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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
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

Smooth minimization of nonsmooth functions

by Yu. Nesterov - Math. Programming , 2005
"... In this paper we propose a new approach for constructing efficient schemes for nonsmooth convex optimization. It is based on a special smoothing technique, which can be applied to the functions with explicit max-structure. Our approach can be considered as an alternative to black-box minimization. F ..."
Abstract - Cited by 523 (1 self) - Add to MetaCart
In this paper we propose a new approach for constructing efficient schemes for nonsmooth convex optimization. It is based on a special smoothing technique, which can be applied to the functions with explicit max-structure. Our approach can be considered as an alternative to black-box minimization

Keying hash functions for message authentication

by Mihir Bellare, Ran Canetti, Hugo Krawczyk , 1996
"... The use of cryptographic hash functions like MD5 or SHA for message authentication has become a standard approach inmanyInternet applications and protocols. Though very easy to implement, these mechanisms are usually based on ad hoc techniques that lack a sound security analysis. We present new cons ..."
Abstract - Cited by 611 (39 self) - Add to MetaCart
The use of cryptographic hash functions like MD5 or SHA for message authentication has become a standard approach inmanyInternet applications and protocols. Though very easy to implement, these mechanisms are usually based on ad hoc techniques that lack a sound security analysis. We present new

Functions from a set to a set

by Czesław Byliński - Journal of Formalized Mathematics , 1989
"... function from a set X into a set Y, denoted by “Function of X,Y ”, the set of all functions from a set X into a set Y, denoted by Funcs(X,Y), and the permutation of a set (mode Permutation of X, where X is a set). Theorems and schemes included in the article are reformulations of the theorems of [1] ..."
Abstract - Cited by 1089 (23 self) - Add to MetaCart
] in the new terminology. Also some basic facts about functions of two variables are proved.

Graph-based algorithms for Boolean function manipulation

by Randal E. Bryant - IEEE TRANSACTIONS ON COMPUTERS , 1986
"... In this paper we present a new data structure for representing Boolean functions and an associated set of manipulation algorithms. Functions are represented by directed, acyclic graphs in a manner similar to the representations introduced by Lee [1] and Akers [2], but with further restrictions on th ..."
Abstract - Cited by 3526 (46 self) - Add to MetaCart
In this paper we present a new data structure for representing Boolean functions and an associated set of manipulation algorithms. Functions are represented by directed, acyclic graphs in a manner similar to the representations introduced by Lee [1] and Akers [2], but with further restrictions

A new learning algorithm for blind signal separation

by S. Amari, A. Cichocki, H. H. Yang - , 1996
"... A new on-line learning algorithm which minimizes a statistical de-pendency among outputs is derived for blind separation of mixed signals. The dependency is measured by the average mutual in-formation (MI) of the outputs. The source signals and the mixing matrix are unknown except for the number of ..."
Abstract - Cited by 622 (80 self) - Add to MetaCart
A new on-line learning algorithm which minimizes a statistical de-pendency among outputs is derived for blind separation of mixed signals. The dependency is measured by the average mutual in-formation (MI) of the outputs. The source signals and the mixing matrix are unknown except for the number

A New Location Technique for the Active Office

by Andy Ward, Alan Jones , 1997
"... Configuration of the computing and communications systems found at home and in the workplace is a complex task that currently requires the attention of the user. Recently, researchers have begun to examine computers that would autonomously change their functionality based on observations of who or ..."
Abstract - Cited by 515 (4 self) - Add to MetaCart
Configuration of the computing and communications systems found at home and in the workplace is a complex task that currently requires the attention of the user. Recently, researchers have begun to examine computers that would autonomously change their functionality based on observations of who

What energy functions can be minimized via graph cuts?

by Vladimir Kolmogorov, Ramin Zabih - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2004
"... In the last few years, several new algorithms based on graph cuts have been developed to solve energy minimization problems in computer vision. Each of these techniques constructs a graph such that the minimum cut on the graph also minimizes the energy. Yet, because these graph constructions are co ..."
Abstract - Cited by 1047 (23 self) - Add to MetaCart
In the last few years, several new algorithms based on graph cuts have been developed to solve energy minimization problems in computer vision. Each of these techniques constructs a graph such that the minimum cut on the graph also minimizes the energy. Yet, because these graph constructions

Learning quickly when irrelevant attributes abound: A new linear-threshold algorithm

by Nick Littlestone - Machine Learning , 1988
"... learning Boolean functions, linear-threshold algorithms Abstract. Valiant (1984) and others have studied the problem of learning various classes of Boolean functions from examples. Here we discuss incremental learning of these functions. We consider a setting in which the learner responds to each ex ..."
Abstract - Cited by 773 (5 self) - Add to MetaCart
learning Boolean functions, linear-threshold algorithms Abstract. Valiant (1984) and others have studied the problem of learning various classes of Boolean functions from examples. Here we discuss incremental learning of these functions. We consider a setting in which the learner responds to each

A review of image denoising algorithms, with a new one

by A. Buades, B. Coll, J. M. Morel - SIMUL , 2005
"... The search for efficient image denoising methods is still a valid challenge at the crossing of functional analysis and statistics. In spite of the sophistication of the recently proposed methods, most algorithms have not yet attained a desirable level of applicability. All show an outstanding perf ..."
Abstract - Cited by 508 (6 self) - Add to MetaCart
The search for efficient image denoising methods is still a valid challenge at the crossing of functional analysis and statistics. In spite of the sophistication of the recently proposed methods, most algorithms have not yet attained a desirable level of applicability. All show an outstanding
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