Research Activities (Papers)
Refereed Journals

T. Kanamori, S. Fujiwara, A. Takeda,
" Breakdown Point of Robust Support Vector Machine",
accepted by Entropy, 2017.

S. Fujiwara, A. Takeda, T. Kanamori,
"DC Algorithm for Extended Robust Support Vector Machine", accepted by Neural Computation, 2017.

N. Ito, A. Takeda and K.C. Toh,
"A Unified Formulation and Fast Accelerated Proximal Gradient Method for Classification", accepted by Journal of Machine Learning Research, 2016.

S. Sakaue, A. Takeda, S. Kim and N. Ito,
"Exact SDP Relaxations with Truncated Moment Matrix for Binary Polynomial Optimization Problems", accepted by SIAM Journal on Optimization, 2016.

S. Adachi, S. Iwata, Y. Nakatsukasa and A. Takeda,
"Solving the Trust Region Subproblem by a Generalized Eigenvalue Problem", accepted by SIAM Journal on Optimization, 2016.

S. Sakaue, Y. Nakatsukasa, A. Takeda and S. Iwata,
"Solving generalized CDT problems via twoparameter eigenvalues", SIAM Journal on Optimization, 26 (3), pp.16691694 (2016). DOI:10.1137/15100624X

S. Iwata, Y. Nakatsukasa and A. Takeda,
"Computing the signed distance between overlapping ellipsoids", SIAM Journal on Optimization, 25 (4), pp.23592384 (2015). DOI: :10.1137/140979654

D. Bertsimas and A. Takeda,
"Optimizing Over Coherent Risk Measures and Nonconvexities: A Robust Mixed Integer Optimization Approach",
Computational Optimization and Applications 62 (3), pp.613639 (2015).
DOI: 10.1007/s1058901597553

Y. Gunawardana, S. Fujiwara, A. Takeda, J. Woo, C. Woelk, M. Niranjan,
"OutlierDetection at the TranscriptomeProteome Interface",
Bioinformatics, 31 (15), pp.25302536 (2015).
DOI: 10.1093/bioinformatics/btv182

Y. Yamaguchi, A. Ogawa, A. Takeda and S. Iwata,
"Cyber Security Analysis of Power Networks by Hypergraph Cut Algorithms",
The IEEE Transactions on Smart Grid, 6 (5), pp.21892199 (2015). DOI: 10.1109/TSG.2015.2394791

A. Barbero, A. Takeda and J. Lopez,
"Geometric intuition and algorithms for EnuSVM",
Journal of Machine Learning Research, 16, pp.323369 (2015).

A. Takeda and T. Kanamori,
"Using Financial Risk Measures for Analyzing Generalization Performance of Machine Learning Models",
Neural Networks , 57, pp.2938 (2014).
DOI: 10.1016/j.neunet.2014.05.006

A. Takeda, S. Fujiwara and T. Kanamori,
"Extended Robust Support Vector Machine Based on Financial Risk Minimization",
Neural Computation, 26 (11), pp.25412569 (2014). DOI: 10.1162/NECO_a_00647

T. Kanamori and A. Takeda,
"Numerical Study of Learning Algorithms on Stiefel Manifold",
Computational Management Science, 11 (4), pp.319340 (2014).
DOI: 10.1007/s1028701301817

J. Gotoh, A. Takeda and R. Yamamoto,
"Interactions between Financial Risk Measures and Machine Learning Methods",
Computational Management Science, 11 (4), pp.365402 (2014).
DOI: 10.1007/s1028701301755

T. Kanamori, A. Takeda and T. Suzuki,
"A Conjugate Property between Loss Functions and
Uncertainty Sets in Classification Problems",
Journal of
Machine Learning Research, 14, pp.1461−1504 (2013).

S. Okido and A. Takeda,
"
Economic and Environmental Analysis of Photovoltaic Energy Systems via
Robust Optimization",
Energy Systems, 4, pp.239266 (2013). DOI: 10.1007/s1266701300771
 J. Gotoh, K. Shinozaki and A. Takeda,
"Robust Portfolio Techniques for Mitigating the
Fragility of CVaR Minimization and Generalization to Coherent Risk Measures",
Quantitative Finance,
13 (10), pp.16211635 (2013). DOI: 10.1080/14697688.2012.738930
 A. Takeda, H. Mitsugi and T. Kanamori,
"A Unified Classification Model Based on Robust Optimization",
Neural Computation,
25 (3), pp.759804 (2013). DOI: 10.1162/NECO_a_00412

