I’m Yuki Takezawa, a 1st year Ph.D. student at Kashima Laboratory, Kyoto University.
Research interests: Machine Learning, Optimal Transport, Distributed Optimization.
contact: yuki-takezawa at ml.ist.i.kyoto-u.ac.jp
dblp / google scholar / semantic scholar
Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada
“Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence”
Neural Information Processing Systems (NeurIPS) 2023
Kazutoshi Shinoda, Yuki Takezawa, Masahiro Suzuki, Yusuke Iwasawa, Yutaka Matsuo
“Improving the Robustness to Variations of Objects and Instructions with A Neuro-Symbolic Approach for Interactive Instruction Following”
International Conference on Multimedia Modeling 2023
Yuki Takezawa, Ryoma Sato, Zornitsa Kozareva, Sujith Ravi, Makoto Yamada
“Fixed Support Tree-Sliced Wasserstein Barycenter”
International Conference on Artificial Intelligence and Statistics (AISTATS) 2022
Yuki Takezawa, Ryoma Sato, Makoto Yamada
“Supervised Tree-Wasserstein Distance”
International Conference on Machine Learning (ICML) 2021
Yuki Takezawa, Han Bao, Kenta Niwa, Ryoma Sato, Makoto Yamada
“Momentum Tracking: Momentum Acceleration for Decentralized Deep Learning on Heterogeneous Data”
Transactions on Machine Learning Research 2023
Yuki Takezawa, Kenta Niwa, Makoto Yamada
“Communication Compression for Decentralized Learning with Operator Splitting Methods”
IEEE Transactions on Signal and Information Processing over Networks 2023
Makoto Yamada, Yuki Takezawa, Ryoma Sato, Han Bao, Zornitsa Kozareva, Sujith Ravi
“Approximating 1-Wasserstein Distance with Trees”
Transactions on Machine Learning Research 2022