James V. Burke

66 papers Journal 61Unranked 5

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	A Relaxation Approach to Feature Selection for Linear Mixed Effects Models. J. Comput. Graph. Stat. Aleksei Sholokhov, James V. Burke, Damian F. Santomauro, Peng Zheng, Aleksandr Y. Aravkin
2021	J	`jnl`	A Study of Convex Convex-Composite Functions via Infimal Convolution with Applications. Math. Oper. Res. James V. Burke, Tim Hoheisel, Quang V. Nguyen
2021	J	`jnl`	On the Global Minimizers of Real Robust Phase Retrieval With Sparse Noise. IEEE Trans. Inf. Theory Aleksandr Y. Aravkin, James V. Burke, Daiwei He
2020	J	`jnl`	Inexact Sequential Quadratic Optimization with Penalty Parameter Updates within the QP Solver. SIAM J. Optim. James V. Burke, Frank E. Curtis, Hao Wang, Jiashan Wang
2020	J	`jnl`	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. James V. Burke, Abraham Engle
2020	J	`jnl`	The subdifferential of measurable composite max integrands and smoothing approximation. Math. Program. James V. Burke, Xiaojun Chen, Hailin Sun
2019	J	`jnl`	Fast robust methods for singular state-space models. Autom. Jonathan Jonker, Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, Sarah E. Webster
2019	J	`jnl`	Level-set methods for convex optimization. Math. Program. Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Scott Roy
2019	J	`jnl`	On the Global Minimizers of Real Robust Phase Retrieval with Sparse Noise. CoRR Aleksandr Y. Aravkin, James V. Burke, Daiwei He
2019	—	`conf`	Robust Singular Smoothers for Tracking Using Low-Fidelity Data. Robotics: Science and Systems Jonathan Jonker, Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, Sarah E. Webster
2019	J	`jnl`	Variational Properties of Matrix Functions via the Generalized Matrix-Fractional Function. SIAM J. Optim. James V. Burke, Yuan Gao, Tim Hoheisel
2018	J	`jnl`	Convex Geometry of the Generalized Matrix-Fractional Function. SIAM J. Optim. James V. Burke, Yuan Gao, Tim Hoheisel
2018	J	`jnl`	Foundations of Gauge and Perspective Duality. SIAM J. Optim. Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Kellie J. MacPhee
2018	J	`jnl`	Generalized System Identification with Stable Spline Kernels. SIAM J. Sci. Comput. Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
2018	J	`jnl`	Variational analysis of convexly generated spectral max functions. Math. Program. James V. Burke, Julia Eaton
2017	J	`jnl`	Convex Geometry of the Generalized Matrix-Fractional Function. CoRR James V. Burke, Yuan Gao, Tim Hoheisel
2017	J	`jnl`	Generalized Kalman smoothing: Modeling and algorithms. Autom. Aleksandr Y. Aravkin, James V. Burke, Lennart Ljung, Aurélie C. Lozano, Gianluigi Pillonetto
2016	J	`jnl`	Level-set methods for convex optimization. CoRR Aleksandr Y. Aravkin, James V. Burke, Dmitriy Drusvyatskiy, Michael P. Friedlander, Scott Roy
2015	J	`jnl`	Iterative Reweighted Linear Least Squares for Exact Penalty Subproblems on Product Sets. SIAM J. Optim. James V. Burke, Frank E. Curtis, Hao Wang, Jiashan Wang
2015	J	`jnl`	Matrix Support Functionals for Inverse Problems, Regularization, and Learning. SIAM J. Optim. James V. Burke, Tim Hoheisel
2015	J	`jnl`	The Connection Between Bayesian Estimation of a Gaussian Random Field and RKHS. IEEE Trans. Neural Networks Learn. Syst. Aleksandr Y. Aravkin, Bradley M. Bell, James V. Burke, Gianluigi Pillonetto
