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Wrappers for Feature Subset Selection

by Ron Kohavi, George H. John - AIJ SPECIAL ISSUE ON RELEVANCE , 1997
"... In the feature subset selection problem, a learning algorithm is faced with the problem of selecting a relevant subset of features upon which to focus its attention, while ignoring the rest. To achieve the best possible performance with a particular learning algorithm on a particular training set, a ..."
Abstract - Cited by 1569 (3 self) - Add to MetaCart
the strengths and weaknesses of the wrapper approach andshow a series of improved designs. We compare the wrapper approach to induction without feature subset selection and to Relief, a filter approach to feature subset selection. Significant improvement in accuracy is achieved for some datasets for the two

Bagging predictors

by LEO BREIMAN , 1996
"... Bagging predictors is a method for generating multiple versions of a predictor and using these to get an aggregated predictor. The aggregation averages over the versions when predicting a numerical outcome and does a plurality vote when predicting a class. The multiple versions are formed by making ..."
Abstract - Cited by 3650 (1 self) - Add to MetaCart
by making bootstrap replicates of the learning set and using these as new learning sets. Tests on real and simulated data sets using classification and regression trees and subset selection in linear regression show that bagging can give substantial gains in accuracy. The vital element is the instability

Robust wide baseline stereo from maximally stable extremal regions

by J. Matas, O. Chum, M. Urban, T. Pajdla - In Proc. BMVC , 2002
"... The wide-baseline stereo problem, i.e. the problem of establishing correspon-dences between a pair of images taken from different viewpoints is studied. A new set of image elements that are put into correspondence, the so called extremal regions, is introduced. Extremal regions possess highly de-sir ..."
Abstract - Cited by 1016 (35 self) - Add to MetaCart
subset of extremal regions, the maximally stable extremal regions (MSER). A new robust similarity measure for establishing tentative correspon-dences is proposed. The robustness ensures that invariants from multiple measurement regions (regions obtained by invariant constructions from ex-tremal regions

Maximizing the Spread of Influence Through a Social Network

by David Kempe - In KDD , 2003
"... Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technological innovations, the sudden and widespread adoption of various strategies in game-theoretic settings, and the effects of ..."
Abstract - Cited by 990 (7 self) - Add to MetaCart
of “word of mouth ” in the promotion of new products. Recently, motivated by the design of viral marketing strategies, Domingos and Richardson posed a fundamental algorithmic problem for such social network processes: if we can try to convince a subset of individuals to adopt a new product or innovation

Loopy belief propagation for approximate inference: An empirical study. In:

by Kevin P Murphy , Yair Weiss , Michael I Jordan - Proceedings of Uncertainty in AI, , 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" -the use of Pearl's polytree algorithm in a Bayesian network with loops -can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon-limit performanc ..."
Abstract - Cited by 676 (15 self) - Add to MetaCart
the parents of each symptom were a random subset of the diseases. terior marginals of all other nodes. Again we found that loopy belief propagation always converged with the average number of iterations equal to 14.55. The results presented up until now show that loopy propagation performs well for a variety

Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis

by Theresa Wilson - In Proceedings of HLT-EMNLP , 2005
"... This paper presents a new approach to phrase-level sentiment analysis that first determines whether an expression is neutral or polar and then disambiguates the polarity of the polar expressions. With this approach, the system is able to automatically identify the contextual polarity for a large sub ..."
Abstract - Cited by 454 (15 self) - Add to MetaCart
subset of sentiment expressions, achieving results that are significantly better than baseline. 1

A general framework for object detection

by Constantine P. Papageorgiou, Michael Oren, Tomaso Poggio - Sixth International Conference on , 1998
"... This paper presents a general trainable framework for object detection in static images of cluttered scenes. The detection technique we develop is based on a wavelet representation of an object class derived from a statistical analysis of the class instances. By learning an object class in terms of ..."
Abstract - Cited by 395 (21 self) - Add to MetaCart
of a subset of an overcomplete dictionary of wavelet basis functions, we derive a compact representation of an object class which is used as an input to a suppori vector machine classifier. This representation overcomes both the problem of in-class variability and provides a low false detection rate

Discovering Statistically Significant Biclusters in Gene Expression Data

by Amos Tanay, Roded Sharan, Ron Shamir - In Proceedings of ISMB 2002 , 2002
"... In gene expression data, a bicluster is a subset of the genes exhibiting consistent patterns over a subset of the conditions. We propose a new method to detect significant biclusters in large expression datasets. Our approach is graph theoretic coupled with statistical modelling of the data. Under p ..."
Abstract - Cited by 302 (4 self) - Add to MetaCart
In gene expression data, a bicluster is a subset of the genes exhibiting consistent patterns over a subset of the conditions. We propose a new method to detect significant biclusters in large expression datasets. Our approach is graph theoretic coupled with statistical modelling of the data. Under

The Role of Information and Social Interactions in Retirement Plan Decisions: Evidence From a Randomized Experiment

by Esther Duflo, Emmanuel Saez , 2002
"... This paper analyzes a randomized experiment to shed light on the role of information and social interactions in employees’ decisions to enroll in a Tax Deferred Account (TDA) retirement plan within a large university. The experiment encouraged a random sample of employees in a subset of department ..."
Abstract - Cited by 375 (10 self) - Add to MetaCart
This paper analyzes a randomized experiment to shed light on the role of information and social interactions in employees’ decisions to enroll in a Tax Deferred Account (TDA) retirement plan within a large university. The experiment encouraged a random sample of employees in a subset

An evolutionary trace method defines binding surfaces common to protein families

by Olivier Lichtarge, Henry R. Bourne, Fred E. Cohen - J. Mol. Biol , 1996
"... 1Departments of Cellular and X-ray or NMR structures of proteins are often derived without their Molecular Pharmacology and ligands, and even when the structure of a full complex is available, the area Medicine and of contact that is functionally and energetically significant may be a 2Department of ..."
Abstract - Cited by 355 (31 self) - Add to MetaCart
1Departments of Cellular and X-ray or NMR structures of proteins are often derived without their Molecular Pharmacology and ligands, and even when the structure of a full complex is available, the area Medicine and of contact that is functionally and energetically significant may be a 2Department
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