Approximate bregman proximal gradient algorithm for relatively smooth nonconvex optimization - Shota Takahashi; Akiko Takeda (Comput. Optim. Appl., 2025)

Stochastic approach for price optimization problems with decision-dependent uncertainty - Yuya Hikima; Akiko Takeda (Eur. J. Oper. Res., 2025)

Zeroth-Order Random Subspace Algorithm for Non-smooth Convex Optimization - Ryota Nozawa; Pierre-Louis Poirion; Akiko Takeda (J. Optim. Theory Appl., 2025)

Univariate Representations of Solutions to Generic Polynomial Complementarity Problems - Vu Trung Hieu; Alfredo Noel Iusem; Paul Hugo Schmölling; Akiko Takeda (J. Optim. Theory Appl., 2025)

Universal heavy-ball method for nonconvex optimization under Hölder continuous Hessians - Naoki Marumo; Akiko Takeda (Math. Program., 2025)

Unified smoothing approach for best hyperparameter selection problem using a bilevel optimization strategy - Jan Harold Alcantara; Chieu Thanh Nguyen; Takayuki Okuno; Akiko Takeda; Jein-Shan Chen (Math. Program., 2025)

Zeroth-Order Methods for Nonconvex Stochastic Problems with Decision-Dependent Distributions - Yuya Hikima; Akiko Takeda (AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25 - March 4, 2025, Philadelphia, PA, USA, 2025)

Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization - Rei Higuchi; Pierre-Louis Poirion; Akiko Takeda (The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025, 2025)

The Adaptive Complexity of Finding a Stationary Point - Huanjian Zhou; Andi Han; Akiko Takeda; Masashi Sugiyama (CoRR, 2025)

Efficient Optimization with Orthogonality Constraint: a Randomized Riemannian Submanifold Method - Andi Han; Pierre-Louis Poirion; Akiko Takeda (CoRR, 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 (CoRR, 2025)

Modified K-means Algorithm with Local Optimality Guarantees - Mingyi Li; Michael R. Metel; Akiko Takeda (CoRR, 2025)

Parameter-Free Accelerated Gradient Descent for Nonconvex Minimization - Naoki Marumo; Akiko Takeda (SIAM J. Optim., 2024)

Stable Linear System Identification With Prior Knowledge by Riemannian Sequential Quadratic Optimization - Mitsuaki Obara; Kazuhiro Sato; Hiroki Sakamoto; Takayuki Okuno; Akiko Takeda (IEEE Trans. Autom. Control., 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 Kumar Jawanpuria; Bamdev Mishra (Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024, 2024)

A Framework for Bilevel Optimization on Riemannian Manifolds - Andi Han; Bamdev Mishra; Pratik Kumar Jawanpuria; Akiko Takeda (Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024, 2024)

A Framework for Bilevel Optimization on Riemannian Manifolds - Andi Han; Bamdev Mishra; Pratik Jawanpuria; Akiko Takeda (CoRR, 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 (CoRR, 2024)

Initial Placement for Fruchterman-Reingold Force Model with Coordinate Newton Direction - Hiroki Hamaguchi; Naoki Marumo; Akiko Takeda (CoRR, 2024)

Zeroth-Order Methods for Nonconvex Stochastic Problems with Decision-Dependent Distributions - Yuya Hikima; Akiko Takeda (CoRR, 2024)

Majorization-minimization-based Levenberg-Marquardt method for constrained nonlinear least squares - Naoki Marumo; Takayuki Okuno; Akiko Takeda (Comput. Optim. Appl., 2023)

Doubly majorized algorithm for sparsity-inducing optimization problems with regularizer-compatible constraints - Tianxiang Liu; Ting Kei Pong; Akiko Takeda (Comput. Optim. Appl., 2023)

Complexity analysis of interior-point methods for second-order stationary points of nonlinear semidefinite optimization problems - Shun Arahata; Takayuki Okuno; Akiko Takeda (Comput. Optim. Appl., 2023)

A study on modularity density maximization: Column generation acceleration and computational complexity analysis - Issey Sukeda; Atsushi Miyauchi; Akiko Takeda (Eur. J. Oper. Res., 2023)

Robust Gaussian process regression with the trimmed marginal likelihood - Daniel Andrade; Akiko Takeda (Uncertainty in Artificial Intelligence, UAI 2023, July 31 - 4 August 2023, Pittsburgh, PA, USA, 2023)

