Extension of Karmarkar's algorithm onto convex quadratically constrained quadratic problems. - Arkadii Nemirovskii; Katya Scheinberg (Math. Program., 1996)

Recent progress in unconstrained nonlinear optimization without derivatives. - Andrew R. Conn; Katya Scheinberg; Philippe L. Toint (Math. Program., 1997)

Interior Point Trajectories in Semidefinite Programming. - Donald Goldfarb; Katya Scheinberg (SIAM J. Optim., 1998)

A Modified Barrier-Augmented Lagrangian Method for Constrained Minimization. - Donald Goldfarb; R. Polyak; Katya Scheinberg; I. Yuzefovich (Comput. Optim. Appl., 1999)

Incremental Learning and Selective Sampling via Parametric Optimization Framework for SVM. - Shai Fine; Katya Scheinberg (NIPS, 2001)

Efficient SVM Training Using Low-Rank Kernel Representations. - Shai Fine; Katya Scheinberg (J. Mach. Learn. Res., 2001)

A product-form Cholesky factorization method for handling dense columns in interior point methods for linear programming. - Donald Goldfarb; Katya Scheinberg (Math. Program., 2004)

Product-form Cholesky factorization in interior point methods for second-order cone programming. - Donald Goldfarb; Katya Scheinberg (Math. Program., 2005)

IBM Research TRECVID-2006 Video Retrieval System. - Murray Campbell; Alexander Haubold; Shahram Ebadollahi; Dhiraj Joshi; Milind R. Naphade; Apostol Natsev; Joachim Seidl; John R. Smith; Katya Scheinberg; Jelena Tesic; Lexing Xie (TRECVID, 2006)

An Efficient Implementation of an Active Set Method for SVMs. - Katya Scheinberg (J. Mach. Learn. Res., 2006)

Geometry of interpolation sets in derivative free optimization. - Andrew R. Conn; Katya Scheinberg; Luís Nunes Vicente (Math. Program., 2008)

PREFACESpecial section on mathematical programming in data mining and machine learning. - Katya Scheinberg; Jiming Peng (Optim. Methods Softw., 2008)

Introduction to Derivative-Free Optimization. - Andrew R. Conn; Katya Scheinberg; Luís Nunes Vicente (SIAM, 2009)

Map approach to learning sparse Gaussian Markov networks. - Narges Bani Asadi; Irina Rish; Katya Scheinberg; Dimitri Kanevsky; Bhuvana Ramabhadran (ICASSP, 2009)

Global Convergence of General Derivative-Free Trust-Region Algorithms to First- and Second-Order Critical Points. - Andrew R. Conn; Katya Scheinberg; Luís Nunes Vicente (SIAM J. Optim., 2009)

Sparse Markov net learning with priors on regularization parameters. - Katya Scheinberg; Irina Rish; Narges Bani Asadi (ISAIM, 2010)

Sparse Inverse Covariance Selection via Alternating Linearization Methods. - Katya Scheinberg; Shiqian Ma; Donald Goldfarb (NIPS, 2010)

Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach. - Katya Scheinberg; Irina Rish (ECML/PKDD (3), 2010)

Self-Correcting Geometry in Model-Based Algorithms for Derivative-Free Unconstrained Optimization. - Katya Scheinberg; Philippe L. Toint (SIAM J. Optim., 2010)

A Derivative-Free Algorithm for Least-Squares Minimization. - Hongchao Zhang; Andrew R. Conn; Katya Scheinberg (SIAM J. Optim., 2010)

Aligning ligand binding cavities by optimizing superposed volume. - Ruobing Chen 001; Katya Scheinberg; Brian Yuan Chen (BIBM, 2012)

Computation of sparse low degree interpolating polynomials and their application to derivative-free optimization. - Afonso S. Bandeira; Katya Scheinberg; Luís Nunes Vicente (Math. Program., 2012)

Complexity of Inexact Proximal Newton methods. - Katya Scheinberg; Xiaocheng Tang (CoRR, 2013)

Efficiently Using Second Order Information in Large l1 Regularization Problems - Xiaocheng Tang; Katya Scheinberg (CoRR, 2013)

On partial sparse recovery - Afonso S. Bandeira; Katya Scheinberg; Luís Nunes Vicente (CoRR, 2013)

