Kazusato Oko - RankMe

27 papers A* 15B 1Journal 11

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Statistical Theory of Contrastive Pre-training and Multimodal Generative AI. CoRR Kazusato Oko, Licong Lin, Yuhang Cai, Song Mei
2025	A*	`conf`	Direct Distributional Optimization for Provable Alignment of Diffusion Models. ICLR Ryotaro Kawata, Kazusato Oko, Atsushi Nitanda, Taiji Suzuki
2025	J	`jnl`	Direct Distributional Optimization for Provable Alignment of Diffusion Models. CoRR Ryotaro Kawata, Kazusato Oko, Atsushi Nitanda, Taiji Suzuki
2025	A*	`conf`	Flow matching achieves almost minimax optimal convergence. ICLR Kenji Fukumizu, Taiji Suzuki, Noboru Isobe, Kazusato Oko, Masanori Koyama
2025	A*	`conf`	Nonlinear transformers can perform inference-time feature learning. ICML Naoki Nishikawa, Yujin Song, Kazusato Oko, Denny Wu, Taiji Suzuki
2025	J	`jnl`	When Does Metadata Conditioning (NOT) Work for Language Model Pre-Training? A Study with Context-Free Grammars. CoRR Rei Higuchi, Ryotaro Kawata, Naoki Nishikawa, Kazusato Oko, Shoichiro Yamaguchi, Sosuke Kobayashi, Seiya Tokui, Kohei Hayashi, Daisuke Okanohara, Taiji Suzuki
2024	J	`jnl`	Flow matching achieves minimax optimal convergence. CoRR Kenji Fukumizu, Taiji Suzuki, Noboru Isobe, Kazusato Oko, Masanori Koyama
2024	A*	`conf`	Improved statistical and computational complexity of the mean-field Langevin dynamics under structured data. ICLR Atsushi Nitanda, Kazusato Oko, Taiji Suzuki, Denny Wu
2024	A*	`conf`	Learning sum of diverse features: computational hardness and efficient gradient-based training for ridge combinations. COLT Kazusato Oko, Yujin Song, Taiji Suzuki, Denny Wu
2024	J	`jnl`	Learning sum of diverse features: computational hardness and efficient gradient-based training for ridge combinations. CoRR Kazusato Oko, Yujin Song, Taiji Suzuki, Denny Wu
2024	A*	`conf`	Mean Field Langevin Actor-Critic: Faster Convergence and Global Optimality beyond Lazy Learning. ICML Kakei Yamamoto, Kazusato Oko, Zhuoran Yang, Taiji Suzuki
2024	A*	`conf`	Neural network learns low-dimensional polynomials with SGD near the information-theoretic limit. NeurIPS Jason D. Lee, Kazusato Oko, Taiji Suzuki, Denny Wu
2024	J	`jnl`	Neural network learns low-dimensional polynomials with SGD near the information-theoretic limit. CoRR Jason D. Lee, Kazusato Oko, Taiji Suzuki, Denny Wu
2024	A*	`conf`	Pretrained Transformer Efficiently Learns Low-Dimensional Target Functions In-Context. NeurIPS Kazusato Oko, Yujin Song, Taiji Suzuki, Denny Wu
2024	J	`jnl`	Pretrained transformer efficiently learns low-dimensional target functions in-context. CoRR Kazusato Oko, Yujin Song, Taiji Suzuki, Denny Wu
2024	A*	`conf`	SILVER: Single-loop variance reduction and application to federated learning. ICML Kazusato Oko, Shunta Akiyama, Denny Wu, Tomoya Murata, Taiji Suzuki
2024	A*	`conf`	Symmetric Mean-field Langevin Dynamics for Distributional Minimax Problems. ICLR Juno Kim, Kakei Yamamoto, Kazusato Oko, Zhuoran Yang, Taiji Suzuki
2023	A*	`conf`	Diffusion Models are Minimax Optimal Distribution Estimators. ICML Kazusato Oko, Shunta Akiyama, Taiji Suzuki
2023	J	`jnl`	Diffusion Models are Minimax Optimal Distribution Estimators. CoRR Kazusato Oko, Shunta Akiyama, Taiji Suzuki
2023	A*	`conf`	Feature learning via mean-field Langevin dynamics: classifying sparse parities and beyond. NeurIPS Taiji Suzuki, Denny Wu, Kazusato Oko, Atsushi Nitanda
2023	A*	`conf`	Nearly Tight Spectral Sparsification of Directed Hypergraphs. ICALP Kazusato Oko, Shinsaku Sakaue, Shin-ichi Tanigawa
2023	A*	`conf`	Primal and Dual Analysis of Entropic Fictitious Play for Finite-sum Problems. ICML Atsushi Nitanda, Kazusato Oko, Denny Wu, Nobuhito Takenouchi, Taiji Suzuki
2023	J	`jnl`	Primal and Dual Analysis of Entropic Fictitious Play for Finite-sum Problems. CoRR Atsushi Nitanda, Kazusato Oko, Denny Wu, Nobuhito Takenouchi, Taiji Suzuki
2022	B	`conf`	MOCHA: mobile check-in application for university campuses beyond COVID-19. MobiHoc Yuuki Nishiyama, Hiroaki Murakami, Ryoto Suzuki, Kazusato Oko, Issey Sukeda, Kaoru Sezaki, Yoshihiro Kawahara
2022	J	`jnl`	Nearly Tight Spectral Sparsification of Directed Hypergraphs by a Simple Iterative Sampling Algorithm. CoRR Kazusato Oko, Shinsaku Sakaue, Shin-ichi Tanigawa
2022	A*	`conf`	Particle Stochastic Dual Coordinate Ascent: Exponential convergent algorithm for mean field neural network optimization. ICLR Kazusato Oko, Taiji Suzuki, Atsushi Nitanda, Denny Wu
2022	J	`jnl`	Versatile Single-Loop Method for Gradient Estimator: First and Second Order Optimality, and its Application to Federated Learning. CoRR Kazusato Oko, Shunta Akiyama, Tomoya Murata, Taiji Suzuki