An inexact successive quadratic approximation method for a class of difference-of-convex optimization problems - Tianxiang Liu; Akiko Takeda (Comput. Optim. Appl., 2022)

Perturbed Iterate SGD for Lipschitz Continuous Loss Functions - Michael R. Metel; Akiko Takeda (J. Optim. Theory Appl., 2022)

Sequential Quadratic Optimization for Nonlinear Optimization Problems on Riemannian Manifolds - Mitsuaki Obara; Takayuki Okuno; Akiko Takeda (SIAM J. Optim., 2022)

Convexification with Bounded Gap for Randomly Projected Quadratic Optimization - Terunari Fuji; Pierre-Louis Poirion; Akiko Takeda (SIAM J. Optim., 2022)

Single Loop Gaussian Homotopy Method for Non-convex Optimization - Hidenori Iwakiri; Yuhang Wang; Shinji Ito; Akiko Takeda (Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022)

A Study on Modularity Density Maximization: Column Generation Acceleration and Computational Complexity Analysis - Issey Sukeda; Atsushi Miyauchi; Akiko Takeda (CoRR, 2022)

Stochastic Proximal Methods for Non-Smooth Non-Convex Constrained Sparse Optimization - Michael R. Metel; Akiko Takeda (J. Mach. Learn. Res., 2021)

On lp-hyperparameter Learning via Bilevel Nonsmooth Optimization - Takayuki Okuno; Akiko Takeda; Akihiro Kawana; Motokazu Watanabe (J. Mach. Learn. Res., 2021)

Primal-dual subgradient method for constrained convex optimization problems - Michael R. Metel; Akiko Takeda (Optim. Lett., 2021)

A Projected Gradient Method for Opinion Optimization with Limited Changes of Susceptibility to Persuasion - Naoki Marumo; Atsushi Miyauchi; Akiko Takeda; Akira Tanaka (CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1 - 5, 2021, 2021)

A Gradient Method for Multilevel Optimization - Ryo Sato; Mirai Tanaka; Akiko Takeda (Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 2021)

BODAME: Bilevel Optimization for Defense Against Model Extraction - Yuto Mori; Atsushi Nitanda; Akiko Takeda (CoRR, 2021)

A Gradient Method for Multilevel Optimization - Ryo Sato; Mirai Tanaka; Akiko Takeda (CoRR, 2021)

A Projected Gradient Method for Opinion Optimization with Limited Changes of Susceptibility to Persuasion - Naoki Marumo; Atsushi Miyauchi; Akiko Takeda; Akira Tanaka (CoRR, 2021)

Construction Methods of the Nearest Positive System - Kazuhiro Sato; Akiko Takeda (IEEE Control. Syst. Lett., 2020)

Controllability Maximization of Large-Scale Systems Using Projected Gradient Method - Kazuhiro Sato; Akiko Takeda (IEEE Control. Syst. Lett., 2020)

Theory and Algorithms for Shapelet-Based Multiple-Instance Learning - Daiki Suehiro; Kohei Hatano; Eiji Takimoto; Shuji Yamamoto; Kenichi Bannai; Akiko Takeda (Neural Comput., 2020)

Estimation of Gaussian mixture models via tensor moments with application to online learning - Donya Rahmani; Mahesan Niranjan; Damien Fay; Akiko Takeda; Jacek Brodzki (Pattern Recognit. Lett., 2020)

Robust Bayesian model selection for variable clustering with the Gaussian graphical model - Daniel Andrade; Akiko Takeda; Kenji Fukumizu (Stat. Comput., 2020)

Generalized Subdifferentials of Spectral Functions over Euclidean Jordan Algebras - Bruno F. Lourenço; Akiko Takeda (SIAM J. Optim., 2020)

A Hybrid Penalty Method for a Class of Optimization Problems with Multiple Rank Constraints - Tianxiang Liu; Ivan Markovsky; Ting Kei Pong; Akiko Takeda (SIAM J. Matrix Anal. Appl., 2020)

Data-Driven Structured Noise Filtering via Common Dynamics Estimation - Ivan Markovsky; Tianxiang Liu; Akiko Takeda (IEEE Trans. Signal Process., 2020)

Convex Fairness Constrained Model Using Causal Effect Estimators - Hikaru Ogura; Akiko Takeda (Companion of The 2020 Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020)

Convex Fairness Constrained Model Using Causal Effect Estimators - Hikaru Ogura; Akiko Takeda (CoRR, 2020)

