Katya Scheinberg
Orcid: 0000-0003-3547-1841
According to our database1,
Katya Scheinberg
authored at least 67 papers
between 1996 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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on zbmath.org
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on orcid.org
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on id.loc.gov
On csauthors.net:
Bibliography
2024
First- and second-order high probability complexity bounds for trust-region methods with noisy oracles.
Math. Program., September, 2024
High Probability Complexity Bounds for Adaptive Step Search Based on Stochastic Oracles.
SIAM J. Optim., 2024
2023
Stochastic Adaptive Regularization Method with Cubics: a High Probability Complexity Bound.
Proceedings of the Winter Simulation Conference, 2023
2022
INFORMS J. Comput., 2022
A Theoretical and Empirical Comparison of Gradient Approximations in Derivative-Free Optimization.
Found. Comput. Math., 2022
Proceedings of the International Conference on Machine Learning, 2022
2021
SIAM J. Optim., 2021
J. Glob. Optim., 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
2020
Adaptive Stochastic Optimization: A Framework for Analyzing Stochastic Optimization Algorithms.
IEEE Signal Process. Mag., 2020
SIAM J. Optim., 2020
2019
INFORMS J. Optim., July, 2019
INFORMS J. Optim., April, 2019
J. Mach. Learn. Res., 2019
A Novel Smoothed Loss and Penalty Function for Noncrossing Composite Quantile Estimation via Deep Neural Networks.
CoRR, 2019
Feature Engineering and Forecasting via Integration of Derivative-free Optimization and Ensemble of Sequence-to-sequence Networks: Renewable Energy Case Studies.
CoRR, 2019
CoRR, 2019
2018
Math. Program., 2018
Global convergence rate analysis of unconstrained optimization methods based on probabilistic models.
Math. Program., 2018
CoRR, 2018
Proximal quasi-Newton methods for regularized convex optimization with linear and accelerated sublinear convergence rates.
Comput. Optim. Appl., 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
2017
EURO J. Comput. Optim., 2017
Black-Box Optimization in Machine Learning with Trust Region Based Derivative Free Algorithm.
CoRR, 2017
Optimization Methods for Supervised Machine Learning: From Linear Models to Deep Learning.
CoRR, 2017
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient.
Proceedings of the 34th International Conference on Machine Learning, 2017
Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017
An Empirical Analysis of Constrained Support Vector Quantile Regression for Nonparametric Probabilistic Forecasting of Wind Power.
Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017
2016
Math. Program., 2016
2015
Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015
Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine, 2015
2014
SIAM J. Optim., 2014
Found. Comput. Math., 2014
2013
Math. Program. Comput., 2013
Fast alternating linearization methods for minimizing the sum of two convex functions.
Math. Program., 2013
CoRR, 2013
2012
Computation of sparse low degree interpolating polynomials and their application to derivative-free optimization.
Math. Program., 2012
Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine, 2012
2010
Self-Correcting Geometry in Model-Based Algorithms for Derivative-Free Unconstrained Optimization.
SIAM J. Optim., 2010
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2010
2009
Global Convergence of General Derivative-Free Trust-Region Algorithms to First- and Second-Order Critical Points.
SIAM J. Optim., 2009
Proceedings of the IEEE International Conference on Acoustics, 2009
Introduction to Derivative-Free Optimization.
MPS-SIAM series on optimization 8, SIAM, ISBN: 978-0-89871-668-9, 2009
2008
PREFACESpecial section on mathematical programming in data mining and machine learning.
Optim. Methods Softw., 2008
2006
J. Mach. Learn. Res., 2006
Proceedings of the 2006 TREC Video Retrieval Evaluation, 2006
2005
Product-form Cholesky factorization in interior point methods for second-order cone programming.
Math. Program., 2005
2004
A product-form Cholesky factorization method for handling dense columns in interior point methods for linear programming.
Math. Program., 2004
2001
J. Mach. Learn. Res., 2001
Incremental Learning and Selective Sampling via Parametric Optimization Framework for SVM.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001
1999
Comput. Optim. Appl., 1999
1998
1997
Math. Program., 1997
1996
Extension of Karmarkar's algorithm onto convex quadratically constrained quadratic problems.
Math. Program., 1996