Results 1 - 10 of 55,734

The Nature of Statistical Learning Theory

by Vladimir N. Vapnik , 1999
"... Statistical learning theory was introduced in the late 1960’s. Until the 1990’s it was a purely theoretical analysis of the problem of function estimation from a given collection of data. In the middle of the 1990’s new types of learning algorithms (called support vector machines) based on the deve ..."
Abstract - Cited by 13236 (32 self) - Add to MetaCart
on the developed theory were proposed. This made statistical learning theory not only a tool for the theoretical analysis but also a tool for creating practical algorithms for estimating multidimensional functions. This article presents a very general overview of statistical learning theory including both

Generalized Autoregressive Conditional Heteroskedasticity

by Tim Bollerslev - JOURNAL OF ECONOMETRICS , 1986
"... A natural generalization of the ARCH (Autoregressive Conditional Heteroskedastic) process introduced in Engle (1982) to allow for past conditional variances in the current conditional variance equation is proposed. Stationarity conditions and autocorrelation structure for this new class of parametri ..."
Abstract - Cited by 2406 (30 self) - Add to MetaCart
A natural generalization of the ARCH (Autoregressive Conditional Heteroskedastic) process introduced in Engle (1982) to allow for past conditional variances in the current conditional variance equation is proposed. Stationarity conditions and autocorrelation structure for this new class

Natural Selection

by Belcher Christopher D. Williams , 1992
"... This study examined how middle science teachers perceive the textbooks they use and how their perceptions varied with their personal attributes and professional backgrounds. A questionnaire was sent to 79 middle school science teachers in Missouri, and 66 responded. The questionnaire was designed to ..."
Abstract - Cited by 461 (1 self) - Add to MetaCart
to determine the teachers ' perceptions about the quality, usability, and congruency of their respective textbooks. The data indicated a general positive acceptance by the teachers towards their textbooks. However, 30 percent did not feel that their current textbook was congruent with the state

Greed is Good: Algorithmic Results for Sparse Approximation

by Joel A. Tropp , 2004
"... This article presents new results on using a greedy algorithm, orthogonal matching pursuit (OMP), to solve the sparse approximation problem over redundant dictionaries. It provides a sufficient condition under which both OMP and Donoho’s basis pursuit (BP) paradigm can recover the optimal representa ..."
Abstract - Cited by 916 (9 self) - Add to MetaCart
representation of an exactly sparse signal. It leverages this theory to show that both OMP and BP succeed for every sparse input signal from a wide class of dictionaries. These quasi-incoherent dictionaries offer a natural generalization of incoherent dictionaries, and the cumulative coherence function

The Small-World Phenomenon: An Algorithmic Perspective

by Jon Kleinberg - in Proceedings of the 32nd ACM Symposium on Theory of Computing , 2000
"... Long a matter of folklore, the “small-world phenomenon ” — the principle that we are all linked by short chains of acquaintances — was inaugurated as an area of experimental study in the social sciences through the pioneering work of Stanley Milgram in the 1960’s. This work was among the first to m ..."
Abstract - Cited by 824 (5 self) - Add to MetaCart
that no decentralized algorithm, operating with local information only, can construct short paths in these networks with non-negligible probability. We then define an infinite family of network models that naturally generalizes the Watts-Strogatz model, and show that for one of these models, there is a decentralized

Optimal contracts and competitive markets with costly state verification

by Robert M. Townsend - Journal of Economic Theory , 1979
"... The insight of Arrow [4] and Debreu [7] that uncertainty is easily incor-porated into general equilibrium models is double-edged. It is true that one need only index commodities by the state of nature, and classical results on the existence and optimality of competitive equilibria can be made to ..."
Abstract - Cited by 879 (8 self) - Add to MetaCart
The insight of Arrow [4] and Debreu [7] that uncertainty is easily incor-porated into general equilibrium models is double-edged. It is true that one need only index commodities by the state of nature, and classical results on the existence and optimality of competitive equilibria can be made to

Is it an Agent, or just a Program?: A Taxonomy for Autonomous Agents

by Stan Franklin, Art Graesser - In Intelligent Agents III , 1997
"... The advent of software agents gave rise to much discussion of just what such an agent is, and of how they differ from programs in general. Here we propose a formal definition of an autonomous agent which clearly distinguishes a software agent from just any program. We also offer the beginnings of a ..."
Abstract - Cited by 788 (51 self) - Add to MetaCart
The advent of software agents gave rise to much discussion of just what such an agent is, and of how they differ from programs in general. Here we propose a formal definition of an autonomous agent which clearly distinguishes a software agent from just any program. We also offer the beginnings of a

A Sense of Self for Unix Processes

by Stephanie Forrest, Steven A. Hofmeyr, Anil Somayaji, Thomas A. Longstaff - In Proceedings of the 1996 IEEE Symposium on Security and Privacy , 1996
"... A method for anomaly detection is introduced in which "normal" is defined by short-range correlations in a process ' system calls. Initial experiments suggest that the definition is stable during normal behavior for standard UNIX programs. Further, it is able to detect several common ..."
Abstract - Cited by 689 (27 self) - Add to MetaCart
intrusions involving sendmail and lpr. This work is part of a research program aimed at building computer security systems that incorporate the mechanisms and algorithms used by natural immune systems. 1 Introduction We are interested in developing computer security methods that are based on the way natural

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
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

Regression Shrinkage and Selection Via the Lasso

by Robert Tibshirani - JOURNAL OF THE ROYAL STATISTICAL SOCIETY, SERIES B , 1994
"... We propose a new method for estimation in linear models. The "lasso" minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant. Because of the nature of this constraint it tends to produce some coefficients that are exactl ..."
Abstract - Cited by 4212 (49 self) - Add to MetaCart
We propose a new method for estimation in linear models. The "lasso" minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant. Because of the nature of this constraint it tends to produce some coefficients
Results 1 - 10 of 55,734