2014	J	`jnl`	A Sequential Quadratic Optimization Algorithm with Rapid Infeasibility Detection. SIAM J. Optim. James V. Burke, Frank E. Curtis, Hao Wang
2014	J	`jnl`	Convex vs non-convex estimators for regression and sparse estimation: the mean squared error properties of ARD and GLasso. J. Mach. Learn. Res. Aleksandr Y. Aravkin, James V. Burke, Alessandro Chiuso, Gianluigi Pillonetto
2014	J	`jnl`	Robust and Trend-Following Student's t Kalman Smoothers. SIAM J. Control. Optim. Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
2014	—	`conf`	Smoothing dynamic systems with state-dependent covariance matrices. CDC Aleksandr Y. Aravkin, James V. Burke
2013	J	`jnl`	Epi-convergent Smoothing with Applications to Convex Composite Functions. SIAM J. Optim. James V. Burke, Tim Hoheisel
2013	—	`conf`	Linear system identification using stable spline kernels and PLQ penalties. CDC Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
2013	J	`jnl`	Sparse/robust estimation and Kalman smoothing with nonsmooth log-concave densities: modeling, computation, and theory. J. Mach. Learn. Res. Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
2013	J	`jnl`	The exact relationship between regularization in RKHS and Bayesian estimation of Gaussian random fields CoRR Aleksandr Y. Aravkin, Bradley M. Bell, James V. Burke, Gianluigi Pillonetto
2013	J	`jnl`	Variational Properties of Value Functions. SIAM J. Optim. Aleksandr Y. Aravkin, James V. Burke, Michael P. Friedlander
2012	—	`conf`	Nonsmooth regression and state estimation using piecewise quadratic log-concave densities. CDC Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
2011	J	`jnl`	An IEEE Trans. Autom. Control. Aleksandr Y. Aravkin, Bradley M. Bell, James V. Burke, Gianluigi Pillonetto
2011	—	`conf`	Convex vs nonconvex approaches for sparse estimation: Lasso, Multiple Kernel Learning and Hyperparameter Lasso. CDC/ECC Aleksandr Y. Aravkin, James V. Burke, Alessandro Chiuso, Gianluigi Pillonetto
2009	J	`jnl`	An inequality constrained nonlinear Kalman-Bucy smoother by interior point likelihood maximization. Autom. Bradley M. Bell, James V. Burke, Gianluigi Pillonetto
2009	J	`jnl`	Weak sharp minima revisited, Part III: error bounds for differentiable convex inclusions. Math. Program. James V. Burke, Sien Deng
2007	J	`jnl`	Convexity and Lipschitz Behavior of Small Pseudospectra. SIAM J. Matrix Anal. Appl. James V. Burke, Adrian S. Lewis, Michael L. Overton
2007	J	`jnl`	Spectral conditioning and pseudospectral growth. Numerische Mathematik James V. Burke, Adrian S. Lewis, Michael L. Overton
2006	J	`jnl`	Stabilization via Nonsmooth, Nonconvex Optimization. IEEE Trans. Autom. Control. James V. Burke, Didier Henrion, Adrian S. Lewis, Michael L. Overton
2005	J	`jnl`	A Robust Gradient Sampling Algorithm for Nonsmooth, Nonconvex Optimization. SIAM J. Optim. James V. Burke, Adrian S. Lewis, Michael L. Overton
2005	J	`jnl`	Variational analysis of functions of the roots of polynomials. Math. Program. James V. Burke, Adrian S. Lewis, Michael L. Overton
2005	J	`jnl`	Weak sharp minima revisited, part II: application to linear regularity and error bounds. Math. Program. James V. Burke, Sien Deng
2004	J	`jnl`	Pseudospectral Components and the Distance to Uncontrollability. SIAM J. Matrix Anal. Appl. James V. Burke, Adrian S. Lewis, Michael L. Overton