Fast alternating linearization methods for minimizing the sum of two convex functions. - Donald Goldfarb; Shiqian Ma; Katya Scheinberg (Math. Program., 2013)

Efficient block-coordinate descent algorithms for the Group Lasso. - Zhiwei (Tony) Qin; Katya Scheinberg; Donald Goldfarb (Math. Program. Comput., 2013)

Fast First-Order Methods for Composite Convex Optimization with Backtracking. - Katya Scheinberg; Donald Goldfarb; Xi Bai (Found. Comput. Math., 2014)

Convergence of Trust-Region Methods Based on Probabilistic Models. - Afonso S. Bandeira; Katya Scheinberg; Luís Nunes Vicente (SIAM J. Optim., 2014)

Superposition of protein structures using electrostatic isopotentials. - Ziyi Guo; Katya Scheinberg; Juliana Hong; Brian Yuan Chen (BIBM, 2015)

A scalable solution for group feature selection. - Priya Govindan; Ruobing Chen 001; Katya Scheinberg; Soundararajan Srinivasan (IEEE BigData, 2015)

Proximal Quasi-Newton Methods for Convex Optimization. - Hiva Ghanbari; Katya Scheinberg (CoRR, 2016)

Optimal Generalized Decision Trees via Integer Programming. - Matt Menickelly; Oktay Günlük; Jayant Kalagnanam; Katya Scheinberg (CoRR, 2016)

Practical inexact proximal quasi-Newton method with global complexity analysis. - Katya Scheinberg; Xiaocheng Tang (Math. Program., 2016)

An Empirical Analysis of Constrained Support Vector Quantile Regression for Nonparametric Probabilistic Forecasting of Wind Power. - Kostas Hatalis; Shalinee Kishore; Katya Scheinberg; Alberto J. Lamadrid (AAAI Workshops, 2017)

A Novel l0-Constrained Gaussian Graphical Model for Anomaly Localization. - Dzung T. Phan; Tsuyoshi Idé; Jayant Kalagnanam; Matt Menickelly; Katya Scheinberg (ICDM Workshops, 2017)

SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient. - Lam M. Nguyen; Jie Liu 036; Katya Scheinberg; Martin Takác 001 (ICML, 2017)

Optimization Methods for Supervised Machine Learning: From Linear Models to Deep Learning. - Frank E. Curtis; Katya Scheinberg (CoRR, 2017)

Black-Box Optimization in Machine Learning with Trust Region Based Derivative Free Algorithm. - Hiva Ghanbari; Katya Scheinberg (CoRR, 2017)

Stochastic Recursive Gradient Algorithm for Nonconvex Optimization. - Lam M. Nguyen; Jie Liu 036; Katya Scheinberg; Martin Takác 001 (CoRR, 2017)

On the construction of quadratic models for derivative-free trust-region algorithms. - Adriano Verdério; Elizabeth W. Karas; Lucas G. Pedroso; Katya Scheinberg (EURO J. Comput. Optim., 2017)

SGD and Hogwild! Convergence Without the Bounded Gradients Assumption. - Lam M. Nguyen; Phuong Ha Nguyen; Marten van Dijk; Peter Richtárik; Katya Scheinberg; Martin Takác 001 (ICML, 2018)

Proximal quasi-Newton methods for regularized convex optimization with linear and accelerated sublinear convergence rates. - Hiva Ghanbari; Katya Scheinberg (Comput. Optim. Appl., 2018)

When Does Stochastic Gradient Algorithm Work Well? - Lam M. Nguyen; Nam H. Nguyen; Dzung T. Phan; Jayant R. Kalagnanam; Katya Scheinberg (CoRR, 2018)

Directly and Efficiently Optimizing Prediction Error and AUC of Linear Classifiers. - Hiva Ghanbari; Katya Scheinberg (CoRR, 2018)

Global convergence rate analysis of unconstrained optimization methods based on probabilistic models. - Coralia Cartis; Katya Scheinberg (Math. Program., 2018)

Stochastic optimization using a trust-region method and random models. - Ruobing Chen 001; Matt Menickelly; Katya Scheinberg (Math. Program., 2018)

Novel and Efficient Approximations for Zero-One Loss of Linear Classifiers. - Hiva Ghanbari; Minhan Li; Katya Scheinberg (CoRR, 2019)

