Katya Scheinberg

79 papers A* 4Misc 3Journal 62Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Editor's Comments on the 50th Anniversary of Math. Oper. Res. Katya Scheinberg
2025	J	`jnl`	High Probability Complexity Bounds of Trust-Region Stochastic Sequential Quadratic Programming with Heavy-Tailed Noise. CoRR Yuchen Fang, Javad Lavaei, Katya Scheinberg, Sen Na
2025	J	`jnl`	Sample complexity analysis for adaptive optimization algorithms with stochastic oracles. Math. Program. Billy Jin, Katya Scheinberg, Miaolan Xie
2025	J	`jnl`	Stochastic ISTA/FISTA Adaptive Step Search Algorithms for Convex Composite Optimization. J. Optim. Theory Appl. Lam M. Nguyen, Katya Scheinberg, Trang H. Tran
2024	J	`jnl`	First- and second-order high probability complexity bounds for trust-region methods with noisy oracles. Math. Program. Liyuan Cao, Albert S. Berahas, Katya Scheinberg
2024	J	`jnl`	High Probability Complexity Bounds for Adaptive Step Search Based on Stochastic Oracles. SIAM J. Optim. Billy Jin, Katya Scheinberg, Miaolan Xie
2023	Misc	`conf`	Stochastic Adaptive Regularization Method with Cubics: a High Probability Complexity Bound. WSC Katya Scheinberg, Miaolan Xie
2022	J	`jnl`	A Theoretical and Empirical Comparison of Gradient Approximations in Derivative-Free Optimization. Found. Comput. Math. Albert S. Berahas, Liyuan Cao, Krzysztof Choromanski, Katya Scheinberg
2022	J	`jnl`	Finding Optimal Policy for Queueing Models: New Parameterization. CoRR Trang H. Tran, Lam M. Nguyen, Katya Scheinberg
2022	J	`jnl`	Finite Difference Gradient Approximation: To Randomize or Not? INFORMS J. Comput. Katya Scheinberg
2022	A*	`conf`	Nesterov Accelerated Shuffling Gradient Method for Convex Optimization. ICML Trang H. Tran, Katya Scheinberg, Lam M. Nguyen
2022	J	`jnl`	Nesterov Accelerated Shuffling Gradient Method for Convex Optimization. CoRR Trang H. Tran, Lam M. Nguyen, Katya Scheinberg
2021	J	`jnl`	Global Convergence Rate Analysis of a Generic Line Search Algorithm with Noise. SIAM J. Optim. Albert S. Berahas, Liyuan Cao, Katya Scheinberg
2021	A*	`conf`	High Probability Complexity Bounds for Line Search Based on Stochastic Oracles. NeurIPS Billy Jin, Katya Scheinberg, Miaolan Xie
2021	J	`jnl`	Inexact SARAH algorithm for stochastic optimization. Optim. Methods Softw. Lam M. Nguyen, Katya Scheinberg, Martin Takác
2021	J	`jnl`	Optimal decision trees for categorical data via integer programming. J. Glob. Optim. Oktay Günlük, Jayant Kalagnanam, Minhan Li, Matt Menickelly, Katya Scheinberg
2020	J	`jnl`	A Stochastic Line Search Method with Expected Complexity Analysis. SIAM J. Optim. Courtney Paquette, Katya Scheinberg
2020	J	`jnl`	Adaptive Stochastic Optimization. CoRR Frank E. Curtis, Katya Scheinberg
2020	J	`jnl`	Adaptive Stochastic Optimization: A Framework for Analyzing Stochastic Optimization Algorithms. IEEE Signal Process. Mag. Frank E. Curtis, Katya Scheinberg
2019	J	`jnl`	A Novel Smoothed Loss and Penalty Function for Noncrossing Composite Quantile Estimation via Deep Neural Networks. CoRR Kostas Hatalis, Alberto J. Lamadrid, Katya Scheinberg, Shalinee Kishore
2019	J	`jnl`	A Stochastic Trust Region Algorithm Based on Careful Step Normalization. INFORMS J. Optim. Frank E. Curtis, Katya Scheinberg, Rui Shi
2019	J	`jnl`	Convergence Rate Analysis of a Stochastic Trust-Region Method via Supermartingales. INFORMS J. Optim. Jose H. Blanchet, Coralia Cartis, Matt Menickelly, Katya Scheinberg
2019	J	`jnl`	Feature Engineering and Forecasting via Integration of Derivative-free Optimization and Ensemble of Sequence-to-sequence Networks: Renewable Energy Case Studies. CoRR Mohammad Pirhooshyaran, Lawrence V. Snyder, Katya Scheinberg
2019	J	`jnl`	New Convergence Aspects of Stochastic Gradient Algorithms. J. Mach. Learn. Res. Lam M. Nguyen, Phuong Ha Nguyen, Peter Richtárik, Katya Scheinberg, Martin Takác, Marten van Dijk
2019	J	`jnl`	Novel and Efficient Approximations for Zero-One Loss of Linear Classifiers. CoRR Hiva Ghanbari, Minhan Li, Katya Scheinberg
