Akiko Takeda

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 59

Top Topics

Optimization Problems

Quadratic Optimization

Top Venues

Comput. Optim. Appl.

J. Mach. Learn. Res.

Publications

Andi Han, Bamdev Mishra, Pratik Jawanpuria, Akiko Takeda
A Framework for Bilevel Optimization on Riemannian Manifolds. CoRR (2024)
Mitsuaki Obara, Kazuhiro Sato, Hiroki Sakamoto, Takayuki Okuno, Akiko Takeda
Stable Linear System Identification With Prior Knowledge by Riemannian Sequential Quadratic Optimization. IEEE Trans. Autom. Control. 69 (3) (2024)
Andi Han, Jiaxiang Li, Wei Huang, Mingyi Hong, Akiko Takeda, Pratik Jawanpuria, Bamdev Mishra
SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining. CoRR (2024)
Naoki Marumo, Akiko Takeda
Parameter-Free Accelerated Gradient Descent for Nonconvex Minimization. SIAM J. Optim. 34 (2) (2024)
Tianxiang Liu, Ting Kei Pong, Akiko Takeda
Doubly majorized algorithm for sparsity-inducing optimization problems with regularizer-compatible constraints. Comput. Optim. Appl. 86 (2) (2023)
Daniel Andrade, Akiko Takeda
Robust Gaussian process regression with the trimmed marginal likelihood. UAI (2023)
Naoki Marumo, Takayuki Okuno, Akiko Takeda
Majorization-minimization-based Levenberg-Marquardt method for constrained nonlinear least squares. Comput. Optim. Appl. 84 (3) (2023)
Shun Arahata, Takayuki Okuno, Akiko Takeda
Complexity analysis of interior-point methods for second-order stationary points of nonlinear semidefinite optimization problems. Comput. Optim. Appl. 86 (2) (2023)
Issey Sukeda, Atsushi Miyauchi, Akiko Takeda
A study on modularity density maximization: Column generation acceleration and computational complexity analysis. Eur. J. Oper. Res. 309 (2) (2023)
Terunari Fuji, Pierre-Louis Poirion, Akiko Takeda
Convexification with Bounded Gap for Randomly Projected Quadratic Optimization. SIAM J. Optim. 32 (2) (2022)
Michael R. Metel, Akiko Takeda
Perturbed Iterate SGD for Lipschitz Continuous Loss Functions. J. Optim. Theory Appl. 195 (2) (2022)
Mitsuaki Obara, Takayuki Okuno, Akiko Takeda
Sequential Quadratic Optimization for Nonlinear Optimization Problems on Riemannian Manifolds. SIAM J. Optim. 32 (2) (2022)
Tianxiang Liu, Akiko Takeda
An inexact successive quadratic approximation method for a class of difference-of-convex optimization problems. Comput. Optim. Appl. 82 (1) (2022)
Hidenori Iwakiri, Yuhang Wang, Shinji Ito, Akiko Takeda
Single Loop Gaussian Homotopy Method for Non-convex Optimization. NeurIPS (2022)
Issey Sukeda, Atsushi Miyauchi, Akiko Takeda
A Study on Modularity Density Maximization: Column Generation Acceleration and Computational Complexity Analysis. CoRR (2022)
Ryo Sato, Mirai Tanaka, Akiko Takeda
A Gradient Method for Multilevel Optimization. NeurIPS (2021)
Yuto Mori, Atsushi Nitanda, Akiko Takeda
BODAME: Bilevel Optimization for Defense Against Model Extraction. CoRR (2021)
Michael R. Metel, Akiko Takeda
Primal-dual subgradient method for constrained convex optimization problems. Optim. Lett. 15 (4) (2021)
Naoki Marumo, Atsushi Miyauchi, Akiko Takeda, Akira Tanaka
A Projected Gradient Method for Opinion Optimization with Limited Changes of Susceptibility to Persuasion. CIKM (2021)
Takayuki Okuno, Akiko Takeda, Akihiro Kawana, Motokazu Watanabe
On lp-hyperparameter Learning via Bilevel Nonsmooth Optimization. J. Mach. Learn. Res. 22 (2021)
Michael R. Metel, Akiko Takeda
Stochastic Proximal Methods for Non-Smooth Non-Convex Constrained Sparse Optimization. J. Mach. Learn. Res. 22 (2021)
Ryo Sato, Mirai Tanaka, Akiko Takeda
A Gradient Method for Multilevel Optimization. CoRR (2021)
Naoki Marumo, Atsushi Miyauchi, Akiko Takeda, Akira Tanaka
A Projected Gradient Method for Opinion Optimization with Limited Changes of Susceptibility to Persuasion. CoRR (2021)
