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1,721,015
The minimumentropy set cover problem
 Theoret. Comput. Sci
, 2005
"... Abstract. We consider the minimum entropy principle for learning datagenerated by a random source and observed with random noise. In our setting we have a sequence of observations of objects drawn uniformly at random from a population. Each object in the population belongs to one class. We perform ..."
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Cited by 17 (1 self)
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Abstract. We consider the minimum entropy principle for learning datagenerated by a random source and observed with random noise. In our setting we have a sequence of observations of objects drawn uniformly at random from a population. Each object in the population belongs to one class. We perform
Tight results on minimum entropy set cover
 In 9th. International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX
, 2006
"... In the minimum entropy set cover problem, one is given a collection of k sets which collectively cover an nelement ground set. A feasible solution of the problem is a partition of the ground set into parts such that each part is included in some of the k given sets. Such a partition defines a proba ..."
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Cited by 13 (5 self)
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In the minimum entropy set cover problem, one is given a collection of k sets which collectively cover an nelement ground set. A feasible solution of the problem is a partition of the ground set into parts such that each part is included in some of the k given sets. Such a partition defines a
Minimum Entropy Orientations ∗
, 802
"... We study graph orientations that minimize the entropy of the indegree sequence. The problem of finding such an orientation is an interesting special case of the minimum entropy set cover problem previously studied by Halperin and Karp (Theoret. Comput. Sci., 2005) and by the current authors (Algori ..."
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Cited by 4 (1 self)
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We study graph orientations that minimize the entropy of the indegree sequence. The problem of finding such an orientation is an interesting special case of the minimum entropy set cover problem previously studied by Halperin and Karp (Theoret. Comput. Sci., 2005) and by the current authors
A Threshold of ln n for Approximating Set Cover
 JOURNAL OF THE ACM
, 1998
"... Given a collection F of subsets of S = f1; : : : ; ng, set cover is the problem of selecting as few as possible subsets from F such that their union covers S, and max kcover is the problem of selecting k subsets from F such that their union has maximum cardinality. Both these problems are NPhar ..."
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Cited by 778 (5 self)
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Given a collection F of subsets of S = f1; : : : ; ng, set cover is the problem of selecting as few as possible subsets from F such that their union covers S, and max kcover is the problem of selecting k subsets from F such that their union has maximum cardinality. Both these problems are NP
A MinimumEntropy Algorithm for Surface Phasing Problems
, 1997
"... Methods of determining the phases for noisy and incomplete surface diffraction data (Xray or transmission electron) are investigated. It is found that, while conventional methods do not always work, a minimumentropy method that uses the relative entropy is more effective in finding the correct solu ..."
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Methods of determining the phases for noisy and incomplete surface diffraction data (Xray or transmission electron) are investigated. It is found that, while conventional methods do not always work, a minimumentropy method that uses the relative entropy is more effective in finding the correct
A minimumentropy procedure for robust motion estimation
 In ICIP, Atlanta, GA
, 2006
"... We focus on motion estimation using a block matching approach and suggest using a minimumentropy criterion. Many entropybased estimation procedures exist, such as plugin estimators based on Parzen windowing. We consider here an alternative that is applicable to data of any dimension and that circ ..."
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Cited by 6 (6 self)
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We focus on motion estimation using a block matching approach and suggest using a minimumentropy criterion. Many entropybased estimation procedures exist, such as plugin estimators based on Parzen windowing. We consider here an alternative that is applicable to data of any dimension
Shape modeling with front propagation: A level set approach
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1995
"... Abstract Shape modeling is an important constituent of computer vision as well as computer graphics research. Shape models aid the tasks of object representation and recognition. This paper presents a new approach to shape modeling which retains some of the attractive features of existing methods ..."
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Cited by 804 (20 self)
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secting, hypersurface flowing along its gradient field with constant speed or a speed that depends on the curvature. It is moved by solving a “HamiltonJacob? ’ type equation written for a function in which the interface is a particular level set. A speed term synthesizpd from the image is used to stop the interface
The Hungarian method for the assignment problem
 Naval Res. Logist. Quart
, 1955
"... Assuming that numerical scores are available for the performance of each of n persons on each of n jobs, the "assignment problem" is the quest for an assignment of persons to jobs so that the sum of the n scores so obtained is as large as possible. It is shown that ideas latent in the work ..."
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Cited by 1238 (0 self)
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Assuming that numerical scores are available for the performance of each of n persons on each of n jobs, the "assignment problem" is the quest for an assignment of persons to jobs so that the sum of the n scores so obtained is as large as possible. It is shown that ideas latent
Solving multiclass learning problems via errorcorrecting output codes
 JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
, 1995
"... Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass l ..."
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Cited by 730 (8 self)
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Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass
Results 1  10
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1,721,015