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A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization

by Thorsten Joachims , 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 ..."
Abstract - Cited by 456 (1 self) - Add to MetaCart
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

by John Goldsmith - 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 ..."
Abstract - Cited by 355 (12 self) - Add to MetaCart
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

by Irfan A. Essa , 1997
"... We describe a computer vision system for observing facial motion by using an optimal estimation optical flow method coupled with geometric, physical and motion-based dynamic models describing the facial structure. Our method produces a reliable parametric representation of the face's independen ..."
Abstract - Cited by 331 (6 self) - Add to MetaCart
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

by Aaron E. Darling, Bob Mau, Nicole T. Perna - 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 ..."
Abstract - Cited by 272 (3 self) - Add to MetaCart
. The method uses a novel alignment objective score called a sum-of-pairs 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 3-Satisfiability Problem

by Ming-Te Chao , John Franco - SIAM JOURNAL ON COMPUTING , 1986
"... An algorithm for the 3-Satisfiability 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 ..."
Abstract - Cited by 78 (11 self) - Add to MetaCart
An algorithm for the 3-Satisfiability 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

by Richard Hughey, Anders Krogh , 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 expectation-maxi ..."
Abstract - Cited by 219 (23 self) - Add to MetaCart
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 k-SAT

by Alan Frieze, Stephen Suen - 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 ..."
Abstract - Cited by 147 (4 self) - Add to MetaCart
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 NP-complete, 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

by Huan Liu, Rudy Setiono
"... 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 ..."
Abstract - Cited by 157 (13 self) - Add to MetaCart
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

by Philippe Flajolet, Xavier Gourdon, Philippe Dumas - THEORETICAL COMPUTER SCIENCE , 1995
"... This survey presents a unified and essentially self-contained approach to the asymptotic analysis of a large class of sums that arise in combinatorial mathematics, discrete probabilistic models, and the average-case analysis of algorithms. It relies on the Mellin transform, a close relative of the i ..."
Abstract - Cited by 202 (12 self) - Add to MetaCart
This survey presents a unified and essentially self-contained approach to the asymptotic analysis of a large class of sums that arise in combinatorial mathematics, discrete probabilistic models, and the average-case 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 K-Satisfiability Problem

by Min-te Chao, John Franco - INFORMATION SCIENCE , 1990
"... Two algorithms for the k-Satisfiability 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 ..."
Abstract - Cited by 104 (11 self) - Add to MetaCart
Two algorithms for the k-Satisfiability 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
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