Hikaru Ogura, Akiko Takeda
Convex Fairness Constrained Model Using Causal Effect Estimators. CoRR (2020)
Bruno F. Lourenço, Akiko Takeda
Generalized Subdifferentials of Spectral Functions over Euclidean Jordan Algebras. SIAM J. Optim. 30 (4) (2020)
Daiki Suehiro, Kohei Hatano, Eiji Takimoto, Shuji Yamamoto, Kenichi Bannai, Akiko Takeda
Theory and Algorithms for Shapelet-based Multiple-Instance Learning. CoRR (2020)
Donya Rahmani, Mahesan Niranjan, Damien Fay, Akiko Takeda, Jacek Brodzki
Estimation of Gaussian mixture models via tensor moments with application to online learning. Pattern Recognit. Lett. 131 (2020)
Hikaru Ogura, Akiko Takeda
Convex Fairness Constrained Model Using Causal Effect Estimators. WWW (Companion Volume) (2020)
Daniel Andrade, Akiko Takeda, Kenji Fukumizu
Robust Bayesian model selection for variable clustering with the Gaussian graphical model. Stat. Comput. 30 (2) (2020)
Tianxiang Liu, Ivan Markovsky, Ting Kei Pong, Akiko Takeda
A Hybrid Penalty Method for a Class of Optimization Problems with Multiple Rank Constraints. SIAM J. Matrix Anal. Appl. 41 (3) (2020)
Kazuhiro Sato, Akiko Takeda
Construction Methods of the Nearest Positive System. IEEE Control. Syst. Lett. 4 (1) (2020)
Ivan Markovsky, Tianxiang Liu, Akiko Takeda
Data-Driven Structured Noise Filtering via Common Dynamics Estimation. IEEE Trans. Signal Process. 68 (2020)
Daiki Suehiro, Kohei Hatano, Eiji Takimoto, Shuji Yamamoto, Kenichi Bannai, Akiko Takeda
Theory and Algorithms for Shapelet-Based Multiple-Instance Learning. Neural Comput. 32 (8) (2020)
Kazuhiro Sato, Akiko Takeda
Controllability Maximization of Large-Scale Systems Using Projected Gradient Method. IEEE Control. Syst. Lett. 4 (4) (2020)
Ivan Markovsky, Tianxiang Liu, Akiko Takeda
Subspace methods for multi-channel sum-of-exponentials common dynamics estimation. CDC (2019)
Tianxiang Liu, Ting Kei Pong, Akiko Takeda
A refined convergence analysis of \(\hbox {pDCA}_{e}\) with applications to simultaneous sparse recovery and outlier detection. Comput. Optim. Appl. 73 (1) (2019)
Michael R. Metel, Akiko Takeda
Simple Stochastic Gradient Methods for Non-Smooth Non-Convex Regularized Optimization. ICML (2019)
Naoki Ito, Sunyoung Kim, Masakazu Kojima, Akiko Takeda, Kim-Chuan Toh
Algorithm 996: BBCPOP: A Sparse Doubly Nonnegative Relaxation of Polynomial Optimization Problems With Binary, Box, and Complementarity Constraints. ACM Trans. Math. Softw. 45 (3) (2019)
Tianxiang Liu, Ting Kei Pong, Akiko Takeda
A successive difference-of-convex approximation method for a class of nonconvex nonsmooth optimization problems. Math. Program. 176 (1-2) (2019)
Atsushi Miyauchi, Akiko Takeda
Robust Densest Subgraph Discovery. CoRR (2018)
Junpei Komiyama, Akiko Takeda, Junya Honda, Hajime Shimao
Nonconvex Optimization for Regression with Fairness Constraints. ICML (2018)
Jorge López Lázaro, Álvaro Barbero Jiménez, Akiko Takeda
Improving cash logistics in bank branches by coupling machine learning and robust optimization. Expert Syst. Appl. 92 (2018)
Jun-ya Gotoh, Akiko Takeda, Katsuya Tono
DC formulations and algorithms for sparse optimization problems. Math. Program. 169 (1) (2018)
Daiki Suehiro, Kohei Hatano, Eiji Takimoto, Shuji Yamamoto, Kenichi Bannai, Akiko Takeda
Multiple-Instance Learning by Boosting Infinitely Many Shapelet-based Classifiers. CoRR (2018)
Shinji Yamada, Akiko Takeda
Successive Lagrangian relaxation algorithm for nonconvex quadratic optimization. J. Glob. Optim. 71 (2) (2018)
Atsushi Miyauchi, Akiko Takeda
Robust Densest Subgraph Discovery. ICDM (2018)
Naoki Ito, Sunyoung Kim, Masakazu Kojima, Akiko Takeda, Kim-Chuan Toh
Equivalences and differences in conic relaxations of combinatorial quadratic optimization problems. J. Glob. Optim. 72 (4) (2018)