2018	J	`jnl`	An Empirical Analysis of Constrained Support Vector Quantile Regression for Nonparametric Probabilistic Forecasting of Wind Power. CoRR Kostas Hatalis, Shalinee Kishore, Katya Scheinberg, Alberto J. Lamadrid
2018	J	`jnl`	Directly and Efficiently Optimizing Prediction Error and AUC of Linear Classifiers. CoRR Hiva Ghanbari, Katya Scheinberg
2018	J	`jnl`	Global convergence rate analysis of unconstrained optimization methods based on probabilistic models. Math. Program. Coralia Cartis, Katya Scheinberg
2018	J	`jnl`	Inexact SARAH Algorithm for Stochastic Optimization. CoRR Lam M. Nguyen, Katya Scheinberg, Martin Takác
2018	J	`jnl`	New Convergence Aspects of Stochastic Gradient Algorithms. CoRR Lam M. Nguyen, Phuong Ha Nguyen, Peter Richtárik, Katya Scheinberg, Martin Takác, Marten van Dijk
2018	J	`jnl`	Proximal quasi-Newton methods for regularized convex optimization with linear and accelerated sublinear convergence rates. Comput. Optim. Appl. Hiva Ghanbari, Katya Scheinberg
2018	A*	`conf`	SGD and Hogwild! Convergence Without the Bounded Gradients Assumption. ICML Lam M. Nguyen, Phuong Ha Nguyen, Marten van Dijk, Peter Richtárik, Katya Scheinberg, Martin Takác
2018	J	`jnl`	SGD and Hogwild! Convergence Without the Bounded Gradients Assumption. CoRR Lam M. Nguyen, Phuong Ha Nguyen, Marten van Dijk, Peter Richtárik, Katya Scheinberg, Martin Takác
2018	J	`jnl`	Stochastic optimization using a trust-region method and random models. Math. Program. Ruobing Chen, Matt Menickelly, Katya Scheinberg
2018	J	`jnl`	When Does Stochastic Gradient Algorithm Work Well? CoRR Lam M. Nguyen, Nam H. Nguyen, Dzung T. Phan, Jayant R. Kalagnanam, Katya Scheinberg
2017	—	`conf`	A Novel l0-Constrained Gaussian Graphical Model for Anomaly Localization. ICDM Workshops Dzung T. Phan, Tsuyoshi Idé, Jayant Kalagnanam, Matt Menickelly, Katya Scheinberg
2017	—	`conf`	An Empirical Analysis of Constrained Support Vector Quantile Regression for Nonparametric Probabilistic Forecasting of Wind Power. AAAI Workshops Kostas Hatalis, Shalinee Kishore, Katya Scheinberg, Alberto J. Lamadrid
2017	J	`jnl`	Black-Box Optimization in Machine Learning with Trust Region Based Derivative Free Algorithm. CoRR Hiva Ghanbari, Katya Scheinberg
2017	J	`jnl`	On the construction of quadratic models for derivative-free trust-region algorithms. EURO J. Comput. Optim. Adriano Verdério, Elizabeth W. Karas, Lucas G. Pedroso, Katya Scheinberg
2017	J	`jnl`	Optimization Methods for Supervised Machine Learning: From Linear Models to Deep Learning. CoRR Frank E. Curtis, Katya Scheinberg
2017	A*	`conf`	SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient. ICML Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takác
2017	J	`jnl`	SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient. CoRR Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takác
2017	J	`jnl`	Stochastic Recursive Gradient Algorithm for Nonconvex Optimization. CoRR Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takác
2016	J	`jnl`	Optimal Generalized Decision Trees via Integer Programming. CoRR Matt Menickelly, Oktay Günlük, Jayant Kalagnanam, Katya Scheinberg
2016	J	`jnl`	Practical inexact proximal quasi-Newton method with global complexity analysis. Math. Program. Katya Scheinberg, Xiaocheng Tang
2016	J	`jnl`	Proximal Quasi-Newton Methods for Convex Optimization. CoRR Hiva Ghanbari, Katya Scheinberg
2015	—	`conf`	A scalable solution for group feature selection. IEEE BigData Priya Govindan, Ruobing Chen, Katya Scheinberg, Soundararajan Srinivasan
2015	—	`conf`	Superposition of protein structures using electrostatic isopotentials. BIBM Ziyi Guo, Katya Scheinberg, Juliana Hong, Brian Yuan Chen
2014	J	`jnl`	Convergence of Trust-Region Methods Based on Probabilistic Models. SIAM J. Optim. Afonso S. Bandeira, Katya Scheinberg, Luís Nunes Vicente
2014	J	`jnl`	Fast First-Order Methods for Composite Convex Optimization with Backtracking. Found. Comput. Math. Katya Scheinberg, Donald Goldfarb, Xi Bai
2013	J	`jnl`	Complexity of Inexact Proximal Newton methods. CoRR Katya Scheinberg, Xiaocheng Tang
2013	J	`jnl`	Efficient block-coordinate descent algorithms for the Group Lasso. Math. Program. Comput. Zhiwei (Tony) Qin, Katya Scheinberg, Donald Goldfarb
