March 3, 2023 16:48


We will hold a joint workshop with PRAIRIE as follows;

Date and Time:
March 20, 2023: 9:30 am – 16:45 pm (JST)
March 21, 2023: 9:30 am – 15:30 pm (JST)

Time Schedule

【March 20: 9:30 am – 16:45 pm (JST)】

9:30 -10:00
Speaker: Masashi Sugiyama, RIKEN AIP
Title: Introduction of RIKEN-AIP

Speaker: Jean Ponce, PRAIRIE
Title: Introduction of PRAIRIE/Beyond the computer vision comfort zone

10:45-11:15 Break Time

Speaker: Lin Gu, RIKEN AIP
Title: Addressing practical challenges from medical to general applications

Speaker: Florian Yger, PRAIRIE
Title: Representation learning with structured data

12:30-14:30 Break Time and Poster Session*

Speaker: Mihoko Otake, RIKEN AIP
Title: Cognitive Behavioral Assistive Technology

Speaker: Emmanuel Barillot, PRAIRIE
Title: Patient stratification in oncology: learning immunotherapy response

15:45-16:15 Break Time

Speaker: Ichiro Takeuchi, RIKEN AIP
Title: Statistical Test for XAI

【March 21: 9:30 am – 15:30 pm (JST)】

9:30 -10:00
Speaker: Masashi Sugiyama, RIKEN AIP
Title: Transfer learning

Speaker: Stephane Caron, PRAIRIE
Title: Robots that learn world representations, why, and which ones?

10:45-11:15 Break Time

Speaker: Taiji Suzuki, RIKEN AIP
Title: Representation power and optimization ability of neural networks
Speaker: Gabriel Peyre, PRAIRIE
Title: On the Training of Infinitely Deep and Wide ResNets

12:30-14:30 BreakTime and Poster Session*

Speaker: Qibin Zhao, RIKEN AIP
Title: Efficient machine learning with tensor networks
Speaker: Pierre-Louis Poirion, RIKEN AIP
Title: Random subspace methods for non-convex optimization

*Poster Session: Only available at the RIKEN AIP center in Nihonbashi

List of posters (for both days):

Poster presenters (in alphabetical order) Title
Jingfeng Zhang Adversarial robustness
Minh Ha Quang Information geometry and optimal transport framework for Gaussian processes
Yuwei Sun Meta-Learning in Decentralized Neural Networks Towards Systematic Generalization
Vo Nguyen Le Duy Statistical Inference for the Dynamic Time Warping Distance, with Application to Abnormal Time-Series Detection
Wei Huang Benign Overfitting for Graph Nerual Networks
Thomas Moellenhoff SAM as an Optimal Relaxation of Bayes
Andong Wang Robust learning enhanced by low-dimensional strctures
Atsushi Nitanda Primal and Dual Analysis of Mean-field Models
Ryuichiro Hataya Gradient-based hyperparameter optimization using the Nyström method
Kazusato Oko Reducing Communication in Federated Learning
Geoffrey Wolfer Mixing Time Estimation in Markov Chains
Tomohisa Okazaki Scientific Machine Learning for Geophysical Modeling
Alexandra Wolf AI for Social Good – Dementia EEG Neurobiomarker Elucidation with Network Analysis of Time Series and Subsequent Machine Learning Model Application
Peter Jack Naylor & Diego Di Carlo IMPERSONATE IMPlicit nEural RepreSentatiON chAnge deTEction

More Information

Date March 20, 2023 (Mon) - March 21, 2023(Tue) 09:30 - 15:30