Tianxiang Liu, Akiko Takeda. An inexact successive quadratic approximation method for a class of difference-of-convex optimization problems. Computational Optimization and Applications. 2022. 82. 1. 141-173
Ivan Markovsky, Tianxiang Liu, Akiko Takeda. Data-Driven Structured Noise Filtering via Common Dynamics Estimation. IEEE Transactions on Signal Processing. 2020. 68. 3064-3073
Tianxiang Liu, Ivan Markovsky, Ting Kei Pong, Akiko Takeda. A Hybrid Penalty Method for a Class of Optimization Problems with Multiple Rank Constraints. SIAM Journal on Matrix Analysis and Applications. 2020. 41. 3. 1260-1283
Kazuhiro Sato, Akiko Takeda. Controllability maximization of large-scale systems using projected gradient method. IEEE Control Systems Letters. 2020. 1-1
CVaR Minimizations in Support Vector Machines
2016
講演・口頭発表等 (29件)：
Efficient DC Algorithm for Sparse Optimization Problems
(Tokyo Deep Learning Work- shop 2018 2018)
Optimal Sizing of Photovoltaic Systems for Loss Minimization
(2018 SICE International Symposium on Control Systems 2018)
Efficient DC Algorithm for Sparse Optimization Problems
(Georgia Tech and Friedrich- Alexander-Universitat Workshop 2018 2018)
Learning theory and algorithms for shapelets and other local features
(NIPS 2017 Time Series Workshop 2017)
Position-based Multiple-play Multi-armed Bandit Problem with Unknown Position Bias
(The Thirty-First Annual Conference on Neural Infor- mation Processing Systems 2017)
