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A Guided Tour to Approximate String Matching

by Gonzalo Navarro - ACM COMPUTING SURVEYS , 1999
"... We survey the current techniques to cope with the problem of string matching allowing errors. This is becoming a more and more relevant issue for many fast growing areas such as information retrieval and computational biology. We focus on online searching and mostly on edit distance, explaining t ..."
Abstract - Cited by 598 (36 self) - Add to MetaCart
We survey the current techniques to cope with the problem of string matching allowing errors. This is becoming a more and more relevant issue for many fast growing areas such as information retrieval and computational biology. We focus on online searching and mostly on edit distance, explaining

An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision

by Yuri Boykov, Vladimir Kolmogorov - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2001
"... After [10, 15, 12, 2, 4] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in low-level vision. The combinatorial optimization literature provides many min-cut/max-flow algorithms with different polynomial time compl ..."
Abstract - Cited by 1315 (53 self) - Add to MetaCart
After [10, 15, 12, 2, 4] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in low-level vision. The combinatorial optimization literature provides many min-cut/max-flow algorithms with different polynomial time

A training algorithm for optimal margin classifiers

by Bernhard E. Boser, et al. - PROCEEDINGS OF THE 5TH ANNUAL ACM WORKSHOP ON COMPUTATIONAL LEARNING THEORY , 1992
"... A training algorithm that maximizes the margin between the training patterns and the decision boundary is presented. The technique is applicable to a wide variety of classifiaction functions, including Perceptrons, polynomials, and Radial Basis Functions. The effective number of parameters is adjust ..."
Abstract - Cited by 1865 (43 self) - Add to MetaCart
is adjusted automatically to match the complexity of the problem. The solution is expressed as a linear combination of supporting patterns. These are the subset of training patterns that are closest to the decision boundary. Bounds on the generalization performance based on the leave-one-out method and the VC

Large margin methods for structured and interdependent output variables

by Ioannis Tsochantaridis, Thorsten Joachims, Thomas Hofmann, Yasemin Altun - JOURNAL OF MACHINE LEARNING RESEARCH , 2005
"... Learning general functional dependencies between arbitrary input and output spaces is one of the key challenges in computational intelligence. While recent progress in machine learning has mainly focused on designing flexible and powerful input representations, this paper addresses the complementary ..."
Abstract - Cited by 624 (12 self) - Add to MetaCart
the complementary issue of designing classification algorithms that can deal with more complex outputs, such as trees, sequences, or sets. More generally, we consider problems involving multiple dependent output variables, structured output spaces, and classification problems with class attributes. In order

The Structure-Mapping Engine: Algorithm and Examples

by Brian Falkenhainer, Kenneth D. Forbus, Dedre Gentner - Artificial Intelligence , 1989
"... This paper describes the Structure-Mapping Engine (SME), a program for studying analogical processing. SME has been built to explore Gentner's Structure-mapping theory of analogy, and provides a "tool kit" for constructing matching algorithms consistent with this theory. Its flexibili ..."
Abstract - Cited by 522 (116 self) - Add to MetaCart
This paper describes the Structure-Mapping Engine (SME), a program for studying analogical processing. SME has been built to explore Gentner's Structure-mapping theory of analogy, and provides a "tool kit" for constructing matching algorithms consistent with this theory. Its

Dynamic Bayesian Networks: Representation, Inference and Learning

by Kevin Patrick Murphy , 2002
"... Modelling sequential data is important in many areas of science and engineering. Hidden Markov models (HMMs) and Kalman filter models (KFMs) are popular for this because they are simple and flexible. For example, HMMs have been used for speech recognition and bio-sequence analysis, and KFMs have bee ..."
Abstract - Cited by 770 (3 self) - Add to MetaCart
) space instead of O(T); a simple way of using the junction tree algorithm for online inference in DBNs; new complexity bounds on exact online inference in DBNs; a new deterministic approximate inference algorithm called factored frontier; an analysis of the relationship between the BK algorithm and loopy

A general approximation technique for constrained forest problems

by Michel X. Goemans, David P. Williamson - SIAM J. COMPUT. , 1995
"... We present a general approximation technique for a large class of graph problems. Our technique mostly applies to problems of covering, at minimum cost, the vertices of a graph with trees, cycles, or paths satisfying certain requirements. In particular, many basic combinatorial optimization proble ..."
Abstract - Cited by 414 (21 self) - Add to MetaCart
of these problems. For instance, we obtain a 2-approximation algorithm for the minimum-weight perfect matching problem under the triangle inequality. Our running time of O(n log n) time compares favorably with the best strongly polynomial exact algorithms running in O(n 3) time for dense graphs. A similar result

Approximating the permanent

by Mark Jerrum, Alistair Sinclair - SIAM J. Computing , 1989
"... Abstract. A randomised approximation scheme for the permanent of a 0-1 matrix is presented. The task of estimating a permanent is reduced to that of almost uniformly generating perfect matchings in a graph; the latter is accomplished by simulating a Markov chain whose states are the matchings in the ..."
Abstract - Cited by 345 (26 self) - Add to MetaCart
to demonstrating that the matchings chain is rapidly mixing, apparently the first such result for a Markov chain with genuinely complex structure. The techniques used seem to have general applicability, and are applied again in the paper to validate a fully-polynomial randomised approximation scheme

Weighted polynomial approximation in the complex plane

by Igor E. Pritsker, Richard S. Varga - CONSTR. APPROX , 1996
"... Given a pair (G, W) of an open bounded set G in the complex plane and a weight function W (z) which is analytic and different from zero in G, we consider the problem of the locally uniform approximation of any function f(z), which is analytic in G, by weighted polynomials of the form {W n (z)Pn(z) ..."
Abstract - Cited by 7 (6 self) - Add to MetaCart
Given a pair (G, W) of an open bounded set G in the complex plane and a weight function W (z) which is analytic and different from zero in G, we consider the problem of the locally uniform approximation of any function f(z), which is analytic in G, by weighted polynomials of the form {W n (z

Shock Graphs and Shape Matching

by Kaleem Siddiqi, Ali Shokoufandeh, Sven J. Dickinson, Steven W. Zucker , 1997
"... We have been developing a theory for the generic representation of 2-D shape, where structural descriptions are derived from the shocks (singularities) of a curve evolution process, acting on bounding contours. We now apply the theory to the problem of shape matching. The shocks are organized into a ..."
Abstract - Cited by 269 (35 self) - Add to MetaCart
unique rooted shock tree. We introduce a novel tree matching algorithm which finds the best set of corresponding nodes between two shock trees in polynomial time. Using a diverse database of shapes, we demonstrate our system's performance under articulation, occlusion, and changes in viewpoint.
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