James V. Burke

Publication Activity (10 Years)

Years Active: 1985-2021
Publications (10 Years): 20

Top Topics

Gaussian Random Field

Top Venues

Publications

James V. Burke, Tim Hoheisel, Quang V. Nguyen
A Study of Convex Convex-Composite Functions via Infimal Convolution with Applications. Math. Oper. Res. 46 (4) (2021)
Aleksandr Y. Aravkin, James V. Burke, Daiwei He
On the Global Minimizers of Real Robust Phase Retrieval With Sparse Noise. IEEE Trans. Inf. Theory 67 (3) (2021)
James V. Burke, Abraham Engle
Strong Metric (Sub)regularity of Karush-Kuhn-Tucker Mappings for Piecewise Linear-Quadratic Convex-Composite Optimization and the Quadratic Convergence of Newton's Method. Math. Oper. Res. 45 (3) (2020)
James V. Burke, Xiaojun Chen, Hailin Sun
The subdifferential of measurable composite max integrands and smoothing approximation. Math. Program. 181 (2) (2020)
James V. Burke, Frank E. Curtis, Hao Wang, Jiashan Wang
Inexact Sequential Quadratic Optimization with Penalty Parameter Updates within the QP Solver. SIAM J. Optim. 30 (3) (2020)
Jonathan Jonker, Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, Sarah E. Webster
Fast robust methods for singular state-space models. Autom. 105 (2019)
James V. Burke, Yuan Gao, Tim Hoheisel
Variational Properties of Matrix Functions via the Generalized Matrix-Fractional Function. SIAM J. Optim. 29 (3) (2019)
Aleksandr Y. Aravkin, James V. Burke, Daiwei He
On the Global Minimizers of Real Robust Phase Retrieval with Sparse Noise. CoRR (2019)
Jonathan Jonker, Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, Sarah E. Webster
Robust Singular Smoothers for Tracking Using Low-Fidelity Data. Robotics: Science and Systems (2019)
Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Scott Roy
Level-set methods for convex optimization. Math. Program. 174 (1-2) (2019)
Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Kellie J. MacPhee
Foundations of Gauge and Perspective Duality. SIAM J. Optim. 28 (3) (2018)
James V. Burke, Yuan Gao, Tim Hoheisel
Convex Geometry of the Generalized Matrix-Fractional Function. SIAM J. Optim. 28 (3) (2018)
Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
Generalized System Identification with Stable Spline Kernels. SIAM J. Sci. Comput. 40 (5) (2018)
James V. Burke, Julia Eaton
Variational analysis of convexly generated spectral max functions. Math. Program. 168 (1-2) (2018)
Aleksandr Y. Aravkin, James V. Burke, Lennart Ljung, Aurelie C. Lozano, Gianluigi Pillonetto
Generalized Kalman smoothing: Modeling and algorithms. Autom. 86 (2017)
James V. Burke, Yuan Gao, Tim Hoheisel
Convex Geometry of the Generalized Matrix-Fractional Function. CoRR (2017)
Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Scott Roy
Level-set methods for convex optimization. CoRR (2016)
James V. Burke, Frank E. Curtis, Hao Wang, Jiashan Wang
Iterative Reweighted Linear Least Squares for Exact Penalty Subproblems on Product Sets. SIAM J. Optim. 25 (1) (2015)
James V. Burke, Tim Hoheisel
Matrix Support Functionals for Inverse Problems, Regularization, and Learning. SIAM J. Optim. 25 (2) (2015)
Aleksandr Y. Aravkin, Bradley M. Bell, James V. Burke, Gianluigi Pillonetto
The Connection Between Bayesian Estimation of a Gaussian Random Field and RKHS. IEEE Trans. Neural Networks Learn. Syst. 26 (7) (2015)
James V. Burke, Frank E. Curtis, Hao Wang
A Sequential Quadratic Optimization Algorithm with Rapid Infeasibility Detection. SIAM J. Optim. 24 (2) (2014)
Aleksandr Y. Aravkin, James V. Burke
Smoothing dynamic systems with state-dependent covariance matrices. CDC (2014)
Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
Robust and Trend-Following Student's t Kalman Smoothers. SIAM J. Control. Optim. 52 (5) (2014)
Aleksandr Y. Aravkin, James V. Burke, Alessandro Chiuso, Gianluigi Pillonetto
Convex vs non-convex estimators for regression and sparse estimation: the mean squared error properties of ARD and GLasso. J. Mach. Learn. Res. 15 (1) (2014)
Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
Linear system identification using stable spline kernels and PLQ penalties. CDC (2013)
Aleksandr Y. Aravkin, James V. Burke, Michael P. Friedlander
Variational Properties of Value Functions. SIAM J. Optim. 23 (3) (2013)
Aleksandr Y. Aravkin, Bradley M. Bell, James V. Burke, Gianluigi Pillonetto
The exact relationship between regularization in RKHS and Bayesian estimation of Gaussian random fields CoRR (2013)
James V. Burke, Tim Hoheisel
Epi-convergent Smoothing with Applications to Convex Composite Functions. SIAM J. Optim. 23 (3) (2013)
Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
Sparse/robust estimation and Kalman smoothing with nonsmooth log-concave densities: modeling, computation, and theory. J. Mach. Learn. Res. 14 (1) (2013)
Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
Nonsmooth regression and state estimation using piecewise quadratic log-concave densities. CDC (2012)
Aleksandr Y. Aravkin, James V. Burke, Alessandro Chiuso, Gianluigi Pillonetto
