Workshop Program - June 25

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Time

Speaker (Affil.)

Title/Information

Chair

14:30 ~ 14:35

 Qibin Zhao
(RIKEN AIP)		 Opening Remarks

Keynote Talk (Presentation + 3 mins Q&A)

14:35 ~ 14:55

 Michael Ng
(HKBU)		 Tensor Representation in Data Science Qibin Zhao

14:55 ~ 15:15

 Liqing Zhang
(SJTU)		 Tensor Submanifold Embedding for Deep Learning and Applications Guoxu Zhou

15:15 ~ 15:30

 Y-H. Taguchi
(Chuo University)		 Signal detection from dirty world: signal detection from large dimension, small size, and data using tensor decomposition Tatsuya Yokota

15:30 ~ 15:45

 Jicong Fan
(CUHK-SZ)		 Schatten-p Quasi-Norm Regularization for Tensor Completion and Tensor Robust PCA Yuning Qiu

15:45 ~ 16:00

 Kazu Ghalamkari
(RIKEN AIP)		 Tensor Factorization via Multi-Body Modeling on Statistical Manifold Andong Wang

16:00 ~ 16:30

 Coffee Break and Poster Session Andong Wang

16:30 ~ 16:45

 Qibin Zhao
(RIKEN AIP)		 Efficient and Robust Machine Learning with Tensor Networks Yuning Qiu

Spotlight Talk Andong Wang

16:45 ~ 16:50

 Jianfu Zhang
(SJTU)		 The Emergence and Challenges of Diffusion Models in Visual Content Generation

16:50 ~ 16:55

 Deqing Wang
(CAS)		 Doubly Accelerated Proximal Gradient for Nonnegative Tensor Decomposition

16:55 ~ 17:00

 Hong Lai
(SWU)		 Dynamic hierarchical quantum secret sharing based on the multiscale entanglement renormalization ansatz

17:00 ~ 17:05

 Naoya Yamauchi
(NITech)		 EM algorithm for tensor network logistic regression based on Polya-Gamma augmentation

17:05 ~ 17:10

 Chao Li
(RIKEN AIP)		 Discovering More Effective Tensor Network Structure Search Algorithms via Large Language Models (LLMs)

17:10 ~ 17:15

 Zhiqi Shao
(USYD)		 ST-SSMs: Spatial-Temporal Selective State of Space Model for Enhanced Traffic Forecasting

17:15 ~ 17:20

 Hang Liu
(DUT)		 Reproducibility Analysis for Coupled Tensor Decompositions Based on Federated Learning Results

17:20 ~ 17:55

 Poster Session Yuning Qiu

17:55 ~ 18:00

 Guoxu Zhou
(GDUT)		 Closing Remarks

Registration

To participate in this workshop, attendees of all kinds must register for IEEE CAI 2024 through the following URL: https://ieeecai.org/2024/registration/.


In accordance with the guidance provided by the IEEE CAI organizers, you should register as a "workshop author/speaker/invited guest". During the registration process, please select "Tensor Models for Machine Learning - Empowering Efficiency, Interpretability" when prompted for Workshop Selection to Present.