A. Takeda, M. Niranjan, J. Gotoh and Y. Kawahara,
"Simultaneous Pursuit of OutofSample Performance and Sparsity in
Index Tracking Portfolios",
Computational Management Science,
10 (1), pp.2149 (2013).
DOI: 10.1007/s102870120158y
 J. Gotoh and A. Takeda,
"Minimizing Loss Probability Bounds for Portfolio Selection",
European Journal of Operational
Research, 217 (2), pp.371380 (2012). DOI: 10.1016/j.ejor.2011.09.012
 T. Kanamori and A. Takeda,
"WorstCase Violation of Sampled Convex Programs for Optimization with Uncertainty",
Journal of Optimization Theory and
Applications, 152 (1), pp.171197 (2012).
DOI: 10.1007/s1095701199232
 J. Gotoh and A. Takeda,
"On the Role of Norm Constraints in Portfolio Selection",
Computational Management Science, 8 (4), pp.323353 (2011).
DOI: 10.1007/s1028701101302
 A. Takeda, S. Taguchi and T. Tanaka,
"A Relaxation Algorithm with a Probabilistic Guarantee for Robust
Deviation Optimization",
Computational Optimization and
Applications, 47 (1), pp.131 (2010).
DOI: 10.1007/s1058900892127
 A. Takeda and M. Sugiyama,
"On generalization performance and nonconvex optimization of
extended nusupport vector machine",
New Generation Computing, 27,
pp.259279 (2009).
DOI: 10.1007/s0035400800646

A. Takeda,
"Generalization Performance of nuSupport Vector Classifier Based on Conditional ValueatRisk Minimization",
Neurocomputing, 72 (1012), pp.23512358 (2009). DOI: 10.1016/j.neucom.2008.11.022

A. Takeda and T. Kanamori,
"A Robust Approach Based on Conditional ValueatRisk
Measure to Statistical Learning Problems",
European Journal of Operational Research, 198 (1), pp. 287296 (2009).
DOI: 10.1016/j.ejor.2008.07.027

J. Gotoh and A. Takeda,
"Conditional Minimum Volume Ellipsoid with Applications to Multiclass Discrimination",
Computational Optimization and Applications,
41 (1), pp.2751 (2008). DOI: 10.1007/s105890079097x

A. Takeda, S. Taguchi and R. Tutuncu,
"Adjustable Robust Optimization Models for a Nonlinear TwoPeriod
System",
Journal of Optimization Theory and Applications,
136 (2), pp.275295 (2008). DOI: 10.1007/s1095700792888

T. Mizutani, A. Takeda and M. Kojima,
"Dynamic Enumeration of All Mixed Cells",
Discrete and Computational Geometry, 37 (3), pp.351367 (2007).
DOI: 10.1007/s0045400613009

A. Takeda, N. Uchihira, M. Nakamoto and S. Matsumoto,
"An Electric Powerplant Planning Method for Uncertain Environments" (Japanese),
Journal of Japan Industrial Management Association, 56 (5), pp.366376 (2005).

J. Gotoh and A. Takeda,
"A linear Classification Model Based on Conditional Geometric Score",
Pacific Journal of Optimization, 1 (2),pp.277296 (2005).

K. Fujisawa, M. Kojima, A. Takeda and M. Yamashita,
"Solving Large Scale Optimization Problems via Grid and Cluster Computing".
Journal of the Operations Research Society of Japan, 47(4),pp.265274 (2004).
 T. Gunji, S. Kim, M. Kojima, A. Takeda, K. Fujisawa and T. Mizutani,
"PHoM  a Polyhedral Homotopy Continuation Method".
Computing, 73, pp.5777 (2004). DOI: 10.1007/s0060700300324

C. Vo, A. Takeda and M. Kojima,
"A Multilevel Parallelized Hybrid Branch and Bound Algorithm for Quadratic Optimization",
IPSJ Transactions on Advanced Computing Systems, 45 SIG 6(ACS 6), pp.186196 (2004).
 A. Takeda, K. Fujisawa, Y. Fukaya and M. Kojima,
"Parallel Implementation of Successive Convex Relaxation Methods for Quadratic Optimization Problems",
Journal of Global Optimization, 24 (2), pp.237260 (2002).
 A. Takeda, M. Kojima and K. Fujisawa,
"Enumeration of All Solutions of a Combinatorial linear Inequality System Arising from
the Polyhedral Homotopy Continuation Method",
Journal of the Operations Research Society of Japan,
45 (1), pp.6482 (2002).
 A. Takeda and H. Nishino,
"On Measuring the Inefficiency with the InnerProduct Norm in Date Envelopment Analysis",
European Journal of Operational Research, Vol.133 (2), pp.377393 (2001).
 M. Kojima and A. Takeda,
"Complexity Analysis of Successive Convex Relaxation Methods for
Nonconvex Sets",
Mathematics of Operations Research, 26 (3), pp.519542 (2001).
Refereed Book Chapters
 T. Mizutani and A. Takeda,
"DEMiCs: A software package for computing the mixed volume via dynamic enumeration of all mixed cells",
in M.E. Stillman, N. Takayama and J. Verschelde (Eds.),
IMA Volumes on "Software for algebraic geometry",
pp.5979 (2008).
 A. Takeda and M. Kojima,
"Successive
Convex Relaxation Approach to Bilevel Quadratic Optimization
Problems",
in M. C. Ferris, O. L. Mangasarian and J.S. Pang (Eds.),
Applications and Algorithms of Complementarity,
Kluwer Academic Publishers, p.317p.340 (2001).
 A. Takeda, Y. Dai, M. Fukuda, and M. Kojima,
"Towards the Implementation of Successive Convex Relaxation
Method for Nonconvex Quadratic
Optimization Problems",
in P.M. Pardalos (Ed.),
Approximation and Complexity in Numerical Optimization:
Continuous and Discrete Problems, Kluwer Academic
Publishers, p.489p.510 (2000).
Refereed Conference Proceedings

