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Jun-ya Gotoh
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2020 – today
- 2024
- [j21]Shotaro Yagishita, Jun-ya Gotoh:
Pursuit of the Cluster Structure of Network Lasso: Recovery Condition and Non-convex Extension. J. Mach. Learn. Res. 25: 21:1-21:42 (2024) - 2021
- [j20]Jun-ya Gotoh
, Michael Jong Kim
Calibration of Distributionally Robust Empirical Optimization Models. Oper. Res. 69(5): 1630-1650 (2021) - [j19]Shummin Nakayama
On the superiority of PGMs to PDCAs in nonsmooth nonconvex sparse regression. Optim. Lett. 15(8): 2831-2860 (2021) - [i3]Jun-ya Gotoh, Michael Jong Kim, Andrew E. B. Lim:
A data-driven approach to beating SAA out-of-sample. CoRR abs/2105.12342 (2021) - 2020
- [i2]Jun-ya Gotoh, Michael Jong Kim, Andrew E. B. Lim:
Worst-case sensitivity. CoRR abs/2010.10794 (2020)
2010 – 2019
- 2018
- [j18]Stan Uryasev
Preface. Ann. Oper. Res. 262(1): 1-2 (2018) - [j17]Jun-ya Gotoh, Akiko Takeda, Katsuya Tono:
DC formulations and algorithms for sparse optimization problems. Math. Program. 169(1): 141-176 (2018) - [j16]Jun-ya Gotoh, Michael Jong Kim, Andrew E. B. Lim:
Robust empirical optimization is almost the same as mean-variance optimization. Oper. Res. Lett. 46(4): 448-452 (2018) - 2017
- [j15]Jun-ya Gotoh, Stan Uryasev
Support vector machines based on convex risk functions and general norms. Ann. Oper. Res. 249(1-2): 301-328 (2017) - [i1]Jun-ya Gotoh, Michael Jong Kim, Andrew E. B. Lim:
Calibration of Distributionally Robust Empirical Optimization Models. CoRR abs/1711.06565 (2017) - 2016
- [j14]Jun-ya Gotoh, Stan Uryasev
Two pairs of families of polyhedral norms versus ℓ p -norms: proximity and applications in optimization. Math. Program. 156(1-2): 391-431 (2016) - 2014
- [j13]Jun-ya Gotoh, Akiko Takeda, Rei Yamamoto:
Interaction between financial risk measures and machine learning methods. Comput. Manag. Sci. 11(4): 365-402 (2014) - [j12]Yuichi Takano, Jun-ya Gotoh:
Multi-period portfolio selection using kernel-based control policy with dimensionality reduction. Expert Syst. Appl. 41(8): 3901-3914 (2014) - 2013
- [j11]Akiko Takeda, Mahesan Niranjan
Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios. Comput. Manag. Sci. 10(1): 21-49 (2013) - 2012
- [j10]Jun-ya Gotoh, Akiko Takeda:
Minimizing loss probability bounds for portfolio selection. Eur. J. Oper. Res. 217(2): 371-380 (2012) - 2011
- [j9]Jun-ya Gotoh, Akiko Takeda:
On the role of norm constraints in portfolio selection. Comput. Manag. Sci. 8(4): 323 (2011) - [j8]Jun-ya Gotoh, Yoshitsugu Yamamoto, Weifeng Yao:
Bounding Contingent Claim Prices via Hedging Strategy with Coherent Risk Measures. J. Optim. Theory Appl. 151(3): 613-632 (2011) - 2010
- [j7]Yuichi Takano, Jun-ya Gotoh:
α-Conservative approximation for probabilistically constrained convex programs. Comput. Optim. Appl. 46(1): 113-133 (2010)
2000 – 2009
- 2008
- [j6]Jun-ya Gotoh, Akiko Takeda:
Conditional minimum volume ellipsoid with application to multiclass discrimination. Comput. Optim. Appl. 41(1): 27-51 (2008) - 2007
- [j5]Jun-ya Gotoh, Yuichi Takano:
Newsvendor solutions via conditional value-at-risk minimization. Eur. J. Oper. Res. 179(1): 80-96 (2007) - 2006
- [j4]Jun-ya Gotoh, Hiroshi Konno:
Minimal Ellipsoid Circumscribing a Polytope Defined by a System of Linear Inequalities. J. Glob. Optim. 34(1): 1-14 (2006) - 2003
- [j3]Jun-ya Gotoh, Nguyen Van Thoai, Yoshitsugu Yamamoto:
Global optimization method for solving the minimum maximal flow problem. Optim. Methods Softw. 18(4): 395-415 (2003) - 2002
- [j2]Jun-ya Gotoh, Hiroshi Konno:
Bounding Option Prices by Semidefinite Programming: A Cutting Plane Algorithm. Manag. Sci. 48(5): 665-678 (2002) - 2001
- [j1]Jun-ya Gotoh, Hiroshi Konno:
Maximization of the Ratio of Two Convex Quadratic Functions over a Polytope. Comput. Optim. Appl. 20(1): 43-60 (2001)
Coauthor Index
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