Matthew Norton, Akiko Takeda, Alexander Mafusalov
Optimistic Robust Optimization With Applications To Machine Learning. CoRR (2017)
Song Liu, Akiko Takeda, Taiji Suzuki, Kenji Fukumizu
Trimmed Density Ratio Estimation. NIPS (2017)
Takafumi Kanamori, Shuhei Fujiwara, Akiko Takeda
Breakdown Point of Robust Support Vector Machines. Entropy 19 (2) (2017)
Daiki Suehiro, Kohei Hatano, Eiji Takimoto, Shuji Yamamoto, Kenichi Bannai, Akiko Takeda
Boosting the kernelized shapelets: Theory and algorithms for local features. CoRR (2017)
Shinsaku Sakaue, Akiko Takeda, Sunyoung Kim, Naoki Ito
Exact Semidefinite Programming Relaxations with Truncated Moment Matrix for Binary Polynomial Optimization Problems. SIAM J. Optim. 27 (1) (2017)
Satoru Adachi, Satoru Iwata, Yuji Nakatsukasa, Akiko Takeda
Solving the Trust-Region Subproblem By a Generalized Eigenvalue Problem. SIAM J. Optim. 27 (1) (2017)
Kosuke Nishida, Akiko Takeda, Satoru Iwata, Mariko Kiho, Isao Nakayama
Household energy consumption prediction by feature selection of lifestyle data. SmartGridComm (2017)
Junpei Komiyama, Junya Honda, Akiko Takeda
Position-based Multiple-play Bandit Problem with Unknown Position Bias. NIPS (2017)
Naoki Ito, Akiko Takeda, Kim-Chuan Toh
A Unified Formulation and Fast Accelerated Proximal Gradient Method for Classification. J. Mach. Learn. Res. 18 (2017)
Takafumi Kanamori, Shuhei Fujiwara, Akiko Takeda
Robustness of learning algorithms using hinge loss with outlier indicators. Neural Networks 94 (2017)
Shuhei Fujiwara, Akiko Takeda, Takafumi Kanamori
DC Algorithm for Extended Robust Support Vector Machine. Neural Comput. 29 (5) (2017)
Shinsaku Sakaue, Yuji Nakatsukasa, Akiko Takeda, Satoru Iwata
Solving Generalized CDT Problems via Two-Parameter Eigenvalues. SIAM J. Optim. 26 (3) (2016)
Yawwani Gunawardana, Shuhei Fujiwara, Akiko Takeda, Jeongmin Woo, Christopher H. Woelk, Mahesan Niranjan
Outlier detection at the transcriptome-proteome interface. Bioinform. 31 (15) (2015)
Yutaro Yamaguchi, Anna Ogawa, Akiko Takeda, Satoru Iwata
Cyber Security Analysis of Power Networks by Hypergraph Cut Algorithms. IEEE Trans. Smart Grid 6 (5) (2015)
Dimitris Bertsimas, Akiko Takeda
Optimizing over coherent risk measures and non-convexities: a robust mixed integer optimization approach. Comput. Optim. Appl. 62 (3) (2015)
Shuichi Katsumata, Akiko Takeda
Robust Cost Sensitive Support Vector Machine. AISTATS (2015)
Satoru Iwata, Yuji Nakatsukasa, Akiko Takeda
Computing the Signed Distance Between Overlapping Ellipsoids. SIAM J. Optim. 25 (4) (2015)
Álvaro Barbero Jiménez, Akiko Takeda, Jorge López Lázaro
Geometric intuition and algorithms for Ev-SVM. J. Mach. Learn. Res. 16 (2015)
Abdullah Alrajeh, Akiko Takeda, Mahesan Niranjan
Memory-efficient large-scale linear support vector machine. ICMV (2014)
Yutaro Yamaguchi, Anna Ogawa, Akiko Takeda, Satoru Iwata
Cyber security analysis of power networks by hypergraph cut algorithms. SmartGridComm (2014)
Takafumi Kanamori, Akiko Takeda
Numerical study of learning algorithms on Stiefel manifold. Comput. Manag. Sci. 11 (4) (2014)
Satoru Iwata, Yuji Nakatsukasa, Akiko Takeda
Global Optimization Methods for Extended Fisher Discriminant Analysis. AISTATS (2014)
Akiko Takeda, Takafumi Kanamori
Using financial risk measures for analyzing generalization performance of machine learning models. Neural Networks 57 (2014)
Takafumi Kanamori, Shuhei Fujiwara, Akiko Takeda
Breakdown Point of Robust Support Vector Machine. CoRR (2014)
Akiko Takeda, Shuhei Fujiwara, Takafumi Kanamori
Extended Robust Support Vector Machine Based on Financial Risk Minimization. Neural Comput. 26 (11) (2014)
Masashi Kitamura, Akiko Takeda, Satoru Iwata
Exact SVM training by Wolfe's minimum norm point algorithm. MLSP (2014)