Theory and Algorithms for Shapelet-based Multiple-Instance Learning - Daiki Suehiro; Kohei Hatano; Eiji Takimoto; Shuji Yamamoto; Kenichi Bannai; Akiko Takeda (CoRR, 2020)

A refined convergence analysis of \(\hbox {pDCA}_{e}\) with applications to simultaneous sparse recovery and outlier detection - Tianxiang Liu; Ting Kei Pong; Akiko Takeda (Comput. Optim. Appl., 2019)

A successive difference-of-convex approximation method for a class of nonconvex nonsmooth optimization problems - Tianxiang Liu; Ting Kei Pong; Akiko Takeda (Math. Program., 2019)

Algorithm 996: BBCPOP: A Sparse Doubly Nonnegative Relaxation of Polynomial Optimization Problems With Binary, Box, and Complementarity Constraints - Naoki Ito; Sunyoung Kim; Masakazu Kojima; Akiko Takeda; Kim-Chuan Toh (ACM Trans. Math. Softw., 2019)

Subspace methods for multi-channel sum-of-exponentials common dynamics estimation - Ivan Markovsky; Tianxiang Liu; Akiko Takeda (58th IEEE Conference on Decision and Control, CDC 2019, Nice, France, December 11-13, 2019, 2019)

Simple Stochastic Gradient Methods for Non-Smooth Non-Convex Regularized Optimization - Michael R. Metel; Akiko Takeda (Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA, 2019)

Improving cash logistics in bank branches by coupling machine learning and robust optimization - Jorge López Lázaro; Álvaro Barbero Jiménez; Akiko Takeda (Expert Syst. Appl., 2018)

Successive Lagrangian relaxation algorithm for nonconvex quadratic optimization - Shinji Yamada; Akiko Takeda (J. Glob. Optim., 2018)

Equivalences and differences in conic relaxations of combinatorial quadratic optimization problems - Naoki Ito; Sunyoung Kim; Masakazu Kojima; Akiko Takeda; Kim-Chuan Toh (J. Glob. Optim., 2018)

DC formulations and algorithms for sparse optimization problems - Jun-ya Gotoh; Akiko Takeda; Katsuya Tono (Math. Program., 2018)

Robust Densest Subgraph Discovery - Atsushi Miyauchi; Akiko Takeda (IEEE International Conference on Data Mining, ICDM 2018, Singapore, November 17-20, 2018, 2018)

Nonconvex Optimization for Regression with Fairness Constraints - Junpei Komiyama; Akiko Takeda; Junya Honda; Hajime Shimao (Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsmässan, Stockholm, Sweden, July 10-15, 2018, 2018)

Robust Densest Subgraph Discovery - Atsushi Miyauchi; Akiko Takeda (CoRR, 2018)

Multiple-Instance Learning by Boosting Infinitely Many Shapelet-based Classifiers - Daiki Suehiro; Kohei Hatano; Eiji Takimoto; Shuji Yamamoto; Kenichi Bannai; Akiko Takeda (CoRR, 2018)

Breakdown Point of Robust Support Vector Machines - Takafumi Kanamori; Shuhei Fujiwara; Akiko Takeda (Entropy, 2017)

A Unified Formulation and Fast Accelerated Proximal Gradient Method for Classification - Naoki Ito; Akiko Takeda; Kim-Chuan Toh (J. Mach. Learn. Res., 2017)

DC Algorithm for Extended Robust Support Vector Machine - Shuhei Fujiwara; Akiko Takeda; Takafumi Kanamori (Neural Comput., 2017)

Robustness of learning algorithms using hinge loss with outlier indicators - Takafumi Kanamori; Shuhei Fujiwara; Akiko Takeda (Neural Networks, 2017)

Solving the Trust-Region Subproblem By a Generalized Eigenvalue Problem - Satoru Adachi; Satoru Iwata; Yuji Nakatsukasa; Akiko Takeda (SIAM J. Optim., 2017)

Exact Semidefinite Programming Relaxations with Truncated Moment Matrix for Binary Polynomial Optimization Problems - Shinsaku Sakaue; Akiko Takeda; Sunyoung Kim; Naoki Ito (SIAM J. Optim., 2017)

Trimmed Density Ratio Estimation - Song Liu; Akiko Takeda; Taiji Suzuki; Kenji Fukumizu (Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, 2017)

Position-based Multiple-play Bandit Problem with Unknown Position Bias - Junpei Komiyama; Junya Honda; Akiko Takeda (Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, 2017)

