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Random forests

by Leo Breiman, E. Schapire - Machine Learning , 2001
"... Abstract. Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees in the fo ..."
Abstract - Cited by 3613 (2 self) - Add to MetaCart
Abstract. Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees

Inducing Features of Random Fields

by Stephen Della Pietra, Vincent Della Pietra, John Lafferty - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 1997
"... We present a technique for constructing random fields from a set of training samples. The learning paradigm builds increasingly complex fields by allowing potential functions, or features, that are supported by increasingly large subgraphs. Each feature has a weight that is trained by minimizing the ..."
Abstract - Cited by 670 (10 self) - Add to MetaCart
the Kullback-Leibler divergence between the model and the empirical distribution of the training data. A greedy algorithm determines how features are incrementally added to the field and an iterative scaling algorithm is used to estimate the optimal values of the weights. The random field models and techniques

Mining the Network Value of Customers

by Pedro Domingos, Matt Richardson - In Proceedings of the Seventh International Conference on Knowledge Discovery and Data Mining , 2002
"... One of the major applications of data mining is in helping companies determine which potential customers to market to. If the expected pro t from a customer is greater than the cost of marketing to her, the marketing action for that customer is executed. So far, work in this area has considered only ..."
Abstract - Cited by 568 (11 self) - Add to MetaCart
as a set of independent entities, we view it as a social network and model it as a Markov random eld. We show the advantages of this approach using a social network mined from a collaborative ltering database. Marketing that exploits the network value of customers|also known as viral marketing

Improved Approximation Algorithms for Maximum Cut and Satisfiability Problems Using Semidefinite Programming

by M. X. Goemans, D.P. Williamson - Journal of the ACM , 1995
"... We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2-satisfiability (MAX 2SAT) problems that always deliver solutions of expected value at least .87856 times the optimal value. These algorithms use a simple and elegant technique that randomly rounds the solution ..."
Abstract - Cited by 1211 (13 self) - Add to MetaCart
We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2-satisfiability (MAX 2SAT) problems that always deliver solutions of expected value at least .87856 times the optimal value. These algorithms use a simple and elegant technique that randomly rounds

Where the REALLY Hard Problems Are

by Peter Cheeseman, Bob Kanefsky, William M. Taylor - IN J. MYLOPOULOS AND R. REITER (EDS.), PROCEEDINGS OF 12TH INTERNATIONAL JOINT CONFERENCE ON AI (IJCAI-91),VOLUME 1 , 1991
"... It is well known that for many NP-complete problems, such as K-Sat, etc., typical cases are easy to solve; so that computationally hard cases must be rare (assuming P != NP). This paper shows that NP-complete problems can be summarized by at least one "order parameter", and that the hard p ..."
Abstract - Cited by 683 (1 self) - Add to MetaCart
problems occur at a critical value of such a parameter. This critical value separates two regions of characteristically different properties. For example, for K-colorability, the critical value separates overconstrained from underconstrained random graphs, and it marks the value at which the probability

Random values of the cosmological constant

by John F. Donoghue - JHEP 0008,022 (2000) , hep-ph/0006088
"... One way that an anthropic selection mechanism may be manifest in a physical theory involves multiple domains in the universe with different values of the physical parameters. If this mechanism is to be relevant for understanding the small observed value of the cosmological constant, it may involve a ..."
Abstract - Cited by 5 (2 self) - Add to MetaCart
interesting possibility involves fixed random values of non-dynamical form fields, and a cosmological mechanism is suggested. This case raises the possibility of anthropic selection of other parameters in addition. Further requirements needed for a consistent cosmology are discussed. The problem

Stochastic Perturbation Theory

by G. W. Stewart , 1988
"... . In this paper classical matrix perturbation theory is approached from a probabilistic point of view. The perturbed quantity is approximated by a first-order perturbation expansion, in which the perturbation is assumed to be random. This permits the computation of statistics estimating the variatio ..."
Abstract - Cited by 907 (36 self) - Add to MetaCart
and the eigenvalue problem. Key words. perturbation theory, random matrix, linear system, least squares, eigenvalue, eigenvector, invariant subspace, singular value AMS(MOS) subject classifications. 15A06, 15A12, 15A18, 15A52, 15A60 1. Introduction. Let A be a matrix and let F be a matrix valued function of A

Experimental Tests of the Endowment Effect and the Coase Theorem,”

by Daniel Kahneman , Jack L Knetsch , Richard H Thaler - Journal of Political Economy, , 1990
"... Contrary to theoretical expectations, measures of willingness to accept greatly exceed measures of willingness to pay. This paper reports several experiments that demonstrate that this "endowment effect" persists even in market settings with opportunities to learn. Consumption objects (e. ..."
Abstract - Cited by 677 (25 self) - Add to MetaCart
.g., coffee mugs) are randomly given to half the subjects in an experiment. Markets for the mugs are then conducted. The Coase theorem predicts that about half the mugs will trade, but observed volume is always significantly less. When markets for "induced-value" tokens are conducted, the predicted

Empirical exchange rate models of the Seventies: do they fit out of sample?

by Richard A. Meese, Kenneth Rogoff - JOURNAL OF INTERNATIONAL ECONOMICS , 1983
"... This study compares the out-of-sample forecasting accuracy of various structural and time series exchange rate models. We find that a random walk model performs as well as any estimated model at one to twelve month horizons for the dollar/pound, dollar/mark, dollar/yen and trade-weighted dollar exch ..."
Abstract - Cited by 854 (12 self) - Add to MetaCart
This study compares the out-of-sample forecasting accuracy of various structural and time series exchange rate models. We find that a random walk model performs as well as any estimated model at one to twelve month horizons for the dollar/pound, dollar/mark, dollar/yen and trade-weighted dollar

Image denoising using a scale mixture of Gaussians in the wavelet domain

by Javier Portilla, Vasily Strela, Martin J. Wainwright, Eero P. Simoncelli - IEEE TRANS IMAGE PROCESSING , 2003
"... We describe a method for removing noise from digital images, based on a statistical model of the coefficients of an overcomplete multiscale oriented basis. Neighborhoods of coefficients at adjacent positions and scales are modeled as the product of two independent random variables: a Gaussian vecto ..."
Abstract - Cited by 513 (17 self) - Add to MetaCart
We describe a method for removing noise from digital images, based on a statistical model of the coefficients of an overcomplete multiscale oriented basis. Neighborhoods of coefficients at adjacent positions and scales are modeled as the product of two independent random variables: a Gaussian
Results 1 - 10 of 24,568