Tomoya Murata - RankMe

27 papers A* 8A 2Journal 15Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Adaptive Clipping for Differential Private Federated Learning in Interpolation Regimes. Trans. Mach. Learn. Res. Takumi Fukami, Tomoya Murata, Kenta Niwa
2025	A	`conf`	Clustered Invariant Risk Minimization. AISTATS Tomoya Murata, Atsushi Nitanda, Taiji Suzuki
2025	—	`conf`	Development of an Automated Animation Image Coloring System Based on Inclusion Matching. IIAI-AAI-Winter Tomoya Murata, Naoki Mori
2024	J	`jnl`	A Localized Primal-Dual Method for Centralized/Decentralized Federated Learning Robust to Data Heterogeneity. IEEE Trans. Signal Inf. Process. over Networks Iifan Tyou, Tomoya Murata, Takumi Fukami, Yuki Takezawa, Kenta Niwa
2024	J	`jnl`	DP-Norm: Differential Privacy Primal-Dual Algorithm for Decentralized Federated Learning. IEEE Trans. Inf. Forensics Secur. Takumi Fukami, Tomoya Murata, Kenta Niwa, Iifan Tyou
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`	Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity. ICLR Tomoya Murata, Kenta Niwa, Takumi Fukami, Iifan Tyou
2023	A*	`conf`	DIFF2: Differential Private Optimization via Gradient Differences for Nonconvex Distributed Learning. ICML Tomoya Murata, Taiji Suzuki
2023	J	`jnl`	DIFF2: Differential Private Optimization via Gradient Differences for Nonconvex Distributed Learning. CoRR Tomoya Murata, Taiji Suzuki
2022	A*	`conf`	Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning. NeurIPS Tomoya Murata, Taiji Suzuki
2022	J	`jnl`	Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning. CoRR Tomoya Murata, Taiji Suzuki
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
2021	A*	`conf`	Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning. ICML Tomoya Murata, Taiji Suzuki
2021	J	`jnl`	Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning. CoRR Tomoya Murata, Taiji Suzuki
2021	A	`conf`	Gradient Descent in RKHS with Importance Labeling. AISTATS Tomoya Murata, Taiji Suzuki
2021	J	`jnl`	Sharp characterization of optimal minibatch size for stochastic finite sum convex optimization. Knowl. Inf. Syst. Atsushi Nitanda, Tomoya Murata, Taiji Suzuki
2020	J	`jnl`	Gradient Descent in RKHS with Importance Labeling. CoRR Tomoya Murata, Taiji Suzuki
2020	A*	`conf`	Spectral Pruning: Compressing Deep Neural Networks via Spectral Analysis and its Generalization Error. IJCAI Taiji Suzuki, Hiroshi Abe, Tomoya Murata, Shingo Horiuchi, Kotaro Ito, Tokuma Wachi, So Hirai, Masatoshi Yukishima, Tomoaki Nishimura
2019	J	`jnl`	Accelerated Sparsified SGD with Error Feedback. CoRR Tomoya Murata, Taiji Suzuki
2019	A*	`conf`	Sharp Characterization of Optimal Minibatch Size for Stochastic Finite Sum Convex Optimization. ICDM Atsushi Nitanda, Tomoya Murata, Taiji Suzuki
2018	A*	`conf`	Sample Efficient Stochastic Gradient Iterative Hard Thresholding Method for Stochastic Sparse Linear Regression with Limited Attribute Observation. NeurIPS Tomoya Murata, Taiji Suzuki
2018	J	`jnl`	Sample Efficient Stochastic Gradient Iterative Hard Thresholding Method for Stochastic Sparse Linear Regression with Limited Attribute Observation. CoRR Tomoya Murata, Taiji Suzuki
2018	J	`jnl`	Spectral-Pruning: Compressing deep neural network via spectral analysis. CoRR Taiji Suzuki, Hiroshi Abe, Tomoya Murata, Shingo Horiuchi, Kotaro Ito, Tokuma Wachi, So Hirai, Masatoshi Yukishima, Tomoaki Nishimura
2017	—	`conf`	Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization. NIPS Tomoya Murata, Taiji Suzuki
2017	J	`jnl`	Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization. CoRR Tomoya Murata, Taiji Suzuki
2016	J	`jnl`	Stochastic dual averaging methods using variance reduction techniques for regularized empirical risk minimization problems. CoRR Tomoya Murata, Taiji Suzuki
2014	J	`jnl`	Hand Gesture and Character Recognition Based on Kinect Sensor. Int. J. Distributed Sens. Networks Tomoya Murata, Jungpil Shin