Descent methods for composite nondifferentiable optimization problems. - James V. Burke (Math. Program., 1985)

A Gauss-Newton Approach to Solving Generalized Inequalities. - James V. Burke; S.-P. Han (Math. Oper. Res., 1986)

Second order necessary and sufficient conditions for convex composite NDO. - James V. Burke (Math. Program., 1987)

A robust sequential quadratic programming method. - James V. Burke; Shih-Ping Han (Math. Program., 1989)

Convergence Properties of Trust Region Methods for Linear and Convex Constraints. - James V. Burke; Jorge J. Moré; Gerardo Toraldo (Math. Program., 1990)

Characterization of solution sets of convex programs. - James V. Burke; Michael C. Ferris (Oper. Res. Lett., 1991)

Optimality conditions for non-finite valued convex composite functions. - James V. Burke; R. A. Poliquin (Math. Program., 1992)

A Robust Trust Region Method for Constrained Nonlinear Programming Problems. - James V. Burke (SIAM J. Optim., 1992)

Exposing Constraints. - James V. Burke; Jorge J. Moré (SIAM J. Optim., 1994)

A Gauss-Newton method for convex composite optimization. - James V. Burke; Michael C. Ferris (Math. Program., 1995)

A Unified Analysis of Hoffman's Bound via Fenchel Duality. - James V. Burke; Paul Tseng (SIAM J. Optim., 1996)

On the Lidskii-Vishik-Lyusternik Perturbation Theory for Eigenvalues of Matrices with Arbitrary Jordan Structure. - Julio Moro; James V. Burke; Michael L. Overton (SIAM J. Matrix Anal. Appl., 1997)

The Global Linear Convergence of a Noninterior Path-Following Algorithm for Linear Complementarity Problems. - James V. Burke; Song Xu 001 (Math. Oper. Res., 1998)

A polynomial time interior-point path-following algorithm for LCP based on Chen-Harker-Kanzow smoothing techniques. - Song Xu 001; James V. Burke (Math. Program., 1999)

On the superlinear convergence of the variable metric proximal point algorithm using Broyden and BFGS matrix secant updating. - James V. Burke; Maijian Qian (Math. Program., 2000)

A non-interior predictor-corrector path following algorithm for the monotone linear complementarity problem. - James V. Burke; Song Xu 001 (Math. Program., 2000)

Optimal Stability and Eigenvalue Multiplicity. - James V. Burke; Adrian S. Lewis; Michael L. Overton (Found. Comput. Math., 2001)

Variational analysis of non-Lipschitz spectral functions. - James V. Burke; Michael L. Overton (Math. Program., 2001)

Variational Analysis of the Abscissa Mapping for Polynomials. - James V. Burke; Michael L. Overton (SIAM J. Control. Optim., 2001)

Approximating Subdifferentials by Random Sampling of Gradients. - James V. Burke; Adrian S. Lewis; Michael L. Overton (Math. Oper. Res., 2002)

Optical Wavefront Reconstruction: Theory and Numerical Methods. - D. Russell Luke; James V. Burke; Richard G. Lyon (SIAM Rev., 2002)

Variational Analysis Applied to the Problem of Optical Phase Retrieval. - James V. Burke; D. Russell Luke (SIAM J. Control. Optim., 2003)

Optimization and Pseudospectra, with Applications to Robust Stability. - James V. Burke; Adrian S. Lewis; Michael L. Overton (SIAM J. Matrix Anal. Appl., 2003)

Variational Analysis of the Abscissa Mapping for Polynomials via the Gauss-Lucas Theorem. - James V. Burke; Adrian S. Lewis; Michael L. Overton (J. Glob. Optim., 2004)

Pseudospectral Components and the Distance to Uncontrollability. - James V. Burke; Adrian S. Lewis; Michael L. Overton (SIAM J. Matrix Anal. Appl., 2004)

Weak sharp minima revisited, part II: application to linear regularity and error bounds. - James V. Burke; Sien Deng (Math. Program., 2005)

Variational analysis of functions of the roots of polynomials. - James V. Burke; Adrian S. Lewis; Michael L. Overton (Math. Program., 2005)

A Robust Gradient Sampling Algorithm for Nonsmooth, Nonconvex Optimization. - James V. Burke; Adrian S. Lewis; Michael L. Overton (SIAM J. Optim., 2005)

Stabilization via Nonsmooth, Nonconvex Optimization. - James V. Burke; Didier Henrion; Adrian S. Lewis; Michael L. Overton (IEEE Trans. Autom. Control., 2006)

Spectral conditioning and pseudospectral growth. - James V. Burke; Adrian S. Lewis; Michael L. Overton (Numerische Mathematik, 2007)

Convexity and Lipschitz Behavior of Small Pseudospectra. - James V. Burke; Adrian S. Lewis; Michael L. Overton (SIAM J. Matrix Anal. Appl., 2007)

An inequality constrained nonlinear Kalman-Bucy smoother by interior point likelihood maximization. - Bradley M. Bell; James V. Burke; Gianluigi Pillonetto (Autom., 2009)

Weak sharp minima revisited, Part III: error bounds for differentiable convex inclusions. - James V. Burke; Sien Deng (Math. Program., 2009)

Convex vs nonconvex approaches for sparse estimation: Lasso, Multiple Kernel Learning and Hyperparameter Lasso. - Aleksandr Y. Aravkin; James V. Burke; Alessandro Chiuso; Gianluigi Pillonetto (CDC/ECC, 2011)

An 1 -Laplace Robust Kalman Smoother. - Aleksandr Y. Aravkin; Bradley M. Bell; James V. Burke; Gianluigi Pillonetto (IEEE Trans. Autom. Control., 2011)

