Takeda, Akiko

25 publications

ICML 2025 Efficient Optimization with Orthogonality Constraint: A Randomized Riemannian Submanifold Method Andi Han, Pierre-Louis Poirion, Akiko Takeda
ICLR 2025 Improving Convergence Guarantees of Random Subspace Second-Order Algorithm for Nonconvex Optimization Rei Higuchi, Pierre-Louis Poirion, Akiko Takeda
ICML 2025 Modified K-Means Algorithm with Local Optimality Guarantees Mingyi Li, Michael R. Metel, Akiko Takeda
ICML 2025 On the Role of Label Noise in the Feature Learning Process Andi Han, Wei Huang, Zhanpeng Zhou, Gang Niu, Wuyang Chen, Junchi Yan, Akiko Takeda, Taiji Suzuki
AAAI 2025 Zeroth-Order Methods for Nonconvex Stochastic Problems with Decision-Dependent Distributions Yuya Hikima, Akiko Takeda
NeurIPS 2024 A Framework for Bilevel Optimization on Riemannian Manifolds Andi Han, Bamdev Mishra, Pratik Jawanpuria, Akiko Takeda
NeurIPS 2024 SLTrain: A Sparse Plus Low Rank Approach for Parameter and Memory Efficient Pretraining Andi Han, Jiaxiang Li, Wei Huang, Mingyi Hong, Akiko Takeda, Pratik Jawanpuria, Bamdev Mishra
UAI 2023 Robust Gaussian Process Regression with the Trimmed Marginal Likelihood Daniel Andrade, Akiko Takeda
NeurIPS 2022 Single Loop Gaussian Homotopy Method for Non-Convex Optimization Hidenori Iwakiri, Yuhang Wang, Shinji Ito, Akiko Takeda
NeurIPS 2021 A Gradient Method for Multilevel Optimization Ryo Sato, Mirai Tanaka, Akiko Takeda
JMLR 2021 On Lp-Hyperparameter Learning via Bilevel Nonsmooth Optimization Takayuki Okuno, Akiko Takeda, Akihiro Kawana, Motokazu Watanabe
JMLR 2021 Stochastic Proximal Methods for Non-Smooth Non-Convex Constrained Sparse Optimization Michael R. Metel, Akiko Takeda
ICML 2019 Simple Stochastic Gradient Methods for Non-Smooth Non-Convex Regularized Optimization Michael Metel, Akiko Takeda
ICML 2018 Nonconvex Optimization for Regression with Fairness Constraints Junpei Komiyama, Akiko Takeda, Junya Honda, Hajime Shimao
JMLR 2017 A Unified Formulation and Fast Accelerated Proximal Gradient Method for Classification Naoki Ito, Akiko Takeda, Kim-Chuan Toh
NeurIPS 2017 Position-Based Multiple-Play Bandit Problem with Unknown Position Bias Junpei Komiyama, Junya Honda, Akiko Takeda
NeurIPS 2017 Trimmed Density Ratio Estimation Song Liu, Akiko Takeda, Taiji Suzuki, Kenji Fukumizu
JMLR 2015 Geometric Intuition and Algorithms for Ev--SVM Álvaro Barbero, Akiko Takeda, Jorge López
AISTATS 2015 Robust Cost Sensitive Support Vector Machine Shuichi Katsumata, Akiko Takeda
AISTATS 2014 Global Optimization Methods for Extended Fisher Discriminant Analysis Satoru Iwata, Yuji Nakatsukasa, Akiko Takeda
JMLR 2013 Conjugate Relation Between Loss Functions and Uncertainty Sets in Classification Problems Takafumi Kanamori, Akiko Takeda, Taiji Suzuki
NeurIPS 2013 Global Solver and Its Efficient Approximation for Variational Bayesian Low-Rank Subspace Clustering Shinichi Nakajima, Akiko Takeda, S. Derin Babacan, Masashi Sugiyama, Ichiro Takeuchi
COLT 2012 A Conjugate Property Between Loss Functions and Uncertainty Sets in Classification Problems Takafumi Kanamori, Akiko Takeda, Taiji Suzuki
ICML 2012 A Unified Robust Classification Model Akiko Takeda, Hiroyuki Mitsugi, Takafumi Kanamori
ICML 2008 Nu-Support Vector Machine as Conditional Value-at-Risk Minimization Akiko Takeda, Masashi Sugiyama