Abstract
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
10:00-10:45
Speaker: Jean Ponce, PRAIRIE
Title: Introduction of PRAIRIE/Beyond the computer vision comfort zone
10:45-11:15 Break Time
11:15-11:45
Speaker: Lin Gu, RIKEN AIP
Title: Addressing practical challenges from medical to general applications
11:45-12:30
Speaker: Florian Yger, PRAIRIE
Title: Representation learning with structured data
12:30-14:30 Break Time and Poster Session*
14:30-15:00
Speaker: Mihoko Otake, RIKEN AIP
Title: Cognitive Behavioral Assistive Technology
15:00-15:45
Speaker: Emmanuel Barillot, PRAIRIE
Title: Patient stratification in oncology: learning immunotherapy response
15:45-16:15 Break Time
16:15-16:45
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
10:00-10:45
Speaker: Stephane Caron, PRAIRIE
Title: Robots that learn world representations, why, and which ones?
10:45-11:15 Break Time
11:15-11:45
Speaker: Taiji Suzuki, RIKEN AIP
Title: Representation power and optimization ability of neural networks
11:45-12:30
Speaker: Gabriel Peyre, PRAIRIE
Title: On the Training of Infinitely Deep and Wide ResNets
12:30-14:30 BreakTime and Poster Session*
14:30-15:00
Speaker: Qibin Zhao, RIKEN AIP
Title: Efficient machine learning with tensor networks
15:00-15:30
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 |
| URL | https://c5dc59ed978213830355fc8978.doorkeeper.jp/events/152447 |
