Akiko Takeda

Orcid: 0000-0002-8846-4496

According to our database1, Akiko Takeda authored at least 90 papers between 2001 and 2024.

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Bibliography

2024
Stable Linear System Identification With Prior Knowledge by Riemannian Sequential Quadratic Optimization.
IEEE Trans. Autom. Control., March, 2024

Parameter-Free Accelerated Gradient Descent for Nonconvex Minimization.
SIAM J. Optim., 2024

SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining.
CoRR, 2024

A Framework for Bilevel Optimization on Riemannian Manifolds.
CoRR, 2024

2023
Doubly majorized algorithm for sparsity-inducing optimization problems with regularizer-compatible constraints.
Comput. Optim. Appl., November, 2023

Complexity analysis of interior-point methods for second-order stationary points of nonlinear semidefinite optimization problems.
Comput. Optim. Appl., November, 2023

A study on modularity density maximization: Column generation acceleration and computational complexity analysis.
Eur. J. Oper. Res., September, 2023

Majorization-minimization-based Levenberg-Marquardt method for constrained nonlinear least squares.
Comput. Optim. Appl., April, 2023

Robust Gaussian process regression with the trimmed marginal likelihood.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

2022
Sequential Quadratic Optimization for Nonlinear Optimization Problems on Riemannian Manifolds.
SIAM J. Optim., 2022

Convexification with Bounded Gap for Randomly Projected Quadratic Optimization.
SIAM J. Optim., 2022

Perturbed Iterate SGD for Lipschitz Continuous Loss Functions.
J. Optim. Theory Appl., 2022

An inexact successive quadratic approximation method for a class of difference-of-convex optimization problems.
Comput. Optim. Appl., 2022

Single Loop Gaussian Homotopy Method for Non-convex Optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Primal-dual subgradient method for constrained convex optimization problems.
Optim. Lett., 2021

On lp-hyperparameter Learning via Bilevel Nonsmooth Optimization.
J. Mach. Learn. Res., 2021

Stochastic Proximal Methods for Non-Smooth Non-Convex Constrained Sparse Optimization.
J. Mach. Learn. Res., 2021

BODAME: Bilevel Optimization for Defense Against Model Extraction.
CoRR, 2021

A Gradient Method for Multilevel Optimization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Projected Gradient Method for Opinion Optimization with Limited Changes of Susceptibility to Persuasion.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
Data-Driven Structured Noise Filtering via Common Dynamics Estimation.
IEEE Trans. Signal Process., 2020

A Hybrid Penalty Method for a Class of Optimization Problems with Multiple Rank Constraints.
SIAM J. Matrix Anal. Appl., 2020

Generalized Subdifferentials of Spectral Functions over Euclidean Jordan Algebras.
SIAM J. Optim., 2020

Robust Bayesian model selection for variable clustering with the Gaussian graphical model.
Stat. Comput., 2020

Estimation of Gaussian mixture models via tensor moments with application to online learning.
Pattern Recognit. Lett., 2020

Theory and Algorithms for Shapelet-Based Multiple-Instance Learning.
Neural Comput., 2020

Controllability Maximization of Large-Scale Systems Using Projected Gradient Method.
IEEE Control. Syst. Lett., 2020

Construction Methods of the Nearest Positive System.
IEEE Control. Syst. Lett., 2020

Convex Fairness Constrained Model Using Causal Effect Estimators.
Proceedings of the Companion of The 2020 Web Conference 2020, 2020

2019
Algorithm 996: BBCPOP: A Sparse Doubly Nonnegative Relaxation of Polynomial Optimization Problems With Binary, Box, and Complementarity Constraints.
ACM Trans. Math. Softw., 2019

A successive difference-of-convex approximation method for a class of nonconvex nonsmooth optimization problems.
Math. Program., 2019

A refined convergence analysis of \(\hbox {pDCA}_{e}\) with applications to simultaneous sparse recovery and outlier detection.
Comput. Optim. Appl., 2019

Simple Stochastic Gradient Methods for Non-Smooth Non-Convex Regularized Optimization.
Proceedings of the 36th International Conference on Machine Learning, 2019

Subspace methods for multi-channel sum-of-exponentials common dynamics estimation.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018
DC formulations and algorithms for sparse optimization problems.
Math. Program., 2018

Successive Lagrangian relaxation algorithm for nonconvex quadratic optimization.
J. Glob. Optim., 2018

Equivalences and differences in conic relaxations of combinatorial quadratic optimization problems.
J. Glob. Optim., 2018

Improving cash logistics in bank branches by coupling machine learning and robust optimization.
Expert Syst. Appl., 2018

Multiple-Instance Learning by Boosting Infinitely Many Shapelet-based Classifiers.
CoRR, 2018

Nonconvex Optimization for Regression with Fairness Constraints.
Proceedings of the 35th International Conference on Machine Learning, 2018

Robust Densest Subgraph Discovery.
Proceedings of the IEEE International Conference on Data Mining, 2018