2004	J	`jnl`	Variational Analysis of the Abscissa Mapping for Polynomials via the Gauss-Lucas Theorem. J. Glob. Optim. James V. Burke, Adrian S. Lewis, Michael L. Overton
2003	J	`jnl`	Optimization and Pseudospectra, with Applications to Robust Stability. SIAM J. Matrix Anal. Appl. James V. Burke, Adrian S. Lewis, Michael L. Overton
2003	J	`jnl`	Variational Analysis Applied to the Problem of Optical Phase Retrieval. SIAM J. Control. Optim. James V. Burke, D. Russell Luke
2002	J	`jnl`	Approximating Subdifferentials by Random Sampling of Gradients. Math. Oper. Res. James V. Burke, Adrian S. Lewis, Michael L. Overton
2002	J	`jnl`	Optical Wavefront Reconstruction: Theory and Numerical Methods. SIAM Rev. D. Russell Luke, James V. Burke, Richard G. Lyon
2001	J	`jnl`	Optimal Stability and Eigenvalue Multiplicity. Found. Comput. Math. James V. Burke, Adrian S. Lewis, Michael L. Overton
2001	J	`jnl`	Variational Analysis of the Abscissa Mapping for Polynomials. SIAM J. Control. Optim. James V. Burke, Michael L. Overton
2001	J	`jnl`	Variational analysis of non-Lipschitz spectral functions. Math. Program. James V. Burke, Michael L. Overton
2000	J	`jnl`	A non-interior predictor-corrector path following algorithm for the monotone linear complementarity problem. Math. Program. James V. Burke, Song Xu
2000	J	`jnl`	On the superlinear convergence of the variable metric proximal point algorithm using Broyden and BFGS matrix secant updating. Math. Program. James V. Burke, Maijian Qian
1999	J	`jnl`	A polynomial time interior-point path-following algorithm for LCP based on Chen-Harker-Kanzow smoothing techniques. Math. Program. Song Xu, James V. Burke
1998	J	`jnl`	The Global Linear Convergence of a Noninterior Path-Following Algorithm for Linear Complementarity Problems. Math. Oper. Res. James V. Burke, Song Xu
1997	J	`jnl`	On the Lidskii-Vishik-Lyusternik Perturbation Theory for Eigenvalues of Matrices with Arbitrary Jordan Structure. SIAM J. Matrix Anal. Appl. Julio Moro, James V. Burke, Michael L. Overton
1996	J	`jnl`	A Unified Analysis of Hoffman's Bound via Fenchel Duality. SIAM J. Optim. James V. Burke, Paul Tseng
1995	J	`jnl`	A Gauss-Newton method for convex composite optimization. Math. Program. James V. Burke, Michael C. Ferris
1994	J	`jnl`	Exposing Constraints. SIAM J. Optim. James V. Burke, Jorge J. Moré
1992	J	`jnl`	A Robust Trust Region Method for Constrained Nonlinear Programming Problems. SIAM J. Optim. James V. Burke
1992	J	`jnl`	Optimality conditions for non-finite valued convex composite functions. Math. Program. James V. Burke, R. A. Poliquin
1991	J	`jnl`	Characterization of solution sets of convex programs. Oper. Res. Lett. James V. Burke, Michael C. Ferris
1990	J	`jnl`	Convergence Properties of Trust Region Methods for Linear and Convex Constraints. Math. Program. James V. Burke, Jorge J. Moré, Gerardo Toraldo
1989	J	`jnl`	A robust sequential quadratic programming method. Math. Program. James V. Burke, Shih-Ping Han
1987	J	`jnl`	Second order necessary and sufficient conditions for convex composite NDO. Math. Program. James V. Burke
1986	J	`jnl`	A Gauss-Newton Approach to Solving Generalized Inequalities. Math. Oper. Res. James V. Burke, S.-P. Han
1985	J	`jnl`	Descent methods for composite nondifferentiable optimization problems. Math. Program. James V. Burke