The Second Korea-Japan Machine Learning Workshop

February 22 (Fri) - 24 (Sun), 2019, Haevichi Hotel/Resort, Jeju, Korea

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Welcome

  • Welcome to the Second Korea-Japan Machine Learning Workshop.

The joint workshop on Machine Learning will take place in Jeju to discuss the state-of-the-art machine learning theories, algorithms, and applications, followed by the First Korea-Japan Machine Learning Symposium.

Announcements

  • Krikamol Muandet will give an informal lecture about kernel mean embedding (KME) (Friday 9pm-10pm). The lecture title is "An Introduction to Hilbert Space Embedding of Probability Measures." Please refer to his recent book about KME: Krikamol's Book. Lecture slide download
  • At the banquet seminar, Hyunjoo Jung & In-Kwon Choi (Samsung Research) and Eun-Sol Kim (Kakao Brain) will introduce their research labs.
  • Hotel information is updated. Please look at the information at the Venue tab for reservations and transportations. For any additional inquiries, please contact Yung-Kyun Noh.
  • We cannot accept more registrations due to the size of venue.

Program Overview

Day 1 (Feb. 22, Friday)
04:30pm - 05:00pm Opening (Yung-Kyun Noh) slides
Introduction (Masashi Sugiyama, Sun Kim)
Session 1
05:00pm - 05:30pm Taiji Suzuki (The University of Tokyo / RIKEN-AIP)
Title: Adaptivity of deep ReLU network and its generalization error analysis slides
05:30pm - 06:00pm Hyunjung Shin (Ajou University)
Title: Graph-based Semi-Supervised Learning for Genome, Diseasome, and Drugome
06:00pm - 06:30pm Krikamol Muandet (Max Plank Institute)
Title: Counterfactual Policy Evaluation and Optimization in Reproducing Kernel Hilbert Spaces slides
06:30pm - 07:00pm Yung-Kyun Noh (Seoul National University)
Title: Inference and Estimation using Nearest Neighbors slides
07:00pm - 09:00pm Dinner and Discussion
09:00pm - 10:00pm Informal lecture by Krikamol Muandet (for those who want to study more)
Title: An Introduction to Hilbert Space Embedding of Probability Measures Lecture slides
Day 2 (Feb. 23, Saturday)
8:00am - 10:00am Breakfast and Discussion
Session 2
10:00am - 10:30am Frank C. Park (Seoul National University)
Title: Riemannian geometry and machine learning for non-Euclidean data slides
10:30am - 11:00am Jill-Jênn Vie (RIKEN-AIP)
Title: Knowledge Tracing Machines: Factorization Machines for Educational Data Mining slides
11:00am - 11:30am Sun Kim (Seoul National University)
Title: Modeling cancer cells using multi-omics data slides
11:30am - 12:00pm Masashi Sugiyama (The University of Tokyo / RIKEN-AIP)
Title: Weakly Supervised Classification, Robust Learning and More: Overview of Our Recent Advances slides
12:00pm - 03:00pm Lunch (Lunch Box) and Posters
Session 3
03:00pm - 03:30pm Young-Han Kim (UCSD)
Title: Deep Variational Inference with Common Information Extraction
03:30pm - 04:00pm Bahareh Kalantar (RIKEN-AIP)
Title: Landslide Susceptibility mapping using machine learning algroithms slides
04:00pm - 04:30pm Koji Tsuda (The University of Tokyo / RIKEN-AIP)
Title: Designing Materials with Machine Learning and Quantum Annealing slides
04:30pm - 05:00pm Chao Li (RIKEN-AIP)
Title: Reshuffled Tensor Decomposition with Exact Recovery of Low-rank Components
05:00pm - 09:00pm Banquet Seminar:
Hyunjoo Jung & In-Kwon Choi (Samsung Research)
Eun-Sol Kim (Kakao Brain)
Day 3 (Feb. 24, Sunday)
08:00am - 10:00am Breakfast and Discussion
Session 4
10:00am - 10:30am Jaejin Lee (Seoul National University)
Title: Accelerating DNNs using Heterogeneous Clusters
10:30am - 11:00am Kazuki Yoshizoe (RIKEN-AIP)
Title: Deep Learning and Tree Search Finds New Molecules slides
11:00am - 11:30am Bohyung Han (Seoul National University)
Title: Learning for Single-Shot Confidence Calibration in Deep Neural Networks through Stochastic Inferences slides
11:30am - 12:00pm Minh Ha Quang (RIKEN-AIP)
Title: Covariance Matrices and Covariance Operators: Theory and Applications slides


Organizers: Yung-Kyun Noh (SNU), Helen Hyunjung Shin (Ajou U.), Masashi Sugiyama (RIKEN-AIP / The U. of Tokyo)