SIAMJO 2008 - PDF Preprint Papers

SIAMJO 2008

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SIAMJO
2008

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Convergence Rate of an Optimization Algorithm for Minimizing Quadratic Functions with Separable Convex Constraints

13 years 10 months ago

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A new active set algorithm for minimizing quadratic functions with separable convex constraints is proposed by combining the conjugate gradient method with the projected gradient. ...

Radek Kucera

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Id	Views	Title	Status

1	212	Convergence Rate of an Optimization Algorithm for Minimizing Quadratic Functions with Separable Convex Constraints	claim
2	175	On Bin Packing with Conflicts	claim
3	144	Embedded in the Shadow of the Separator	claim
4	143	The Proximal Average: Basic Theory	claim
5	141	Constraint Nondegeneracy, Strong Regularity, and Nonsingularity in Semidefinite Programming	claim
6	139	An Augmented Primal-Dual Method for Linear Conic Programs	claim
7	136	Relaxed Alternating Projection Methods	claim
8	117	Two Algorithms for the Minimum Enclosing Ball Problem	claim
9	114	An Inexact SQP Method for Equality Constrained Optimization	claim
10	112	Parallel Space Decomposition of the Mesh Adaptive Direct Search Algorithm	claim
11	110	Subdifferential Calculus Rules in Convex Analysis: A Unifying Approach Via Pointwise Supremum Functions	claim
12	109	A Regularized Smoothing Newton Method for Symmetric Cone Complementarity Problems	claim
13	108	Sparse SOS Relaxations for Minimizing Functions that are Summations of Small Polynomials	claim
14	107	A Short Algebraic Proof of the Farkas Lemma	claim
15	105	On Stability of Multistage Stochastic Programs	claim
16	104	A Minimax Theorem with Applications to Machine Learning, Signal Processing, and Finance	claim
17	100	On the Global Solution of Linear Programs with Linear Complementarity Constraints	claim
18	100	On Extension of Fenchel Duality and its Application	claim
19	99	The Exact Feasibility of Randomized Solutions of Uncertain Convex Programs	claim
20	97	New Formulations for Optimization under Stochastic Dominance Constraints	claim
21	95	Geometric Duality in Multiple Objective Linear Programming	claim
22	93	Stochastic Programs with First-Order Dominance Constraints Induced by Mixed-Integer Linear Recourse	claim
23	93	Recursive Trust-Region Methods for Multiscale Nonlinear Optimization	claim
24	93	Multivariable Utility Functions	claim
25	93	Sufficient Second-Order Optimality Conditions for Semilinear Control Problems with Pointwise State Constraints	claim
26	93	Smooth Optimization with Approximate Gradient	claim
27	92	A Trust Region Spectral Bundle Method for Nonconvex Eigenvalue Optimization	claim
28	92	An Active-Set Newton Method for Mathematical Programs with Complementarity Constraints	claim
29	89	Variational Analysis of Pseudospectra	claim
30	87	Linear Regularity for a Collection of Subsmooth Sets in Banach Spaces	claim
31	86	On the Second-Order Feasibility Cone: Primal-Dual Representation and Efficient Projection	claim
32	86	Semidefinite Relaxation Bounds for Indefinite Homogeneous Quadratic Optimization	claim
33	85	Branch-and-Cut for the Maximum Feasible Subsystem Problem	claim
34	85	Explicit Reformulations for Robust Optimization Problems with General Uncertainty Sets	claim
35	84	Regularity Conditions via Quasi-Relative Interior in Convex Programming	claim
36	82	Primal-Dual Affine Scaling Interior Point Methods for Linear Complementarity Problems	claim
37	81	A First-Order Convergence Analysis of Trust-Region Methods with Inexact Jacobians	claim
38	79	A Class of Interior Proximal-Like Algorithms for Convex Second-Order Cone Programming	claim
39	79	A Class of Inexact Variable Metric Proximal Point Algorithms	claim
40	76	Identification and Elimination of Interior Points for the Minimum Enclosing Ball Problem	claim
41	74	Lagrangian-Dual Functions and Moreau--Yosida Regularization	claim
42	72	A Sample Approximation Approach for Optimization with Probabilistic Constraints	claim
43	66	Further Relaxations of the Semidefinite Programming Approach to Sensor Network Localization	claim
44	57	Universal Confidence Sets for Solutions of Optimization Problems	claim
45	56	Iterative Minimization Schemes for Solving the Single Source Localization Problem	claim
46	53	A New Unblocking Technique to Warmstart Interior Point Methods Based on Sensitivity Analysis	claim
47	47	On Semidefinite Programming Relaxations of the Traveling Salesman Problem	claim

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