2019 paper was invited to Samsung AI Forum 2019 and won the best poster award (three posters are selected among all invited AI top-venue papers).

  • Poster [link]

ICML 2019 Paper Presentation

TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning