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A New Algorithm for Normal Dominance Constraints
 In Proc. SODA
, 2003
"... this paper, we propose a novel graph algorithm relying on graph connectivity, and inspired by [3]. It can enumerate all solved forms of a normal dominance constraint 2 ) per solved form, and thereby improves on the best previously known algorithm in e#ciency. # Humboldt Universitat zu Berlin, Germa ..."
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Cited by 16 (5 self)
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this paper, we propose a novel graph algorithm relying on graph connectivity, and inspired by [3]. It can enumerate all solved forms of a normal dominance constraint 2 ) per solved form, and thereby improves on the best previously known algorithm in e#ciency. # Humboldt Universitat zu Berlin
A New Algorithm for Normal Dominance Constraints
 ACMSIAM SYMPOSIUM ON DISCRETE ALGORITHMS SODA'2003 (2004) 5967
, 2004
"... Dominance constraints are logical descriptions of trees. Efficient algorithms for the subclass of normal dominance constraints were recently proposed. We present a new and simpler graph algorithm solving these constraints more efficiently, in quadratic time per solved form. It also applies to weakly ..."
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Dominance constraints are logical descriptions of trees. Efficient algorithms for the subclass of normal dominance constraints were recently proposed. We present a new and simpler graph algorithm solving these constraints more efficiently, in quadratic time per solved form. It also applies
The geometry of algorithms with orthogonality constraints
 SIAM J. MATRIX ANAL. APPL
, 1998
"... In this paper we develop new Newton and conjugate gradient algorithms on the Grassmann and Stiefel manifolds. These manifolds represent the constraints that arise in such areas as the symmetric eigenvalue problem, nonlinear eigenvalue problems, electronic structures computations, and signal proces ..."
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Cited by 642 (1 self)
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In this paper we develop new Newton and conjugate gradient algorithms on the Grassmann and Stiefel manifolds. These manifolds represent the constraints that arise in such areas as the symmetric eigenvalue problem, nonlinear eigenvalue problems, electronic structures computations, and signal
An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
, 2008
"... ..."
Constraint Networks
, 1992
"... Constraintbased reasoning is a paradigm for formulating knowledge as a set of constraints without specifying the method by which these constraints are to be satisfied. A variety of techniques have been developed for finding partial or complete solutions for different kinds of constraint expression ..."
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Cited by 1149 (43 self)
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Constraintbased reasoning is a paradigm for formulating knowledge as a set of constraints without specifying the method by which these constraints are to be satisfied. A variety of techniques have been developed for finding partial or complete solutions for different kinds of constraint
Concurrent Constraint Programming
, 1993
"... This paper presents a new and very rich class of (concurrent) programming languages, based on the notion of comput.ing with parhal information, and the concommitant notions of consistency and entailment. ’ In this framework, computation emerges from the interaction of concurrently executing agent ..."
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Cited by 502 (16 self)
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This paper presents a new and very rich class of (concurrent) programming languages, based on the notion of comput.ing with parhal information, and the concommitant notions of consistency and entailment. ’ In this framework, computation emerges from the interaction of concurrently executing
Experiments with a New Boosting Algorithm
, 1996
"... In an earlier paper, we introduced a new “boosting” algorithm called AdaBoost which, theoretically, can be used to significantly reduce the error of any learning algorithm that consistently generates classifiers whose performance is a little better than random guessing. We also introduced the relate ..."
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Cited by 2176 (21 self)
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In an earlier paper, we introduced a new “boosting” algorithm called AdaBoost which, theoretically, can be used to significantly reduce the error of any learning algorithm that consistently generates classifiers whose performance is a little better than random guessing. We also introduced
Planning Algorithms
, 2004
"... This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning ..."
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Cited by 1108 (51 self)
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This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning
Efficient Variants of the ICP Algorithm
 INTERNATIONAL CONFERENCE ON 3D DIGITAL IMAGING AND MODELING
, 2001
"... The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of threedimensional models when an initial estimate of the relative pose is known. Many variants of ICP have been proposed, affecting all phases of the algorithm from the selection and matching of points to the minim ..."
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Cited by 702 (5 self)
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to the minimization strategy. We enumerate and classify many of these variants, and evaluate their effect on the speed with which the correct alignment is reached. In order to improve convergence for nearlyflat meshes with small features, such as inscribed surfaces, we introduce a new variant based on uniform
A learning algorithm for Boltzmann machines
 Cognitive Science
, 1985
"... The computotionol power of massively parallel networks of simple processing elements resides in the communication bandwidth provided by the hardware connections between elements. These connections con allow a significant fraction of the knowledge of the system to be applied to an instance of a probl ..."
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Cited by 586 (13 self)
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problem in o very short time. One kind of computation for which massively porollel networks appear to be well suited is large constraint satisfaction searches, but to use the connections efficiently two conditions must be met: First, a search technique that is suitable for parallel networks must be found
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