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1,580
A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization
, 1997
"... The Rocchio relevance feedback algorithm is one of the most popular and widely applied learning methods from information retrieval. Here, a probabilistic analysis of this algorithm is presented in a text categorization framework. The analysis gives theoretical insight into the heuristics used in the ..."
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Cited by 456 (1 self)
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The Rocchio relevance feedback algorithm is one of the most popular and widely applied learning methods from information retrieval. Here, a probabilistic analysis of this algorithm is presented in a text categorization framework. The analysis gives theoretical insight into the heuristics used
Unsupervised Learning of the Morphology of a Natural Language
 COMPUTATIONAL LINGUISTICS
, 2001
"... This study reports the results of using minimum description length (MDL) analysis to model unsupervised learning of the morphological segmentation of European languages, using corpora ranging in size from 5,000 words to 500,000 words. We develop a set of heuristics that rapidly develop a probabilist ..."
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Cited by 355 (12 self)
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probabilistic morphological grammar, and use MDL as our primary tool to determine whether the modifications proposed by the heuristics will be adopted or not. The resulting grammar matches well the analysis that would be developed by a human morphologist. In the final section, we discuss the relationship
Coding, Analysis, Interpretation, and Recognition of Facial Expressions
, 1997
"... We describe a computer vision system for observing facial motion by using an optimal estimation optical flow method coupled with geometric, physical and motionbased dynamic models describing the facial structure. Our method produces a reliable parametric representation of the face's independen ..."
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Cited by 331 (6 self)
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use of this heuristic coding scheme, we have used our computer vision system to probabilistically characterize facial motion and muscle activation in an experimental population, thus deriving a new, more accurate representation of human facial expressions that we call FACS+. Finally, we show how
Progressivemauve: multiple genome alignment with gene gain, loss and rearrangement
 Article ID e11147
, 2010
"... Background: Multiple genome alignment remains a challenging problem. Effects of recombination including rearrangement, segmental duplication, gain, and loss can create a mosaic pattern of homology even among closely related organisms. Methodology/Principal Findings: We describe a new method to align ..."
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Cited by 272 (3 self)
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. The method uses a novel alignment objective score called a sumofpairs breakpoint score, which facilitates accurate detection of rearrangement breakpoints when genomes have unequal gene content. We also apply a probabilistic alignment filtering method to remove erroneous alignments of unrelated sequences
Probabilistic Analysis Of Two Heuristics For The 3Satisfiability Problem
 SIAM JOURNAL ON COMPUTING
, 1986
"... An algorithm for the 3Satisfiability problem is presented and a probabilistic analysis is performed. The analysis is based on an instance distribution which is parameterized to simulate a variety of sample characteristics. The algorithm assigns values to variables appearing in a given instance of 3 ..."
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Cited by 78 (11 self)
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An algorithm for the 3Satisfiability problem is presented and a probabilistic analysis is performed. The analysis is based on an instance distribution which is parameterized to simulate a variety of sample characteristics. The algorithm assigns values to variables appearing in a given instance
Hidden Markov models for sequence analysis: extension and analysis of the basic method
, 1996
"... Hidden Markov models (HMMs) are a highly effective means of modeling a family of unaligned sequences or a common motif within a set of unaligned sequences. The trained HMM can then be used for discrimination or multiple alignment. The basic mathematical description of an HMM and its expectationmaxi ..."
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Cited by 219 (23 self)
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Hidden Markov models (HMMs) are a highly effective means of modeling a family of unaligned sequences or a common motif within a set of unaligned sequences. The trained HMM can then be used for discrimination or multiple alignment. The basic mathematical description of an HMM and its expectation
Analysis Of Two Simple Heuristics On A Random Instance Of kSAT
 Journal of Algorithms
, 1996
"... We consider the performance of two algorithms, GUC and SC studied by Chao and Franco [2], [3], and Chv'atal and Reed [4], when applied to a random instance ! of a boolean formula in conjunctive normal form with n variables and bcnc clauses of size k each. For the case where k = 3, we obtain th ..."
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Cited by 147 (4 self)
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Given a boolean formula ! in conjunctive normal form, the satisfiability problem (sat) is to determine whether there is a truth assignment that satisfies !. Since sat is NPcomplete, one is interested in efficient heuristics that perform well "on average," or with high probability. The choice
A Probabilistic Approach to Feature Selection  A Filter Solution
"... Feature selection can be defined as a problem of finding a minimum set of M relevant attributes that describes the dataset as well as the original N attributes do, where M N . After examining the problems with both the exhaustive and the heuristic approach to feature selection, this paper pro ..."
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Cited by 157 (13 self)
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proposes a probabilistic approach. The theoretic analysis and the experimental study show that the proposed approach is simple to implement and guaranteed to find the optimal if resources permit. It is also fast in obtaining results and effective in selecting features that improve the performance
Mellin Transforms And Asymptotics: Harmonic Sums
 THEORETICAL COMPUTER SCIENCE
, 1995
"... This survey presents a unified and essentially selfcontained approach to the asymptotic analysis of a large class of sums that arise in combinatorial mathematics, discrete probabilistic models, and the averagecase analysis of algorithms. It relies on the Mellin transform, a close relative of the i ..."
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Cited by 202 (12 self)
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This survey presents a unified and essentially selfcontained approach to the asymptotic analysis of a large class of sums that arise in combinatorial mathematics, discrete probabilistic models, and the averagecase analysis of algorithms. It relies on the Mellin transform, a close relative
Probabilistic Analysis Of A Generalization Of The Unit Clause Literal Selection Heuristic For The KSatisfiability Problem
 INFORMATION SCIENCE
, 1990
"... Two algorithms for the kSatisfiability problem are presented and a probabilistic analysis is performed. The analysis is based on an instance distribution which is parameterized to simulate a variety of sample characteristics. The algorithms assign values to literals appearing in a given instance of ..."
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Cited by 104 (11 self)
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Two algorithms for the kSatisfiability problem are presented and a probabilistic analysis is performed. The analysis is based on an instance distribution which is parameterized to simulate a variety of sample characteristics. The algorithms assign values to literals appearing in a given instance
Results 1  10
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1,580