International Symposium on Recent Advances in Theories and Methodologies
for Large Complex Data
Supported by
Grant-in-Aid for Scientific Research (A) 20H00576
"Innovative developments of theories and methodologies for large complex data"
(Principal Investigator: Makoto Aoshima)
Grant-in-Aid for Challenging Research (Exploratory) 22K19769
"Developments of statistical compression technology for massive data having tensor structures"
(Principal Investigator: Makoto Aoshima)
| Date: | December 7-9, 2023 | |
|---|---|---|
| Venue: | Conference Room 101, Tsukuba International Congress Center 2-20-3 Takezono, Tsukuba, Ibaraki 305-0032, Japan (Hybrid Symposium with Zoom) |
|
| Contents & Purposes: | Please look at THIS PAGE for further details. | |
| Access: | Please see THIS PAGE. | |
| Dinner: | December 8, 7:00pm- Kisai Kagari (URL: https://kagari.owst.jp/en/) |
Program Schedule (PDF)/ Flyer (PDF)
* denotes speakers who will present in person
*(Zoom) denotes speakers who will present online via Zoom (not in person)
December 7
1:50-2:00pm Opening
| Time (UTC+9) | Title and Speaker (Affiliation) |
|---|---|
| 2:00-2:40pm | Asymptotic properties of kernel k-means for high dimensional data
[Abstract] Kento Egashira*,a, Kazuyoshi Yatab and Makoto Aoshimab a(Department of Information Sciences, Tokyo University of Science) b(Institute of Mathematics, University of Tsukuba) |
| 2:50-3:30pm | Broken-stick components retention rule for equi-correlated normal population
[Abstract] Yohji Akama (Mathematical Institute, Tohoku University) |
| 3:40-4:20pm | Forecasting high-dimensional covariance matrices using high-dimensional principal component analysis
[Abstract] Takayuki Morimoto (School of Science, Kwansei Gakuin University) |
| 4:30-5:10pm | A geometric algorithm for contrastive principal component analysis in high dimension
[Abstract] Shao-Hsuan Wang (Graduate Institute of Statistics, National Central University) |
| 5:20-6:00pm (Zoom) |
Feature learning via mean field neural networks and anisotropic features
[Abstract] Taiji Suzuki*(Zoom),a, Denny Wub, Atsushi Nitanda c and Kazusato Okoa a(Department of Mathematical Informatics, The University of Tokyo / RIKEN AIP) b(Center for Data Science, New York University) c(Department of Artificial Intelligence, Kyushu Institute of Technology / RIKEN AIP) |
December 8
| Time (UTC+9) | Title and Speaker (Affiliation) | |
|---|---|---|
| 9:00-9:40am | Statistical estimation with integral-based loss functions
[Abstract] Akifumi Okuno (The Institute of Statistical Mathematics / RIKEN AIP) |
|
| 9:50-10:30am | Non-sparse high-dimensional statistics and its applications
[Abstract] Masaaki Imaizumi (Komaba Institute for Science, The University of Tokyo / RIKEN AIP) |
|
| 10:40-11:20am | Statistical challenges to dimensionality in astronomical big data
[Abstract] Tsutomu T. Takeuchi (Division of Particle and Astrophysical Science, Nagoya University) |
|
| 11:30am-12:10pm | Predictive density estimation for two ordered normal means under α-divergence loss
[Abstract] Yuan-Tsung Chang*,a, Nobuo Shinozakib and William, E. Strawdermanc a(Department of Social Information, Mejiro University) b(Faculty of Science and Technology, Keio University) c(Department of Statistics, Rutgers University) |
|
| 12:10-1:40pm | Lunch | |
| Special Invited Session | ||
| 1:40-2:30pm | On the efficiency-loss free ordering-robustness of product-PCA
[Abstract]
Speaker: Hung Hung (Institute of Health Data Analytics and Statistics, National Taiwan University) Discussion Leader: Yuan-Tsung Chang (Department of Social Information, Mejiro University) |
|
| 2:40-3:30pm | Learning ordinality in high-dimensional data
[Abstract]
Speaker: Jeongyoun Ahn (Department of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology) Discussion Leader: Kazuyoshi Yata (Institute of Mathematics, University of Tsukuba) |
|
| Keynote Session | ||
| 3:50-4:50pm | Normal-reference test for high-dimensional covariance matrices
[Abstract]
Speaker: Jin-Ting Zhang (Department of Statistics and Data Science, National University of Singapore) Discussion Leader: Aki Ishii (Department of Information Sciences, Tokyo University of Science) |
|
| 5:00-6:00pm (Zoom) |
Testing high-dimensional general linear hypotheses through spectral shrinkage
[Abstract]
Speaker: Debashis Paul (Department of Statistics, University of California, Davis / Indian Statistical Institute, Kolkata) Discussion Leader: Yuta Koike (Graduate School of Mathematical Sciences, The University of Tokyo) |
|
| 7:00-9:00pm | Dinner | |
December 9
| Time (UTC+9) | Title and Speaker (Affiliation) |
|---|---|
| 9:00-9:40am | On approximate sampling from non-log-concave non-smooth distributions via a Langevin-type Monte Carlo algorithm
[Abstract] Shogo Nakakita (Komaba Institute for Science, The University of Tokyo) |
| 9:50-10:30am | Two step estimations via the Dantzig selector for ergodic time series models Kou Fujimori*,a and Koji Tsukudab a(Department of Economics, Shinshu University) b(Faculty of Mathematics, Kyushu University) |
| 10:40-11:20am | Innovation algorithm of fractionally integrated (I(d)) process and applications on the estimation of parameters Junichi Hirukawa*,a and Kou Fujimorib a(Faculty of Science, Niigata University) b(Department of Economics, Shinshu University) |
| 11:30am-12:10pm | Scaling limits of Markov chains/processes in Monte Carlo methods
[Abstract] Kengo Kamatani (The Institute of Statistical Mathematics) |
| 12:20-1:00pm | On a general linear hypothesis testing problem for latent factor models in high dimensions
[Abstract] Takahiro Nishiyama*,a and Masashi Hyodob a(Department of Business Administration, Senshu University) b(Department of Economics, Kanagawa University) |
1:00-1:10pm Closing