Feature Engineering and Forecasting via Integration of Derivative-free Optimization and Ensemble of Sequence-to-sequence Networks: Renewable Energy Case Studies. - Mohammad Pirhooshyaran; Lawrence V. Snyder; Katya Scheinberg (CoRR, 2019)

A Novel Smoothed Loss and Penalty Function for Noncrossing Composite Quantile Estimation via Deep Neural Networks. - Kostas Hatalis; Alberto J. Lamadrid; Katya Scheinberg; Shalinee Kishore (CoRR, 2019)

New Convergence Aspects of Stochastic Gradient Algorithms. - Lam M. Nguyen; Phuong Ha Nguyen; Peter Richtárik; Katya Scheinberg; Martin Takác 001; Marten van Dijk (J. Mach. Learn. Res., 2019)

Convergence Rate Analysis of a Stochastic Trust-Region Method via Supermartingales. - Jose H. Blanchet; Coralia Cartis; Matt Menickelly; Katya Scheinberg (INFORMS J. Optim., 2019)

A Stochastic Trust Region Algorithm Based on Careful Step Normalization. - Frank E. Curtis; Katya Scheinberg; Rui Shi (INFORMS J. Optim., 2019)

Adaptive Stochastic Optimization. - Frank E. Curtis; Katya Scheinberg (CoRR, 2020)

A Stochastic Line Search Method with Expected Complexity Analysis. - Courtney Paquette; Katya Scheinberg (SIAM J. Optim., 2020)

Adaptive Stochastic Optimization: A Framework for Analyzing Stochastic Optimization Algorithms. - Frank E. Curtis; Katya Scheinberg (IEEE Signal Process. Mag., 2020)

High Probability Complexity Bounds for Line Search Based on Stochastic Oracles. - Billy Jin; Katya Scheinberg; Miaolan Xie (NeurIPS, 2021)

Optimal decision trees for categorical data via integer programming. - Oktay Günlük; Jayant Kalagnanam; Minhan Li; Matt Menickelly; Katya Scheinberg (J. Glob. Optim., 2021)

Inexact SARAH algorithm for stochastic optimization. - Lam M. Nguyen; Katya Scheinberg; Martin Takác 001 (Optim. Methods Softw., 2021)

Global Convergence Rate Analysis of a Generic Line Search Algorithm with Noise. - Albert S. Berahas; Liyuan Cao; Katya Scheinberg (SIAM J. Optim., 2021)

Nesterov Accelerated Shuffling Gradient Method for Convex Optimization. - Trang H. Tran; Katya Scheinberg; Lam M. Nguyen (ICML, 2022)

Finding Optimal Policy for Queueing Models: New Parameterization. - Trang H. Tran; Lam M. Nguyen; Katya Scheinberg (CoRR, 2022)

A Theoretical and Empirical Comparison of Gradient Approximations in Derivative-Free Optimization. - Albert S. Berahas; Liyuan Cao; Krzysztof Choromanski; Katya Scheinberg (Found. Comput. Math., 2022)

Finite Difference Gradient Approximation: To Randomize or Not? - Katya Scheinberg (INFORMS J. Comput., 2022)

Stochastic Adaptive Regularization Method with Cubics: a High Probability Complexity Bound. - Katya Scheinberg; Miaolan Xie (WSC, 2023)

High Probability Complexity Bounds for Adaptive Step Search Based on Stochastic Oracles. - Billy Jin; Katya Scheinberg; Miaolan Xie (SIAM J. Optim., 2024)

First- and second-order high probability complexity bounds for trust-region methods with noisy oracles. - Liyuan Cao; Albert S. Berahas; Katya Scheinberg (Math. Program., 2024)

Sample complexity analysis for adaptive optimization algorithms with stochastic oracles. - Billy Jin; Katya Scheinberg; Miaolan Xie (Math. Program., 2025)

High Probability Complexity Bounds of Trust-Region Stochastic Sequential Quadratic Programming with Heavy-Tailed Noise. - Yuchen Fang; Javad Lavaei; Katya Scheinberg; Sen Na (CoRR, 2025)

Stochastic ISTA/FISTA Adaptive Step Search Algorithms for Convex Composite Optimization. - Lam M. Nguyen; Katya Scheinberg; Trang H. Tran (J. Optim. Theory Appl., 2025)