2017
Exact Semidefinite Programming Relaxations with Truncated Moment Matrix for Binary Polynomial Optimization Problems.
SIAM J. Optim., 2017

Solving the Trust-Region Subproblem By a Generalized Eigenvalue Problem.
SIAM J. Optim., 2017

Robustness of learning algorithms using hinge loss with outlier indicators.
Neural Networks, 2017

DC Algorithm for Extended Robust Support Vector Machine.
Neural Comput., 2017

A Unified Formulation and Fast Accelerated Proximal Gradient Method for Classification.
J. Mach. Learn. Res., 2017

Breakdown Point of Robust Support Vector Machines.
Entropy, 2017

Optimistic Robust Optimization With Applications To Machine Learning.
CoRR, 2017

Boosting the kernelized shapelets: Theory and algorithms for local features.
CoRR, 2017

Household energy consumption prediction by feature selection of lifestyle data.
Proceedings of the 2017 IEEE International Conference on Smart Grid Communications, 2017

Trimmed Density Ratio Estimation.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Position-based Multiple-play Bandit Problem with Unknown Position Bias.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Solving Generalized CDT Problems via Two-Parameter Eigenvalues.
SIAM J. Optim., 2016

2015
Cyber Security Analysis of Power Networks by Hypergraph Cut Algorithms.
IEEE Trans. Smart Grid, 2015

Computing the Signed Distance Between Overlapping Ellipsoids.
SIAM J. Optim., 2015

Geometric intuition and algorithms for Ev-SVM.
J. Mach. Learn. Res., 2015

Optimizing over coherent risk measures and non-convexities: a robust mixed integer optimization approach.
Comput. Optim. Appl., 2015

Outlier detection at the transcriptome-proteome interface.
Bioinform., 2015

Robust Cost Sensitive Support Vector Machine.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Using financial risk measures for analyzing generalization performance of machine learning models.
Neural Networks, 2014

Extended Robust Support Vector Machine Based on Financial Risk Minimization.
Neural Comput., 2014

Breakdown Point of Robust Support Vector Machine.
CoRR, 2014

Numerical study of learning algorithms on Stiefel manifold.
Comput. Manag. Sci., 2014

Interaction between financial risk measures and machine learning methods.
Comput. Manag. Sci., 2014

Exact SVM training by Wolfe's minimum norm point algorithm.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

Memory-efficient large-scale linear support vector machine.
Proceedings of the Seventh International Conference on Machine Vision, 2014

Global Optimization Methods for Extended Fisher Discriminant Analysis.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
A Unified Classification Model Based on Robust Optimization.
Neural Comput., 2013

Conjugate relation between loss functions and uncertainty sets in classification problems.
J. Mach. Learn. Res., 2013

Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios.
Comput. Manag. Sci., 2013

Convex hull pricing for demand response in electricity markets.
Proceedings of the IEEE Fourth International Conference on Smart Grid Communications, 2013

Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering.
Proceedings of the 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

2012
Worst-Case Violation of Sampled Convex Programs for Optimization with Uncertainty.
J. Optim. Theory Appl., 2012

A Conjugate Property between Loss Functions and Uncertainty Sets in Classification Problems.
Proceedings of the COLT 2012, 2012

Minimizing loss probability bounds for portfolio selection.
Eur. J. Oper. Res., 2012

Non-convex Optimization on Stiefel Manifold and Applications to Machine Learning.
Proceedings of the Neural Information Processing - 19th International Conference, 2012

A Unified Robust Classification Model.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
On the role of norm constraints in portfolio selection.
Comput. Manag. Sci., 2011

2010
A relaxation algorithm with a probabilistic guarantee for robust deviation optimization.
Comput. Optim. Appl., 2010

2009
On Generalization Performance and Non-Convex Optimization of Extended <i>nu</i>-Support Vector Machine.
New Gener. Comput., 2009

Generalization performance of nu-support vector classifier based on conditional value-at-risk minimization.
Neurocomputing, 2009

A robust approach based on conditional value-at-risk measure to statistical learning problems.
Eur. J. Oper. Res., 2009

2008
Conditional minimum volume ellipsoid with application to multiclass discrimination.
Comput. Optim. Appl., 2008

<i>nu</i>-support vector machine as conditional value-at-risk minimization.
Proceedings of the Machine Learning, 2008

2007
Dynamic Enumeration of All Mixed Cells.
Discret. Comput. Geom., 2007

2004
PHoM - a Polyhedral Homotopy Continuation Method for Polynomial Systems.
Computing, 2004

High Performance Grid and Cluster Computing for Some Optimization Problems.
Proceedings of the 2004 Symposium on Applications and the Internet Workshops (SAINT 2004 Workshops), 2004

2002
Parallel Implementation of Successive Convex Relaxation Methods for Quadratic Optimization Problems.
J. Glob. Optim., 2002

2001
Complexity Analysis of Successive Convex Relaxation Methods for Nonconvex Sets.
Math. Oper. Res., 2001

On measuring the inefficiency with the inner-product norm in data envelopment analysis.
Eur. J. Oper. Res., 2001


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