S. Katsumata and A. Takeda,
"Robust Cost Sensitive Support Vector Machine",
accepted by the 18th International Conference on Artificial Intelligence and Statistics (AISTATS), 2015.

A. Alrajeh, A. Takeda, M. Niranjan,
"MemoryEfficient LargeScale Linear Support Vector Machine",
The 7th International Conference on Machine Vision (ICMV 2014),
2014.

Y. Gunawardana, S. Fujiwara, A. Takeda, C. Woelk and M. Niranjan,
"OutlierDetecting Support Vector Regression for Modelling at the TranscriptomeProteome Interface",
Eighth International Workshop on Machine Learning in Systems Biology
(MLSB 2014), 2014.

Y. Yamaguchi, A. Ogawa, A. Takeda, S. Iwata,
"Cyber Security Analysis of Power Networks by Hypergraph Cut Algorithms",
IEEE SmartGridComm 2014 Symposium, 2014.

M. Kitamura, A. Takeda, S. Iwata,
"Exact SVM Training by Wolfe's Minimum Norm Point Algorithm",
Proceedings of 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2014), 2014.

S. Iwata, Y. Nakatsukasa, A. Takeda,
"Global Optimization Methods for Extended Fisher Discriminant Analysis",
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics (AISTAT), 2014.

A. Ogawa, A. Takeda and T. Namerikawa,
"Photovoltaic Output Prediction Using Autoregression with Support Vector Machine",
NIPS 2013 workshop on Machine Learning for Sustainability, 2013.

S. Nakajima, A. Takeda, S. D. Babacan, M. Sugiyama and I. Takeuchi,
"Global Solver and Its Efficient Approximation for Variational Bayesian Lowrank Subspace Clustering",
The Neural Information Processing Systems (NIPS2013), 2013.

N. Ito, A. Takeda and T. Namerikawa,
"Convex Hull Pricing for Demand Response in Electricity Markets",
IEEE SmartGridComm 2013 Symposium, 2013. DOI: 10.1109/SmartGridComm.2013.6687949

T. Kanamori and A. Takeda,
"NonConvex Optimization on Stiefel Manifold and Applications to Machine Learning",
The International Conference on Neural Information Processing
(ICONIP2012), 2012.

A. Takeda, H. Mitsugi and T. Kanamori,
"A unified robust classification model",
29th International Conference on Machine Learning (ICML2012), 2012.

T. Kanamori, A. Takeda and T. Suzuki,
"A conjugate property between loss functions and uncertainty sets in classification problems",
Conference on Learning Theory (COLT2012), 2012.

A. Takeda, J. Gotoh and M. Sugiyama,
``Support Vector Regression as Conditional ValueatRisk Minimization with Application to Financial Timeseries Analysis'',
Proceedings of 2010 IEEE International Workshop on
Machine Learning for Signal Processing (MLSP 2010), Kittila, Finland,
2010.

A. Takeda and M. Sugiyama,
"NuSupport Vector Machine as Conditional ValueatRisk Minimization",
Proceedings of the 25th International Conference on Machine
Learning (ICML 2008), Helsinki, Finland, 2008. [paper]

A. Takeda,
"A Modified Algorithm for Nonconvex Support Vector Classification",
Proceedings of the
International Conference on Artificial Intelligence and Applications
(AIA 2008), Innsbruck, Austria, 2008.
 K. Fujisawa, M. Kojima, A. Takeda and M. Yamashita,
"High Performance Grid and Cluster Computing for Some
Optimization Problems",
2004 Symposium on Applications and the Internet (SAINT 2004
Workshops), pp.612615 (2004).
Submitted Articles

J. Gotoh, A. Takeda and K. Tono,
"DC Formulations and Algorithms for Sparse Optimization Problems", 2015.

K. Tono, A. Takeda and J. Gotoh,
"Efficient DC Algorithm for Constrained Sparse Optimization", 2017.
Doctor Thesis

"Successive Convex Relaxation Methods for Nonconvex Quadratic
Optimization Problems"
(PDF file,
PS file), Doctor Thesis, March 2001.
Abstract