Programme

Monday, 16 March

10:30 - 10:40 Opening

Chair: Nihat Ay

10:40 - 11:40 (invited talk) Information Geometry and Wasserstein Distance

Shun-ichi Amari, RIKEN Center for Brain Science

11:40 - 13:10 Lunch

Chair: Asuka Takatsu

13:10 - 14:10 (invited talk) Logarithmic divergences: from finance to optimal transport and information geometry

Ting-Kam Leonard Wong, University of Toronto

14:20 - 15:20 (invited talk) On the Natural Gradient for Deep Learning

Nihat Ay, Max Plank Institute for Mathematics in the Sciences

Chair: Ting-Kam Leonard Wong

15:50 - 16:50 (invited talk) On the Berezin-Wallach-Gindikin-Jorgensen set

Hideyuki Ishi, Osaka City University

17:00 - 18:00 (invited talk) T.B.A.

Hiroshi Nagaoka, The University of Electro-Communications

Tuesday, 17 March

Chair: Takashi Takenouchi

10:00 - 11:00 (invited talk) Learning with Dually Flat Structure and Incidence Algebra

Mahito Sugiyama, National Institute of Informatics

11:05 - 11:20 (short talk) Selection bias may be adjusted when sample size is negative

Hidetoshi Shimodaira, Kyoto University

11:20 - 11:35 (short talk) Riemannian Geometry Machine Learning Methods for EEG and fNIRS Digital Biomarker Development in AI for Aging Societies Application

Tomasz Rutkowski, RIKEN AIP

11:40 - 13:10 Lunch

Chair: Takafumi Kanamori

13:10 - 14:10 (invited talk) From geometric learning machines to the geometry of learning

Frank Nielsen, Sony Computer Science Laboratories Inc.

14:20 - 15:20 (invited talk) Multilabel retrieval: a loss function perspective

Aditya Menon, Google Research

15:50 - 16:50 (invited talk) T.B.D.

Sebastian Nowozin, Google Research

17:00 - 18:00 (invited talk) Information Geometry and Optimal Transport in Reproducing Kernel Hilbert Spaces

Minh Ha Quang, RIKEN AIP

18:10 - Bauquet (Registration has been closed)

Wednesday, 18 March

Chair: Jun Zhang

10:00 - 11:00 (invited talk) Information geometry of reinforcement learning

Shinto Eguchi, The Institute of Statistical Mathematics

11:05 - 11:20 (short talk) MDL Estimators Using Fiber Bundles of Local Exponential Families

Junichi Takeuchi, Kyushu University

11:20 - 11:35 (short talk) Non-informative prior on the Kähler information statistical manifold of complex-valued Gaussian process

Hidemasa Oda, The University of Tokyo

11:40 - 13:10 Lunch

Chair: Kei Kobayashi

13:10 - 13:25 (short talk) A Generalization Bound for Online Variational Inference

Pierre Alquier, RIKEN AIP

13:25- 13:40 (short talk) Deformed q-ELBO for Robust Variational Inference

Deepika Kumari, Romanian Institute of Science and Technology

13:40 - 13:55 (short talk) On the gradient-flow equations in information geometry

Tatsuaki Wada, Ibaraki University

13:55 - 14:10 (short talk) On the Natural Gradient for the Training of Neural Networks

Luigi Malagò, Romanian Institute of Science and Technology

Chair: Shinto Eguchi

14:20 - 15:20 (invited talk) Information geometry of multivariate Poisson distributions and its applications

Fumiyasu Komaki, The University of Tokyo

Chair: Kei Kobayashi

15:50 - 16:50 (invited talk) Bayesian Learning Rule: Combining information geometry, optimization, and statistics to improve deep learning

Mohammad Emtiyaz Khan, RIKEN AIP

Chair: Fumiyasu Komaki

17:00 - 18:00 (invited talk) Statistical Mirror Symmetry

Jun Zhang, University of Michigan

Thursday, 19 March

Chair: Milan Mosonyi

10:00 - 10:30 (tutorial) Introduction to Quantum Information

Fuyuhiko Tanaka, Osaka University

10:40 - 11:40 (invited talk) Recent progress in asymptotic quantum statistics

Akio Fujiwara, Osaka University

11:40 - 13:10 Lunch

Chair: Fuyuhiko Tanaka

13:10 - 13:25 (short talk) Natural Alpha Embeddings and their Impact on Downstream Tasks

Riccardo Volpi, Romanian Institute of Science and Technology

13:25 - 13:40 (short talk) Bregman-Lagrangian Dynamics on the Non-parametric Statistical Bundle

Goffredo Chirco, Romanian Institute of Science and Technology

13:40 - 13:55 (short talk) Towards a canonical divergence within Information Geometry

Domenico Felice, MPI MiS - Leipzig

13:55 - 14:10 (short talk) A method to construct exponential families by representation theory

Koichi Tojo, RIKEN AIP

Chair: Akio Fujiwara

14:20 - 15:20 (invited talk) Rényi divergence radii in quantum information theory

Milan Mosonyi, Budapest University of Technology and Economics

Chair: Takeru Matsuda

15:50 - 16:50 (invited talk) Qubit channel parameter estimation with noisy initial states

David Collins, Colorado Mesa University

Chair: David Collins

17:00 - 18:00 (invited talk) Minimax estimation of quantum states based on the conditional Holevo mutual information

Takeru Matsuda, The University of Tokyo

Friday, 20 March

Chair: TBA

10:00 - 11:00 (invited talk) Geometry of Regularized Wasserstein Distances

Marco Cuturi, Google

11:10 - 12:10 (invited talk) Invariant metric under deformed Markov embeddings with overlapped supports

Asuka Takatsu, Tokyo Metropolitan University

12:10 - 12:20 Closing

Poster Presentation (Monday - Friday)

1. Multi-scale k-nearest neighbour

Akifumi Okuno, RIKEN AIP

2. Natural Wake-Sleep Algorithm for Helmholtz Machines

Csongor-Huba Varady, Romanian Institute of Science and Technology, MPI MiS

3. Correlated Uncertainties for Regression Problems using Bayesian Neural Networks and Generalized Divergences

Hector Hortua, Romanian Institute of Science and Technology

4. Information Geometric Regularizers for Variational AutoEncoders to Improve Robustness Against Adversarial Examples

Petru Hlihor, Romanian Institute of Science and Technology and MPI MiS

5. Projection of Bayesian predictive densities onto finite-dimensional exponential families

Michiko Okudo, The University of Tokyo

6. Information geometry of operator scaling

Tasuku Soma, The University of Tokyo