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Akiko Takeda

DC formulations and algorithms for sparse optimization problems
2017 · Jun-ya Gotoh, Akiko Takeda, et al. · Mathematical Programming · 184
PHoM ? a Polyhedral Homotopy Continuation Method for Polynomial Systems
2004 · Takayuki Gunji, Sunyoung Kim, et al. · Computing · 99
Solving the Trust-Region Subproblem By a Generalized Eigenvalue Problem
2017 · Satoru Adachi, Satoru Iwata, et al. · SIAM Journal on Optimization · 80
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Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios
2012 · Akiko Takeda, Mahesan Niranjan, et al. · Computational Management Science · 76
Nonconvex Optimization for Regression with Fairness Constraints.
2018 · Junpei Komiyama, Akiko Takeda, et al. · ScholarSphere (Penn State Libraries) · 61
On the role of norm constraints in portfolio selection
2011 · Jun-ya Gotoh, Akiko Takeda · Computational Management Science · 59
ν -support vector machine as conditional value-at-risk minimization
2008 · Akiko Takeda, Masashi Sugiyama · International Conference on Machine Learning · 57
A refined convergence analysis of $$\hbox {pDCA}_{e}$$ pDCA e with applications to simultaneous sparse recovery and outlier detection
2019 · Tianxiang Liu, Ting Kei Pong, et al. · Computational Optimization and Applications · 51
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Improving cash logistics in bank branches by coupling machine learning and robust optimization
2017 · Jorge López Lázaro, Álvaro Barbero Jiménez, et al. · Expert Systems with Applications · 47
A successive difference-of-convex approximation method for a class of nonconvex nonsmooth optimization problems
2018 · Tianxiang Liu, Ting Kei Pong, et al. · Mathematical Programming · 41
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A robust approach based on conditional value-at-risk measure to statistical learning problems
2008 · Akiko Takeda, Takafumi Kanamori · European Journal of Operational Research · 41
Solving Generalized CDT Problems via Two-Parameter Eigenvalues
2016 · Shinsaku Sakaue, Yuji Nakatsukasa, et al. · SIAM Journal on Optimization · 38
SLTrain: a sparse plus low rank approach for parameter and memory efficient pretraining
2024 · Andi Han, Jiaxiang Li, et al. · neural information processing systems · 34
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Robust portfolio techniques for mitigating the fragility of CVaR minimization and generalization to coherent risk measures
2013 · Jun-Ya Gotoh, Keita Shinozaki, et al. · Quantitative Finance · 34
Dynamic Enumeration of All Mixed Cells
2007 · Tomohiko Mizutani, Akiko Takeda, et al. · Discrete & Computational Geometry · 31
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Efficient DC Algorithm for Constrained Sparse Optimization
2017 · Tono, Katsuya, Takeda, Akiko, et al. · arXiv (Cornell University) · 30
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Majorization-minimization-based Levenberg–Marquardt method for constrained nonlinear least squares
2023 · Naoki Marumo, Takayuki Okuno, et al. · Computational Optimization and Applications · 28
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Enumeration of All Solutions of a Combinatorial Linear Inequality System Arising From the Polyhedral Homotopy Continuation Method
2002 · Akiko Takeda, Masakazu Kojima, et al. · Journal of the Operations Research Society of Japan · 26
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Non-convex Optimization on Stiefel Manifold and Applications to Machine Learning
2012 · Takafumi Kanamori, Akiko Takeda · Lecture notes in computer science · 25
On $\ell_p$-hyperparameter Learning via Bilevel Nonsmooth Optimization
2018 · Okuno, Takayuki, Takeda, Akiko, et al. · arXiv (Cornell University) · 23
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A unified formulation and fast accelerated proximal gradient method for classification
2017 · Naoki Ito, Akiko Takeda, et al. · Journal of Machine Learning Research · 23
Worst-Case Violation of Sampled Convex Programs for Optimization with Uncertainty
2011 · Takafumi Kanamori, Akiko Takeda · Journal of Optimization Theory and Applications · 23
DEMiCs: A Software Package for Computing the Mixed Volume Via Dynamic Enumeration of all Mixed Cells
2008 · Tomohiko Mizutani, Akiko Takeda · The IMA volumes in mathematics and its applications · 23
A linear classification model based on conditional geometric score
2004 · Jun‐ya Gotoh, Akiko Takeda · 21
Using financial risk measures for analyzing generalization performance of machine learning models
2014 · Akiko Takeda, Takafumi Kanamori · Neural Networks · 20
Works count: 198
Citation count: 1,975
H-index: 23
I10-index: 57
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