Search Results - "Scheinberg, K."

Global convergence rate analysis of unconstrained optimization methods based on probabilistic models by Cartis, C., Scheinberg, K.

“…We present global convergence rates for a line-search method which is based on random first-order models and directions whose quality is ensured only with…”
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Stochastic optimization using a trust-region method and random models by Chen, R., Menickelly, M., Scheinberg, K.

“…In this paper, we propose and analyze a trust-region model-based algorithm for solving unconstrained stochastic optimization problems. Our framework utilizes…”
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Computation of sparse low degree interpolating polynomials and their application to derivative-free optimization by Bandeira, A. S., Scheinberg, K., Vicente, L. N.

“…Interpolation-based trust-region methods are an important class of algorithms for Derivative-Free Optimization which rely on locally approximating an objective…”
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Geometry of interpolation sets in derivative free optimization by Conn, A. R., Scheinberg, K., Vicente, Luís N.

“…We consider derivative free methods based on sampling approaches for nonlinear optimization problems where derivatives of the objective function are not…”
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Product-form Cholesky factorization in interior point methods for second-order cone programming by GOLDFARB, D, SCHEINBERG, K

“…Second-order cone programming (SOCP) problems are typically solved by interior point methods. As in linear programming (LP), interior point methods can, in…”
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Recent progress in unconstrained nonlinear optimization without derivatives by CONN, A. R, SCHEINBERG, K, TOINT, P. L

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Numerically stable LDLT factorizations in interior point methods for convex quadratic programming by Goldfarb, D., Scheinberg, K.

“…Fletcher & Powell (1974, Math. Comput., 28, 1067–1087) proposed a numerically stable method for updating the LDLT factorization of a symmetric…”
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A product-form Cholesky factorization method for handling dense columns in interior point methods for linear programming by GOLDFARB, D, SCHEINBERG, K

“…Cholesky factorization has become the method of choice for solving the symmetric system of linear equations arising in interior point methods (IPMs) for linear…”
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Sparse Modeling in fMRI Analysis by Rish, I, Carroll, M.K., Cecchi, G.A., Garg, R., Rao, A.R., Asadi, N. Bani, Scheinberg, K.

“…[...]we address the problem of learning interactions among voxels in the form of probabilistic graphical models, such as Markov networks (or Markov Random…”
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On parametric semidefinite programming by Goldfarb, D., Scheinberg, K.

“…In this paper we consider a semidefinite programming (SDP) problem in which the objective function depends linearly on a scalar parameter. We study the…”
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A Modified Barrier-Augmented Lagrangian Method for Constrained Minimization by Goldfarb, D, Polyak, R, Scheinberg, K, Yuzefovich, I

“…We present and analyze an interior-exterior augmented Lagrangian method for solving constrained optimization problems with both inequality and equality…”
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Comparison of QTc Interval Prolongation for Patients in Methadone Versus Buprenorphine Maintenance Treatment: A 5-Year Follow-Up by Fareed, Ayman, Patil, Dustin, Scheinberg, Kelly, Blackinton Gale, Robin, Vayalapalli, Sreedevi, Casarella, Jennifer, Drexler, Karen

“…The authors investigated whether patients receiving buprenorphine maintenance treatment (BMT) will have corrected QT (QTc) prolongation after taking…”
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Numerically stable LDL[sup]T factorizations in interior point methods for convex quadratic programming by Goldfarb, D, Scheinberg, K

“…Fletcher & Powell (1974, Math. Comput., 28, 1067-1087) proposed a numerically stable method for updating the LDL[sup]T factorization of a symmetric…”
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Geometry of sample sets in derivative-free optimization: polynomial regression and underdetermined interpolation by Conn, Andrew R., Scheinberg, Katya, Vicente, Luís N.

“…In recent years there has been a considerable amount of work on the development of numerical methods for derivative-free optimization problems. Some of this…”
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Map approach to learning sparse Gaussian Markov networks by Bani Asadi, N., Rish, I., Scheinberg, K., Kanevsky, D., Ramabhadran, B.

“…Recently proposed l 1 -regularized maximum-likelihood optimization methods for learning sparse Markov networks result into convex problems that can be solved…”
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Extension of Karmarkar's algorithm onto convex quadratically constrained quadratic problems by NEMIROVSKII, A, SCHEINBERG, K

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Detecting Generic Visual Eventswith Temporal Cues by Lexing Xie, Dong Xu, Ebadollahi, S., Scheinberg, K., Shih-Fu Chang, Smith, J.R.

“…We present novel algorithms for detecting generic visual events from video. Target event models will produce binary decisions on each shot about classes of…”
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Aligning ligand binding cavities by optimizing superposed volume by Ruobing Chen, Scheinberg, K., Chen, B. Y.

“…We describe an optimization-based method that seeks the superposition of ligand binding cavities that maximizes their overlapping volume. Our method, called…”
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