2013	J	`jnl`	Efficiently Using Second Order Information in Large l1 Regularization Problems CoRR Xiaocheng Tang, Katya Scheinberg
2013	J	`jnl`	Fast alternating linearization methods for minimizing the sum of two convex functions. Math. Program. Donald Goldfarb, Shiqian Ma, Katya Scheinberg
2013	J	`jnl`	On partial sparse recovery CoRR Afonso S. Bandeira, Katya Scheinberg, Luís Nunes Vicente
2012	—	`conf`	Aligning ligand binding cavities by optimizing superposed volume. BIBM Ruobing Chen, Katya Scheinberg, Brian Yuan Chen
2012	J	`jnl`	Computation of sparse low degree interpolating polynomials and their application to derivative-free optimization. Math. Program. Afonso S. Bandeira, Katya Scheinberg, Luís Nunes Vicente
2010	J	`jnl`	A Derivative-Free Algorithm for Least-Squares Minimization. SIAM J. Optim. Hongchao Zhang, Andrew R. Conn, Katya Scheinberg
2010	—	`conf`	Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach. ECML/PKDD (3) Katya Scheinberg, Irina Rish
2010	J	`jnl`	Self-Correcting Geometry in Model-Based Algorithms for Derivative-Free Unconstrained Optimization. SIAM J. Optim. Katya Scheinberg, Philippe L. Toint
2010	J	`jnl`	Sparse Inverse Covariance Selection via Alternating Linearization Methods CoRR Katya Scheinberg, Shiqian Ma, Donald Goldfarb
2010	—	`conf`	Sparse Inverse Covariance Selection via Alternating Linearization Methods. NIPS Katya Scheinberg, Shiqian Ma, Donald Goldfarb
2010	Misc	`conf`	Sparse Markov net learning with priors on regularization parameters. ISAIM Katya Scheinberg, Irina Rish, Narges Bani Asadi
2009	J	`jnl`	Fast Alternating Linearization Methods for Minimizing the Sum of Two Convex Functions. CoRR Donald Goldfarb, Shiqian Ma, Katya Scheinberg
2009	J	`jnl`	Global Convergence of General Derivative-Free Trust-Region Algorithms to First- and Second-Order Critical Points. SIAM J. Optim. Andrew R. Conn, Katya Scheinberg, Luís Nunes Vicente
2009	—	`book`	Introduction to Derivative-Free Optimization. Andrew R. Conn, Katya Scheinberg, Luís Nunes Vicente
2009	Misc	`conf`	Map approach to learning sparse Gaussian Markov networks. ICASSP Narges Bani Asadi, Irina Rish, Katya Scheinberg, Dimitri Kanevsky, Bhuvana Ramabhadran
2008	J	`jnl`	Geometry of interpolation sets in derivative free optimization. Math. Program. Andrew R. Conn, Katya Scheinberg, Luís Nunes Vicente
2008	J	`jnl`	PREFACESpecial section on mathematical programming in data mining and machine learning. Optim. Methods Softw. Katya Scheinberg, Jiming Peng
2006	J	`jnl`	An Efficient Implementation of an Active Set Method for SVMs. J. Mach. Learn. Res. Katya Scheinberg
2006	—	`conf`	IBM Research TRECVID-2006 Video Retrieval System. TRECVID Murray Campbell, Alexander Haubold, Shahram Ebadollahi, Dhiraj Joshi, Milind R. Naphade, Apostol Natsev, Joachim Seidl, John R. Smith, Katya Scheinberg, Jelena Tesic, Lexing Xie
2005	J	`jnl`	Product-form Cholesky factorization in interior point methods for second-order cone programming. Math. Program. Donald Goldfarb, Katya Scheinberg
2004	J	`jnl`	A product-form Cholesky factorization method for handling dense columns in interior point methods for linear programming. Math. Program. Donald Goldfarb, Katya Scheinberg
2001	J	`jnl`	Efficient SVM Training Using Low-Rank Kernel Representations. J. Mach. Learn. Res. Shai Fine, Katya Scheinberg
2001	—	`conf`	Incremental Learning and Selective Sampling via Parametric Optimization Framework for SVM. NIPS Shai Fine, Katya Scheinberg
1999	J	`jnl`	A Modified Barrier-Augmented Lagrangian Method for Constrained Minimization. Comput. Optim. Appl. Donald Goldfarb, R. Polyak, Katya Scheinberg, I. Yuzefovich
1998	J	`jnl`	Interior Point Trajectories in Semidefinite Programming. SIAM J. Optim. Donald Goldfarb, Katya Scheinberg
1997	J	`jnl`	Recent progress in unconstrained nonlinear optimization without derivatives. Math. Program. Andrew R. Conn, Katya Scheinberg, Philippe L. Toint
1996	J	`jnl`	Extension of Karmarkar's algorithm onto convex quadratically constrained quadratic problems. Math. Program. Arkadii Nemirovskii, Katya Scheinberg