Katya Scheinberg

Publication Activity (10 Years)

Years Active: 1996-2024
Publications (10 Years): 44

Top Topics

Optimization Methods

Integer Programming

Convex Optimization

Top Venues

Publications

Liyuan Cao, Albert S. Berahas, Katya Scheinberg
First- and second-order high probability complexity bounds for trust-region methods with noisy oracles. Math. Program. 207 (1) (2024)
Billy Jin, Katya Scheinberg, Miaolan Xie
High Probability Complexity Bounds for Adaptive Step Search Based on Stochastic Oracles. SIAM J. Optim. 34 (3) (2024)
Katya Scheinberg, Miaolan Xie
Stochastic Adaptive Regularization Method with Cubics: a High Probability Complexity Bound. WSC (2023)
Albert S. Berahas, Liyuan Cao, Krzysztof Choromanski, Katya Scheinberg
A Theoretical and Empirical Comparison of Gradient Approximations in Derivative-Free Optimization. Found. Comput. Math. 22 (2) (2022)
Trang H. Tran, Lam M. Nguyen, Katya Scheinberg
Nesterov Accelerated Shuffling Gradient Method for Convex Optimization. CoRR (2022)
Trang H. Tran, Katya Scheinberg, Lam M. Nguyen
Nesterov Accelerated Shuffling Gradient Method for Convex Optimization. ICML (2022)
Trang H. Tran, Lam M. Nguyen, Katya Scheinberg
Finding Optimal Policy for Queueing Models: New Parameterization. CoRR (2022)
Katya Scheinberg
Finite Difference Gradient Approximation: To Randomize or Not? INFORMS J. Comput. 34 (5) (2022)
Lam M. Nguyen, Katya Scheinberg, Martin Takác
Inexact SARAH algorithm for stochastic optimization. Optim. Methods Softw. 36 (1) (2021)
Albert S. Berahas, Liyuan Cao, Katya Scheinberg
Global Convergence Rate Analysis of a Generic Line Search Algorithm with Noise. SIAM J. Optim. 31 (2) (2021)
Oktay Günlük, Jayant Kalagnanam, Minhan Li, Matt Menickelly, Katya Scheinberg
Optimal decision trees for categorical data via integer programming. J. Glob. Optim. 81 (1) (2021)
Billy Jin, Katya Scheinberg, Miaolan Xie
High Probability Complexity Bounds for Line Search Based on Stochastic Oracles. NeurIPS (2021)
Frank E. Curtis, Katya Scheinberg
Adaptive Stochastic Optimization: A Framework for Analyzing Stochastic Optimization Algorithms. IEEE Signal Process. Mag. 37 (5) (2020)
Frank E. Curtis, Katya Scheinberg
Adaptive Stochastic Optimization. CoRR (2020)
Courtney Paquette, Katya Scheinberg
A Stochastic Line Search Method with Expected Complexity Analysis. SIAM J. Optim. 30 (1) (2020)
Mohammad Pirhooshyaran, Lawrence V. Snyder, Katya Scheinberg
Feature Engineering and Forecasting via Integration of Derivative-free Optimization and Ensemble of Sequence-to-sequence Networks: Renewable Energy Case Studies. CoRR (2019)
Frank E. Curtis, Katya Scheinberg, Rui Shi
A Stochastic Trust Region Algorithm Based on Careful Step Normalization. INFORMS J. Optim. 1 (3) (2019)
Hiva Ghanbari, Minhan Li, Katya Scheinberg
Novel and Efficient Approximations for Zero-One Loss of Linear Classifiers. CoRR (2019)
Jose H. Blanchet, Coralia Cartis, Matt Menickelly, Katya Scheinberg
Convergence Rate Analysis of a Stochastic Trust-Region Method via Supermartingales. INFORMS J. Optim. 1 (2) (2019)
Kostas Hatalis, Alberto J. Lamadrid, Katya Scheinberg, Shalinee Kishore
A Novel Smoothed Loss and Penalty Function for Noncrossing Composite Quantile Estimation via Deep Neural Networks. CoRR (2019)
Lam M. Nguyen, Phuong Ha Nguyen, Peter Richtárik, Katya Scheinberg, Martin Takác, Marten van Dijk
New Convergence Aspects of Stochastic Gradient Algorithms. J. Mach. Learn. Res. 20 (2019)
Ruobing Chen, Matt Menickelly, Katya Scheinberg
Stochastic optimization using a trust-region method and random models. Math. Program. 169 (2) (2018)
Coralia Cartis, Katya Scheinberg
Global convergence rate analysis of unconstrained optimization methods based on probabilistic models. Math. Program. 169 (2) (2018)
Hiva Ghanbari, Katya Scheinberg
