Get started
Author

Tomoya Murata

Observed name: Murata, Tomoya
ORCID: 0000-0001-8917-3714
Observed ORCID: 0000-0001-8917-3714
OpenAlex ID: A5065727065
Spectral Pruning: Compressing Deep Neural Networks via Spectral Analysis and its Generalization Error
2020 · Taiji Suzuki, Hiroshi Abe, et al. · International Joint Conference on Artificial Intelligence · 38
PDF
Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning
2021 · Murata, Tomoya, Suzuki, Taiji · arXiv (Cornell University) · 36
PDF
DP-Norm: Differential Privacy Primal-Dual Algorithm for Decentralized Federated Learning
2024 · Takumi Fukami, Tomoya Murata, et al. · IEEE Transactions on Information Forensics and Security · 29
PDF
Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization
2017 · Murata, Tomoya, Suzuki, Taiji · arXiv (Cornell University) · 23
PDF
Spectral-Pruning: Compressing deep neural network via spectral analysis
2018 · Taiji Suzuki, Hiroshi Abe, et al. · arXiv (Cornell University) · 12
A Localized Primal-Dual Method for Centralized/Decentralized Federated Learning Robust to Data Heterogeneity
2023 · Iifan Tyou, Tomoya Murata, et al. · IEEE Transactions on Signal and Information Processing over Networks · 5
PDF
DIFF2: Differential Private Optimization via Gradient Differences for Nonconvex Distributed Learning
2023 · Murata, Tomoya, Suzuki, Taiji · arXiv (Cornell University) · 3
PDF
Gradient Descent in RKHS with Importance Labeling
2020 · Murata, Tomoya, Suzuki, Taiji · arXiv (Cornell University) · 3
PDF
Sharp Characterization of Optimal Minibatch Size for Stochastic Finite Sum Convex Optimization
2019 · Atsushi Nitanda, Tomoya Murata, et al. · Proceedings · 3
Accelerated Sparsified SGD with Error Feedback
2019 · Murata, Tomoya, Suzuki, Taiji · arXiv (Cornell University) · 3
PDF
Sample Efficient Stochastic Gradient Iterative Hard Thresholding Method for Stochastic Sparse Linear Regression with Limited Attribute Observation
2018 · Murata, Tomoya, Suzuki, Taiji · arXiv (Cornell University) · 3
PDF
Stochastic dual averaging methods using variance reduction techniques for regularized empirical risk minimization problems
2016 · Murata, Tomoya, Suzuki, Taiji · arXiv (Cornell University) · 3
PDF
Versatile Single-Loop Method for Gradient Estimator: First and Second Order Optimality, and its Application to Federated Learning
2022 · Oko, Kazusato, Akiyama, Shunta, et al. · arXiv (Cornell University) · 1
PDF
Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning
2022 · Tomoya Murata, Taiji Suzuki · neural information processing systems · 1
PDF
Sharp characterization of optimal minibatch size for stochastic finite sum convex optimization
2021 · Atsushi Nitanda, Tomoya Murata, et al. · Knowledge and Information Systems
Doubly Accelerated Stochastic Variance Reduced Gradient Method for Regularized Empirical Risk Minimization
2017 · Tomoya Murata, Taiji Suzuki · IEICE Technical Report; IEICE Tech. Rep.
Works count: 16
Citation count: 163
H-index: 5
I10-index: 5
Year
Topic
Type