Jun-ya Gotoh

25 papers Journal 25
YearRankTypeTitle / Venue / Authors
2025 J jnl
Distributionally Robust Optimization is a Multi-Objective Problem.
CoRR
Jun-ya Gotoh, Michael Jong Kim, Andrew E. B. Lim
2025 J jnl
Technical Note - A Data-Driven Approach to Beating SAA Out of Sample.
Oper. Res.
Jun-ya Gotoh, Michael Jong Kim, Andrew E. B. Lim
2024 J jnl
Pursuit of the Cluster Structure of Network Lasso: Recovery Condition and Non-convex Extension.
J. Mach. Learn. Res.
Shotaro Yagishita, Jun-ya Gotoh
2021 J jnl
A data-driven approach to beating SAA out-of-sample.
CoRR
Jun-ya Gotoh, Michael Jong Kim, Andrew E. B. Lim
2021 J jnl
Calibration of Distributionally Robust Empirical Optimization Models.
Oper. Res.
Jun-ya Gotoh, Michael Jong Kim, Andrew E. B. Lim
2021 J jnl
On the superiority of PGMs to PDCAs in nonsmooth nonconvex sparse regression.
Optim. Lett.
Shummin Nakayama, Jun-ya Gotoh
2020 J jnl
Worst-case sensitivity.
CoRR
Jun-ya Gotoh, Michael Jong Kim, Andrew E. B. Lim
2018 J jnl
DC formulations and algorithms for sparse optimization problems.
Math. Program.
Jun-ya Gotoh, Akiko Takeda, Katsuya Tono
2018 J jnl
Preface.
Ann. Oper. Res.
Stan Uryasev, Jun-ya Gotoh
2018 J jnl
Robust empirical optimization is almost the same as mean-variance optimization.
Oper. Res. Lett.
Jun-ya Gotoh, Michael Jong Kim, Andrew E. B. Lim
2017 J jnl
Calibration of Distributionally Robust Empirical Optimization Models.
CoRR
Jun-ya Gotoh, Michael Jong Kim, Andrew E. B. Lim
2017 J jnl
Support vector machines based on convex risk functions and general norms.
Ann. Oper. Res.
Jun-ya Gotoh, Stan Uryasev
2016 J jnl
Two pairs of families of polyhedral norms versus ℓ p -norms: proximity and applications in optimization.
Math. Program.
Jun-ya Gotoh, Stan Uryasev
2014 J jnl
Interaction between financial risk measures and machine learning methods.
Comput. Manag. Sci.
Jun-ya Gotoh, Akiko Takeda, Rei Yamamoto
2014 J jnl
Multi-period portfolio selection using kernel-based control policy with dimensionality reduction.
Expert Syst. Appl.
Yuichi Takano, Jun-ya Gotoh
2013 J jnl
Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios.
Comput. Manag. Sci.
Akiko Takeda, Mahesan Niranjan, Jun-ya Gotoh, Yoshinobu Kawahara
2012 J jnl
Minimizing loss probability bounds for portfolio selection.
Eur. J. Oper. Res.
Jun-ya Gotoh, Akiko Takeda
2011 J jnl
Bounding Contingent Claim Prices via Hedging Strategy with Coherent Risk Measures.
J. Optim. Theory Appl.
Jun-ya Gotoh, Yoshitsugu Yamamoto, Weifeng Yao
2011 J jnl
On the role of norm constraints in portfolio selection.
Comput. Manag. Sci.
Jun-ya Gotoh, Akiko Takeda
2008 J jnl
Conditional minimum volume ellipsoid with application to multiclass discrimination.
Comput. Optim. Appl.
Jun-ya Gotoh, Akiko Takeda
2007 J jnl
Newsvendor solutions via conditional value-at-risk minimization.
Eur. J. Oper. Res.
Jun-ya Gotoh, Yuichi Takano
2006 J jnl
Minimal Ellipsoid Circumscribing a Polytope Defined by a System of Linear Inequalities.
J. Glob. Optim.
Jun-ya Gotoh, Hiroshi Konno
2003 J jnl
Global optimization method for solving the minimum maximal flow problem.
Optim. Methods Softw.
Jun-ya Gotoh, Nguyen Van Thoai, Yoshitsugu Yamamoto
2002 J jnl
Bounding Option Prices by Semidefinite Programming: A Cutting Plane Algorithm.
Manag. Sci.
Jun-ya Gotoh, Hiroshi Konno
2001 J jnl
Maximization of the Ratio of Two Convex Quadratic Functions over a Polytope.
Comput. Optim. Appl.
Jun-ya Gotoh, Hiroshi Konno