Directly and Efficiently Optimizing Prediction Error and AUC of Linear Classifiers. CoRR (2018)
Lam M. Nguyen, Nam H. Nguyen, Dzung T. Phan, Jayant R. Kalagnanam, Katya Scheinberg
When Does Stochastic Gradient Algorithm Work Well? CoRR (2018)
Lam M. Nguyen, Phuong Ha Nguyen, Marten van Dijk, Peter Richtárik, Katya Scheinberg, Martin Takác
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption. CoRR (2018)
Hiva Ghanbari, Katya Scheinberg
Proximal quasi-Newton methods for regularized convex optimization with linear and accelerated sublinear convergence rates. Comput. Optim. Appl. 69 (3) (2018)
Kostas Hatalis, Shalinee Kishore, Katya Scheinberg, Alberto J. Lamadrid
An Empirical Analysis of Constrained Support Vector Quantile Regression for Nonparametric Probabilistic Forecasting of Wind Power. CoRR (2018)
Lam M. Nguyen, Phuong Ha Nguyen, Peter Richtárik, Katya Scheinberg, Martin Takác, Marten van Dijk
New Convergence Aspects of Stochastic Gradient Algorithms. CoRR (2018)
Lam M. Nguyen, Phuong Ha Nguyen, Marten van Dijk, Peter Richtárik, Katya Scheinberg, Martin Takác
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption. ICML (2018)
Lam M. Nguyen, Katya Scheinberg, Martin Takác
Inexact SARAH Algorithm for Stochastic Optimization. CoRR (2018)
Frank E. Curtis, Katya Scheinberg
Optimization Methods for Supervised Machine Learning: From Linear Models to Deep Learning. CoRR (2017)
Dzung T. Phan, Tsuyoshi Idé, Jayant Kalagnanam, Matt Menickelly, Katya Scheinberg
A Novel l0-Constrained Gaussian Graphical Model for Anomaly Localization. ICDM Workshops (2017)
Adriano Verdério, Elizabeth W. Karas, Lucas G. Pedroso, Katya Scheinberg
On the construction of quadratic models for derivative-free trust-region algorithms. EURO J. Comput. Optim. 5 (4) (2017)
Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takác
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient. CoRR (2017)
Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takác
Stochastic Recursive Gradient Algorithm for Nonconvex Optimization. CoRR (2017)
Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takác
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient. ICML (2017)
Hiva Ghanbari, Katya Scheinberg
Black-Box Optimization in Machine Learning with Trust Region Based Derivative Free Algorithm. CoRR (2017)
Kostas Hatalis, Shalinee Kishore, Katya Scheinberg, Alberto J. Lamadrid
An Empirical Analysis of Constrained Support Vector Quantile Regression for Nonparametric Probabilistic Forecasting of Wind Power. AAAI Workshops (2017)
Matt Menickelly, Oktay Günlük, Jayant Kalagnanam, Katya Scheinberg
Optimal Generalized Decision Trees via Integer Programming. CoRR (2016)
Katya Scheinberg, Xiaocheng Tang
Practical inexact proximal quasi-Newton method with global complexity analysis. Math. Program. 160 (1-2) (2016)
Hiva Ghanbari, Katya Scheinberg
Proximal Quasi-Newton Methods for Convex Optimization. CoRR (2016)
Priya Govindan, Ruobing Chen, Katya Scheinberg, Soundararajan Srinivasan
A scalable solution for group feature selection. IEEE BigData (2015)
Ziyi Guo, Katya Scheinberg, Juliana Hong, Brian Yuan Chen
Superposition of protein structures using electrostatic isopotentials. BIBM (2015)
Katya Scheinberg, Donald Goldfarb, Xi Bai
Fast First-Order Methods for Composite Convex Optimization with Backtracking. Found. Comput. Math. 14 (3) (2014)
Afonso S. Bandeira, Katya Scheinberg, Luís Nunes Vicente
Convergence of Trust-Region Methods Based on Probabilistic Models. SIAM J. Optim. 24 (3) (2014)
Katya Scheinberg, Xiaocheng Tang
Complexity of Inexact Proximal Newton methods. CoRR (2013)
Donald Goldfarb, Shiqian Ma, Katya Scheinberg
Fast alternating linearization methods for minimizing the sum of two convex functions. Math. Program. 141 (1-2) (2013)
Afonso S. Bandeira, Katya Scheinberg, Luís Nunes Vicente