Jun-ya Gotoh, Akiko Takeda, Rei Yamamoto
Interaction between financial risk measures and machine learning methods. Comput. Manag. Sci. 11 (4) (2014)
Shinichi Nakajima, Akiko Takeda, S. Derin Babacan, Masashi Sugiyama, Ichiro Takeuchi
Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering. NIPS (2013)
Akiko Takeda, Hiroyuki Mitsugi, Takafumi Kanamori
A Unified Classification Model Based on Robust Optimization. Neural Comput. 25 (3) (2013)
Akiko Takeda, Mahesan Niranjan, Jun-ya Gotoh, Yoshinobu Kawahara
Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios. Comput. Manag. Sci. 10 (1) (2013)
Naoki Ito, Akiko Takeda, Toru Namerikawa
Convex hull pricing for demand response in electricity markets. SmartGridComm (2013)
Takafumi Kanamori, Akiko Takeda, Taiji Suzuki
Conjugate relation between loss functions and uncertainty sets in classification problems. J. Mach. Learn. Res. 14 (1) (2013)
Takafumi Kanamori, Akiko Takeda
Worst-Case Violation of Sampled Convex Programs for Optimization with Uncertainty. J. Optim. Theory Appl. 152 (1) (2012)
Takafumi Kanamori, Akiko Takeda, Taiji Suzuki
A Conjugate Property between Loss Functions and Uncertainty Sets in Classification Problems. COLT (2012)
Takafumi Kanamori, Akiko Takeda
Non-convex Optimization on Stiefel Manifold and Applications to Machine Learning. ICONIP (1) (2012)
Jun-ya Gotoh, Akiko Takeda
Minimizing loss probability bounds for portfolio selection. Eur. J. Oper. Res. 217 (2) (2012)
Takafumi Kanamori, Akiko Takeda, Taiji Suzuki
A Conjugate Property between Loss Functions and Uncertainty Sets in Classification Problems CoRR (2012)
Akiko Takeda, Hiroyuki Mitsugi, Takafumi Kanamori
A Unified Robust Classification Model. ICML (2012)
Akiko Takeda, Hiroyuki Mitsugi, Takafumi Kanamori
A Unified Robust Classification Model CoRR (2012)
Jun-ya Gotoh, Akiko Takeda
On the role of norm constraints in portfolio selection. Comput. Manag. Sci. 8 (4) (2011)
Akiko Takeda, Shunsuke Taguchi, Tsutomu Tanaka
A relaxation algorithm with a probabilistic guarantee for robust deviation optimization. Comput. Optim. Appl. 47 (1) (2010)
Akiko Takeda, Masashi Sugiyama
-Support Vector Machine. New Gener. Comput. 27 (3) (2009)
Akiko Takeda, Takafumi Kanamori
A robust approach based on conditional value-at-risk measure to statistical learning problems. Eur. J. Oper. Res. 198 (1) (2009)
Akiko Takeda
Generalization performance of nu-support vector classifier based on conditional value-at-risk minimization. Neurocomputing 72 (10-12) (2009)
Akiko Takeda, Masashi Sugiyama
-support vector machine as conditional value-at-risk minimization. ICML (2008)
Jun-ya Gotoh, Akiko Takeda
Conditional minimum volume ellipsoid with application to multiclass discrimination. Comput. Optim. Appl. 41 (1) (2008)
Tomohiko Mizutani, Akiko Takeda, Masakazu Kojima
Dynamic Enumeration of All Mixed Cells. Discret. Comput. Geom. 37 (3) (2007)
Takayuki Gunji, Sunyoung Kim, Masakazu Kojima, Akiko Takeda, Katsuki Fujisawa, Tomohiko Mizutani
PHoM - a Polyhedral Homotopy Continuation Method for Polynomial Systems. Computing 73 (1) (2004)
Katsuki Fujisawa, Masakazu Kojima, Akiko Takeda, Makoto Yamashita
High Performance Grid and Cluster Computing for Some Optimization Problems. SAINT Workshops (2004)
Akiko Takeda, Katsuki Fujisawa, Yusuke Fukaya, Masakazu Kojima
Parallel Implementation of Successive Convex Relaxation Methods for Quadratic Optimization Problems. J. Glob. Optim. 24 (2) (2002)
Akiko Takeda, Hisakazu Nishino
On measuring the inefficiency with the inner-product norm in data envelopment analysis. Eur. J. Oper. Res. 133 (2) (2001)
Masakazu Kojima, Akiko Takeda
Complexity Analysis of Successive Convex Relaxation Methods for Nonconvex Sets. Math. Oper. Res. 26 (3) (2001)