Household energy consumption prediction by feature selection of lifestyle data - Kosuke Nishida; Akiko Takeda; Satoru Iwata; Mariko Kiho; Isao Nakayama (2017 IEEE International Conference on Smart Grid Communications, SmartGridComm 2017, Dresden, Germany, October 23-27, 2017, 2017)

Boosting the kernelized shapelets: Theory and algorithms for local features - Daiki Suehiro; Kohei Hatano; Eiji Takimoto; Shuji Yamamoto; Kenichi Bannai; Akiko Takeda (CoRR, 2017)

Optimistic Robust Optimization With Applications To Machine Learning - Matthew Norton; Akiko Takeda; Alexander Mafusalov (CoRR, 2017)

Solving Generalized CDT Problems via Two-Parameter Eigenvalues - Shinsaku Sakaue; Yuji Nakatsukasa; Akiko Takeda; Satoru Iwata (SIAM J. Optim., 2016)

Outlier detection at the transcriptome-proteome interface - Yawwani Gunawardana; Shuhei Fujiwara; Akiko Takeda; Jeongmin Woo; Christopher H. Woelk; Mahesan Niranjan (Bioinform., 2015)

Optimizing over coherent risk measures and non-convexities: a robust mixed integer optimization approach - Dimitris Bertsimas; Akiko Takeda (Comput. Optim. Appl., 2015)

Geometric intuition and algorithms for Ev-SVM - Álvaro Barbero Jiménez; Akiko Takeda; Jorge López Lázaro (J. Mach. Learn. Res., 2015)

Computing the Signed Distance Between Overlapping Ellipsoids - Satoru Iwata; Yuji Nakatsukasa; Akiko Takeda (SIAM J. Optim., 2015)

Cyber Security Analysis of Power Networks by Hypergraph Cut Algorithms - Yutaro Yamaguchi; Anna Ogawa; Akiko Takeda; Satoru Iwata (IEEE Trans. Smart Grid, 2015)

Robust Cost Sensitive Support Vector Machine - Shuichi Katsumata; Akiko Takeda (Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2015, San Diego, California, USA, May 9-12, 2015, 2015)

Numerical study of learning algorithms on Stiefel manifold - Takafumi Kanamori; Akiko Takeda (Comput. Manag. Sci., 2014)

Interaction between financial risk measures and machine learning methods - Jun-ya Gotoh; Akiko Takeda; Rei Yamamoto (Comput. Manag. Sci., 2014)

Extended Robust Support Vector Machine Based on Financial Risk Minimization - Akiko Takeda; Shuhei Fujiwara; Takafumi Kanamori (Neural Comput., 2014)

Using financial risk measures for analyzing generalization performance of machine learning models - Akiko Takeda; Takafumi Kanamori (Neural Networks, 2014)

Global Optimization Methods for Extended Fisher Discriminant Analysis - Satoru Iwata; Yuji Nakatsukasa; Akiko Takeda (Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, AISTATS 2014, Reykjavik, Iceland, April 22-25, 2014, 2014)

Memory-efficient large-scale linear support vector machine - Abdullah Alrajeh; Akiko Takeda; Mahesan Niranjan (Seventh International Conference on Machine Vision, ICMV 2014, Milan, Italy, 19-21 November 2014, 2014)

Exact SVM training by Wolfe's minimum norm point algorithm - Masashi Kitamura; Akiko Takeda; Satoru Iwata (IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2014, Reims, France, September 21-24, 2014, 2014)

Cyber security analysis of power networks by hypergraph cut algorithms - Yutaro Yamaguchi; Anna Ogawa; Akiko Takeda; Satoru Iwata (2014 IEEE International Conference on Smart Grid Communications, SmartGridComm 2014, Venice, Italy, November 3-6, 2014, 2014)

Breakdown Point of Robust Support Vector Machine - Takafumi Kanamori; Shuhei Fujiwara; Akiko Takeda (CoRR, 2014)

Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios - Akiko Takeda; Mahesan Niranjan; Jun-ya Gotoh; Yoshinobu Kawahara (Comput. Manag. Sci., 2013)

Conjugate relation between loss functions and uncertainty sets in classification problems - Takafumi Kanamori; Akiko Takeda; Taiji Suzuki (J. Mach. Learn. Res., 2013)

A Unified Classification Model Based on Robust Optimization - Akiko Takeda; Hiroyuki Mitsugi; Takafumi Kanamori (Neural Comput., 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 (Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States, 2013)