On partial sparse recovery CoRR (2013)
Xiaocheng Tang, Katya Scheinberg
Efficiently Using Second Order Information in Large l1 Regularization Problems CoRR (2013)
Zhiwei (Tony) Qin, Katya Scheinberg, Donald Goldfarb
Efficient block-coordinate descent algorithms for the Group Lasso. Math. Program. Comput. 5 (2) (2013)
Ruobing Chen, Katya Scheinberg, Brian Yuan Chen
Aligning ligand binding cavities by optimizing superposed volume. BIBM (2012)
Afonso S. Bandeira, Katya Scheinberg, Luís Nunes Vicente
Computation of sparse low degree interpolating polynomials and their application to derivative-free optimization. Math. Program. 134 (1) (2012)
Katya Scheinberg, Irina Rish, Narges Bani Asadi
Sparse Markov net learning with priors on regularization parameters. ISAIM (2010)
Hongchao Zhang, Andrew R. Conn, Katya Scheinberg
A Derivative-Free Algorithm for Least-Squares Minimization. SIAM J. Optim. 20 (6) (2010)
Katya Scheinberg, Philippe L. Toint
Self-Correcting Geometry in Model-Based Algorithms for Derivative-Free Unconstrained Optimization. SIAM J. Optim. 20 (6) (2010)
Katya Scheinberg, Irina Rish
Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach. ECML/PKDD (3) (2010)
Katya Scheinberg, Shiqian Ma, Donald Goldfarb
Sparse Inverse Covariance Selection via Alternating Linearization Methods CoRR (2010)
Katya Scheinberg, Shiqian Ma, Donald Goldfarb
Sparse Inverse Covariance Selection via Alternating Linearization Methods. NIPS (2010)
Andrew R. Conn, Katya Scheinberg, Luís Nunes Vicente
Global Convergence of General Derivative-Free Trust-Region Algorithms to First- and Second-Order Critical Points. SIAM J. Optim. 20 (1) (2009)
Narges Bani Asadi, Irina Rish, Katya Scheinberg, Dimitri Kanevsky, Bhuvana Ramabhadran
Map approach to learning sparse Gaussian Markov networks. ICASSP (2009)
Donald Goldfarb, Shiqian Ma, Katya Scheinberg
Fast Alternating Linearization Methods for Minimizing the Sum of Two Convex Functions. CoRR (2009)
Andrew R. Conn, Katya Scheinberg, Luís Nunes Vicente
Geometry of interpolation sets in derivative free optimization. Math. Program. 111 (1-2) (2008)
Katya Scheinberg, Jiming Peng
PREFACESpecial section on mathematical programming in data mining and machine learning. Optim. Methods Softw. 23 (4) (2008)
Murray Campbell, Alexander Haubold, Shahram Ebadollahi, Dhiraj Joshi, Milind R. Naphade, Apostol Natsev, Joachim Seidl, John R. Smith, Katya Scheinberg, Jelena Tesic, Lexing Xie
IBM Research TRECVID-2006 Video Retrieval System. TRECVID (2006)
Katya Scheinberg
An Efficient Implementation of an Active Set Method for SVMs. J. Mach. Learn. Res. 7 (2006)
Donald Goldfarb, Katya Scheinberg
Product-form Cholesky factorization in interior point methods for second-order cone programming. Math. Program. 103 (1) (2005)
Donald Goldfarb, Katya Scheinberg
A product-form Cholesky factorization method for handling dense columns in interior point methods for linear programming. Math. Program. 99 (1) (2004)
Shai Fine, Katya Scheinberg
Efficient SVM Training Using Low-Rank Kernel Representations. J. Mach. Learn. Res. 2 (2001)
Shai Fine, Katya Scheinberg
Incremental Learning and Selective Sampling via Parametric Optimization Framework for SVM. NIPS (2001)
Donald Goldfarb, R. Polyak, Katya Scheinberg, I. Yuzefovich
A Modified Barrier-Augmented Lagrangian Method for Constrained Minimization. Comput. Optim. Appl. 14 (1) (1999)
Donald Goldfarb, Katya Scheinberg
Interior Point Trajectories in Semidefinite Programming. SIAM J. Optim. 8 (4) (1998)
Andrew R. Conn, Katya Scheinberg, Philippe L. Toint
Recent progress in unconstrained nonlinear optimization without derivatives. Math. Program. 79 (1997)
Arkadii Nemirovskii, Katya Scheinberg
Extension of Karmarkar's algorithm onto convex quadratically constrained quadratic problems. Math. Program. 72 (1996)