Convex vs nonconvex approaches for sparse estimation: Lasso, Multiple Kernel Learning and Hyperparameter Lasso. CDC/ECC (2011)
Aleksandr Y. Aravkin, Bradley M. Bell, James V. Burke, Gianluigi Pillonetto
-Laplace Robust Kalman Smoother. IEEE Trans. Autom. Control. 56 (12) (2011)
Bradley M. Bell, James V. Burke, Gianluigi Pillonetto
An inequality constrained nonlinear Kalman-Bucy smoother by interior point likelihood maximization. Autom. 45 (1) (2009)
James V. Burke, Sien Deng
Weak sharp minima revisited, Part III: error bounds for differentiable convex inclusions. Math. Program. 116 (1-2) (2009)
James V. Burke, Adrian S. Lewis, Michael L. Overton
Spectral conditioning and pseudospectral growth. Numerische Mathematik 107 (1) (2007)
James V. Burke, Adrian S. Lewis, Michael L. Overton
Convexity and Lipschitz Behavior of Small Pseudospectra. SIAM J. Matrix Anal. Appl. 29 (2) (2007)
James V. Burke, Didier Henrion, Adrian S. Lewis, Michael L. Overton
Stabilization via Nonsmooth, Nonconvex Optimization. IEEE Trans. Autom. Control. 51 (11) (2006)
James V. Burke, Sien Deng
Weak sharp minima revisited, part II: application to linear regularity and error bounds. Math. Program. 104 (2-3) (2005)
James V. Burke, Adrian S. Lewis, Michael L. Overton
A Robust Gradient Sampling Algorithm for Nonsmooth, Nonconvex Optimization. SIAM J. Optim. 15 (3) (2005)
James V. Burke, Adrian S. Lewis, Michael L. Overton
Variational analysis of functions of the roots of polynomials. Math. Program. 104 (2-3) (2005)
James V. Burke, Adrian S. Lewis, Michael L. Overton
Pseudospectral Components and the Distance to Uncontrollability. SIAM J. Matrix Anal. Appl. 26 (2) (2004)
James V. Burke, Adrian S. Lewis, Michael L. Overton
Variational Analysis of the Abscissa Mapping for Polynomials via the Gauss-Lucas Theorem. J. Glob. Optim. 28 (3-4) (2004)
James V. Burke, D. Russell Luke
Variational Analysis Applied to the Problem of Optical Phase Retrieval. SIAM J. Control. Optim. 42 (2) (2003)
James V. Burke, Adrian S. Lewis, Michael L. Overton
Optimization and Pseudospectra, with Applications to Robust Stability. SIAM J. Matrix Anal. Appl. 25 (1) (2003)
D. Russell Luke, James V. Burke, Richard G. Lyon
Optical Wavefront Reconstruction: Theory and Numerical Methods. SIAM Rev. 44 (2) (2002)
James V. Burke, Adrian S. Lewis, Michael L. Overton
Approximating Subdifferentials by Random Sampling of Gradients. Math. Oper. Res. 27 (3) (2002)
James V. Burke, Michael L. Overton
Variational analysis of non-Lipschitz spectral functions. Math. Program. 90 (2) (2001)
James V. Burke, Adrian S. Lewis, Michael L. Overton
Optimal Stability and Eigenvalue Multiplicity. Found. Comput. Math. 1 (2) (2001)
James V. Burke, Michael L. Overton
Variational Analysis of the Abscissa Mapping for Polynomials. SIAM J. Control. Optim. 39 (6) (2001)
James V. Burke, Maijian Qian
On the superlinear convergence of the variable metric proximal point algorithm using Broyden and BFGS matrix secant updating. Math. Program. 88 (1) (2000)
James V. Burke, Song Xu
A non-interior predictor-corrector path following algorithm for the monotone linear complementarity problem. Math. Program. 87 (1) (2000)
Song Xu, James V. Burke
A polynomial time interior-point path-following algorithm for LCP based on Chen-Harker-Kanzow smoothing techniques. Math. Program. 86 (1) (1999)
James V. Burke, Song Xu
The Global Linear Convergence of a Noninterior Path-Following Algorithm for Linear Complementarity Problems. Math. Oper. Res. 23 (3) (1998)
Julio Moro, James V. Burke, Michael L. Overton
On the Lidskii-Vishik-Lyusternik Perturbation Theory for Eigenvalues of Matrices with Arbitrary Jordan Structure. SIAM J. Matrix Anal. Appl. 18 (4) (1997)
James V. Burke, Paul Tseng
A Unified Analysis of Hoffman's Bound via Fenchel Duality. SIAM J. Optim. 6 (2) (1996)
James V. Burke, Michael C. Ferris
A Gauss-Newton method for convex composite optimization. Math. Program. 71 (1995)
James V. Burke, Jorge J. Moré
Exposing Constraints. SIAM J. Optim. 4 (3) (1994)
James V. Burke
A Robust Trust Region Method for Constrained Nonlinear Programming Problems. SIAM J. Optim. 2 (2) (1992)
James V. Burke, R. A. Poliquin
Optimality conditions for non-finite valued convex composite functions. Math. Program. 57 (1992)
James V. Burke, Michael C. Ferris
Characterization of solution sets of convex programs. Oper. Res. Lett. 10 (1) (1991)
James V. Burke, Jorge J. Moré, Gerardo Toraldo
Convergence Properties of Trust Region Methods for Linear and Convex Constraints. Math. Program. 47 (1990)
James V. Burke, Shih-Ping Han
A robust sequential quadratic programming method. Math. Program. 43 (1-3) (1989)
James V. Burke
Second order necessary and sufficient conditions for convex composite NDO. Math. Program. 38 (3) (1987)
James V. Burke, S.-P. Han
A Gauss-Newton Approach to Solving Generalized Inequalities. Math. Oper. Res. 11 (4) (1986)
James V. Burke
Descent methods for composite nondifferentiable optimization problems. Math. Program. 33 (3) (1985)