Convex hull pricing for demand response in electricity markets - Naoki Ito; Akiko Takeda; Toru Namerikawa (IEEE Fourth International Conference on Smart Grid Communications, SmartGridComm 2013, Vancouver, BC, Canada, October 21-24, 2013, 2013)

Minimizing loss probability bounds for portfolio selection - Jun-ya Gotoh; Akiko Takeda (Eur. J. Oper. Res., 2012)

Worst-Case Violation of Sampled Convex Programs for Optimization with Uncertainty - Takafumi Kanamori; Akiko Takeda (J. Optim. Theory Appl., 2012)

A Unified Robust Classification Model - Akiko Takeda; Hiroyuki Mitsugi; Takafumi Kanamori (Proceedings of the 29th International Conference on Machine Learning, ICML 2012, Edinburgh, Scotland, UK, June 26 - July 1, 2012, 2012)

Non-convex Optimization on Stiefel Manifold and Applications to Machine Learning - Takafumi Kanamori; Akiko Takeda (Neural Information Processing - 19th International Conference, ICONIP 2012, Doha, Qatar, November 12-15, 2012, Proceedings, Part I, 2012)

A Conjugate Property between Loss Functions and Uncertainty Sets in Classification Problems - Takafumi Kanamori; Akiko Takeda; Taiji Suzuki (COLT 2012 - The 25th Annual Conference on Learning Theory, June 25-27, 2012, Edinburgh, Scotland, 2012)

A Conjugate Property between Loss Functions and Uncertainty Sets in Classification Problems - Takafumi Kanamori; Akiko Takeda; Taiji Suzuki (CoRR, 2012)

A Unified Robust Classification Model - Akiko Takeda; Hiroyuki Mitsugi; Takafumi Kanamori (CoRR, 2012)

On the role of norm constraints in portfolio selection - Jun-ya Gotoh; Akiko Takeda (Comput. Manag. Sci., 2011)

A relaxation algorithm with a probabilistic guarantee for robust deviation optimization - Akiko Takeda; Shunsuke Taguchi; Tsutomu Tanaka (Comput. Optim. Appl., 2010)

A robust approach based on conditional value-at-risk measure to statistical learning problems - Akiko Takeda; Takafumi Kanamori (Eur. J. Oper. Res., 2009)

Generalization performance of nu-support vector classifier based on conditional value-at-risk minimization - Akiko Takeda (Neurocomputing, 2009)

On Generalization Performance and Non-Convex Optimization of Extended nu-Support Vector Machine - Akiko Takeda; Masashi Sugiyama (New Gener. Comput., 2009)

Conditional minimum volume ellipsoid with application to multiclass discrimination - Jun-ya Gotoh; Akiko Takeda (Comput. Optim. Appl., 2008)

nu-support vector machine as conditional value-at-risk minimization - Akiko Takeda; Masashi Sugiyama (Machine Learning, Proceedings of the Twenty-Fifth International Conference (ICML 2008), Helsinki, Finland, June 5-9, 2008, 2008)

Dynamic Enumeration of All Mixed Cells - Tomohiko Mizutani; Akiko Takeda; Masakazu Kojima (Discret. Comput. Geom., 2007)

PHoM - a Polyhedral Homotopy Continuation Method for Polynomial Systems - Takayuki Gunji; Sunyoung Kim; Masakazu Kojima; Akiko Takeda; Katsuki Fujisawa; Tomohiko Mizutani (Computing, 2004)

High Performance Grid and Cluster Computing for Some Optimization Problems - Katsuki Fujisawa; Masakazu Kojima; Akiko Takeda; Makoto Yamashita (2004 Symposium on Applications and the Internet Workshops (SAINT 2004 Workshops), 26-30 January 2004, Tokyo, Japan, 2004)

Parallel Implementation of Successive Convex Relaxation Methods for Quadratic Optimization Problems - Akiko Takeda; Katsuki Fujisawa; Yusuke Fukaya; Masakazu Kojima (J. Glob. Optim., 2002)

On measuring the inefficiency with the inner-product norm in data envelopment analysis - Akiko Takeda; Hisakazu Nishino (Eur. J. Oper. Res., 2001)

Complexity Analysis of Successive Convex Relaxation Methods for Nonconvex Sets - Masakazu Kojima; Akiko Takeda (Math. Oper. Res., 2001)