Nonsmooth regression and state estimation using piecewise quadratic log-concave densities. - Aleksandr Y. Aravkin; James V. Burke; Gianluigi Pillonetto (CDC, 2012)

Linear system identification using stable spline kernels and PLQ penalties. - Aleksandr Y. Aravkin; James V. Burke; Gianluigi Pillonetto (CDC, 2013)

The exact relationship between regularization in RKHS and Bayesian estimation of Gaussian random fields - Aleksandr Y. Aravkin; Bradley M. Bell; James V. Burke; Gianluigi Pillonetto (CoRR, 2013)

Sparse/robust estimation and Kalman smoothing with nonsmooth log-concave densities: modeling, computation, and theory. - Aleksandr Y. Aravkin; James V. Burke; Gianluigi Pillonetto (J. Mach. Learn. Res., 2013)

Variational Properties of Value Functions. - Aleksandr Y. Aravkin; James V. Burke; Michael P. Friedlander (SIAM J. Optim., 2013)

Epi-convergent Smoothing with Applications to Convex Composite Functions. - James V. Burke; Tim Hoheisel (SIAM J. Optim., 2013)

Smoothing dynamic systems with state-dependent covariance matrices. - Aleksandr Y. Aravkin; James V. Burke (CDC, 2014)

Convex vs non-convex estimators for regression and sparse estimation: the mean squared error properties of ARD and GLasso. - Aleksandr Y. Aravkin; James V. Burke; Alessandro Chiuso; Gianluigi Pillonetto (J. Mach. Learn. Res., 2014)

Robust and Trend-Following Student's t Kalman Smoothers. - Aleksandr Y. Aravkin; James V. Burke; Gianluigi Pillonetto (SIAM J. Control. Optim., 2014)

A Sequential Quadratic Optimization Algorithm with Rapid Infeasibility Detection. - James V. Burke; Frank E. Curtis; Hao Wang 045 (SIAM J. Optim., 2014)

Iterative Reweighted Linear Least Squares for Exact Penalty Subproblems on Product Sets. - James V. Burke; Frank E. Curtis; Hao Wang 045; Jiashan Wang (SIAM J. Optim., 2015)

Matrix Support Functionals for Inverse Problems, Regularization, and Learning. - James V. Burke; Tim Hoheisel (SIAM J. Optim., 2015)

The Connection Between Bayesian Estimation of a Gaussian Random Field and RKHS. - Aleksandr Y. Aravkin; Bradley M. Bell; James V. Burke; Gianluigi Pillonetto (IEEE Trans. Neural Networks Learn. Syst., 2015)

Generalized Kalman smoothing: Modeling and algorithms. - Aleksandr Y. Aravkin; James V. Burke; Lennart Ljung; Aurélie C. Lozano; Gianluigi Pillonetto (Autom., 2017)

Variational analysis of convexly generated spectral max functions. - James V. Burke; Julia Eaton (Math. Program., 2018)

Foundations of Gauge and Perspective Duality. - Aleksandr Y. Aravkin; James V. Burke; Dmitriy Drusvyatskiy; Michael P. Friedlander; Kellie J. MacPhee (SIAM J. Optim., 2018)

Convex Geometry of the Generalized Matrix-Fractional Function. - James V. Burke; Yuan Gao; Tim Hoheisel (SIAM J. Optim., 2018)

Generalized System Identification with Stable Spline Kernels. - Aleksandr Y. Aravkin; James V. Burke; Gianluigi Pillonetto (SIAM J. Sci. Comput., 2018)

Robust Singular Smoothers for Tracking Using Low-Fidelity Data. - Jonathan Jonker; Aleksandr Y. Aravkin; James V. Burke; Gianluigi Pillonetto; Sarah E. Webster (Robotics: Science and Systems, 2019)

Fast robust methods for singular state-space models. - Jonathan Jonker; Aleksandr Y. Aravkin; James V. Burke; Gianluigi Pillonetto; Sarah E. Webster (Autom., 2019)

Level-set methods for convex optimization. - Aleksandr Y. Aravkin; James V. Burke; Dmitriy Drusvyatskiy; Michael P. Friedlander; Scott Roy (Math. Program., 2019)

Variational Properties of Matrix Functions via the Generalized Matrix-Fractional Function. - James V. Burke; Yuan Gao; Tim Hoheisel (SIAM J. Optim., 2019)

Strong Metric (Sub)regularity of Karush-Kuhn-Tucker Mappings for Piecewise Linear-Quadratic Convex-Composite Optimization and the Quadratic Convergence of Newton's Method. - James V. Burke; Abraham Engle (Math. Oper. Res., 2020)

The subdifferential of measurable composite max integrands and smoothing approximation. - James V. Burke; Xiaojun Chen 001; Hailin Sun (Math. Program., 2020)

Inexact Sequential Quadratic Optimization with Penalty Parameter Updates within the QP Solver. - James V. Burke; Frank E. Curtis; Hao Wang 045; Jiashan Wang (SIAM J. Optim., 2020)

A Study of Convex Convex-Composite Functions via Infimal Convolution with Applications. - James V. Burke; Tim Hoheisel; Quang V. Nguyen (Math. Oper. Res., 2021)

On the Global Minimizers of Real Robust Phase Retrieval With Sparse Noise. - Aleksandr Y. Aravkin; James V. Burke; Daiwei He (IEEE Trans. Inf. Theory, 2021)

A Relaxation Approach to Feature Selection for Linear Mixed Effects Models. - Aleksei Sholokhov; James V. Burke; Damian F. Santomauro; Peng Zheng 002; Aleksandr Y. Aravkin (J. Comput. Graph. Stat., 2024)