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AND/OR BranchandBound for Solving Mixed Integer Linear Programming Problems
, 2005
"... AND/OR search spaces have recently been introduced as a unifying paradigm for advanced algorithmic schemes for graphical models. The main virtue of this representation is its sensitivity to the structure of the model, which can translate into exponential time savings for search algorithms. In this ..."
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. In this paper we extend the recently introduced AND/OR BranchandBound algorithm [1] for solving 0/1 Mixed Integer Linear Programming problems. We propose a static version based on pseudotrees, as well as a dynamic one based on hypergraph separators. Preliminary evaluation on problem instances from MIPLIB2003
AND/OR BranchandBound for Solving Mixed Integer Linear Programming Problems
"... Abstract. AND/OR search spaces have recently been introduced as a unifying paradigm for advanced algorithmic schemes for graphical models. The main virtue of this representation is its sensitivity to the structure of the model, which can translate into exponential time savings for search algorithms. ..."
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. In this paper we extend the recently introduced AND/OR BranchandBound algorithm [1] for solving 0/1 Mixed Integer Linear Programming problems. We propose a static version based on pseudotrees, as well as a dynamic one based on hypergraph separators. Preliminary evaluation on problem instances from MIPLIB2003
Decoding by Linear Programming
, 2004
"... This paper considers the classical error correcting problem which is frequently discussed in coding theory. We wish to recover an input vector f ∈ Rn from corrupted measurements y = Af + e. Here, A is an m by n (coding) matrix and e is an arbitrary and unknown vector of errors. Is it possible to rec ..."
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Cited by 1399 (16 self)
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for some ρ> 0. In short, f can be recovered exactly by solving a simple convex optimization problem (which one can recast as a linear program). In addition, numerical experiments suggest that this recovery procedure works unreasonably well; f is recovered exactly even in situations where a significant
SelfScheduling of a Hydro Producer in a PoolBased Electricity Market
 IEEE Transactions of Power Systems
, 2002
"... This paper addresses the selfscheduling of a hydro generating company in a poolbased electricity market. This company comprises several cascaded plants along a river basin. The objective is to maximize the profit of the company from selling energy in the dayahead market. This paper proposes a 0/1 ..."
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Cited by 27 (3 self)
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mixedinteger linear programming model to account, in every plant, for the nonlinear and nonconcave threedimensional (3D) relationship between the power produced, the water discharged, and the head of the associated reservoir. Additionally, startup costs due mainly to the wear and tear are considered
Interior Point Methods in Semidefinite Programming with Applications to Combinatorial Optimization
 SIAM Journal on Optimization
, 1993
"... We study the semidefinite programming problem (SDP), i.e the problem of optimization of a linear function of a symmetric matrix subject to linear equality constraints and the additional condition that the matrix be positive semidefinite. First we review the classical cone duality as specialized to S ..."
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Cited by 547 (12 self)
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mechanical way to algorithms for SDP with proofs of convergence and polynomial time complexity also carrying over in a similar fashion. Finally we study the significance of these results in a variety of combinatorial optimization problems including the general 01 integer programs, the maximum clique
TESTS UNDER DIVERSIFICATION
"... This paper focuses on Stochastic Dominance (SD) efficiency in a finite empirical panel data. We analytically characterize the sets of unsorted time series that dominate a given evaluated distribution by the First, Second, and Third order SD. Using these insights, we develop simple Linear Programming ..."
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Programming and 01 Mixed Integer Linear Programming tests of SD efficiency. The advantage to the earlier efficiency tests is that the proposed approach explicitly accounts for diversification. Allowing for diversification can both improve the power of the empirical SD tests, and enable SD based portfolio
Global Optimization of Common Subexpressions for Multiplierless Synthesis of Multiple Constant Multiplications
"... Abstract — In the context of multiple constant multiplication (MCM) design, we propose a novel common subexpression elimination (CSE) algorithm that models the optimal synthesis of coefficients into a 01 mixedinteger linear programming (MILP) problem. A time delay constraint is included for synt ..."
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Cited by 3 (0 self)
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Abstract — In the context of multiple constant multiplication (MCM) design, we propose a novel common subexpression elimination (CSE) algorithm that models the optimal synthesis of coefficients into a 01 mixedinteger linear programming (MILP) problem. A time delay constraint is included
Quadratic Programming for MultiTarget Tracking
 In MSDM Workshop, AAMAS 2009
, 2009
"... We consider the problem of tracking multiple, partially observed targets using multiple sensors arranged in a given configuration. We model the problem as a special case of a (finite horizon) DECPOMDP. We present a quadratic program whose globally optimal solution yields an optimal tracking joint p ..."
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Cited by 1 (0 self)
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policy, one that maximizes the expected targets detected over the given horizon. However, a globally optimal solution to the QP cannot always be found since the QP is nonconvex. To remedy this, we present two linearizations of the QP to equivalent 01 mixed integer linear programs (MIPs) whose optimal
Raptor codes
 IEEE Transactions on Information Theory
, 2006
"... LTCodes are a new class of codes introduced in [1] for the purpose of scalable and faulttolerant distribution of data over computer networks. In this paper we introduce Raptor Codes, an extension of LTCodes with linear time encoding and decoding. We will exhibit a class of universal Raptor codes: ..."
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Cited by 577 (7 self)
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: for a given integer k, and any real ε> 0, Raptor codes in this class produce a potentially infinite stream of symbols such that any subset of symbols of size k(1 + ε) is sufficient to recover the original k symbols with high probability. Each output symbol is generated using O(log(1/ε)) operations
Making LargeScale Support Vector Machine Learning Practical
, 1998
"... Training a support vector machine (SVM) leads to a quadratic optimization problem with bound constraints and one linear equality constraint. Despite the fact that this type of problem is well understood, there are many issues to be considered in designing an SVM learner. In particular, for large lea ..."
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Cited by 628 (1 self)
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learning tasks with many training examples, offtheshelf optimization techniques for general quadratic programs quickly become intractable in their memory and time requirements. SVM light1 is an implementation of an SVM learner which addresses the problem of large tasks. This chapter presents
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