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116,888
The Nature of Statistical Learning Theory
, 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 ..."
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Cited by 13236 (32 self)
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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
Statistical Mechanics Approach to Coding Theory
, 1999
"... We propose a method based on cluster expansion to study the optimal code with a given distance between codewords. Using this approach we find the GilbertVarshamov lower bound for the rate of largest code. ..."
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Cited by 5 (0 self)
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We propose a method based on cluster expansion to study the optimal code with a given distance between codewords. Using this approach we find the GilbertVarshamov lower bound for the rate of largest code.
A statistical mechanics approach to autopoietic immune networks
, 2010
"... Abstract. In this work we aim to bridge theoretical immunology and disordered statistical mechanics. We introduce a model for the behavior of Bcells which naturally merges the clonal selection theory and the autopoietic network theory as a whole. From the analysis of its features we recover severa ..."
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Cited by 7 (6 self)
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Abstract. In this work we aim to bridge theoretical immunology and disordered statistical mechanics. We introduce a model for the behavior of Bcells which naturally merges the clonal selection theory and the autopoietic network theory as a whole. From the analysis of its features we recover
Statistical mechanics approach to some problems in conformal geometry
 PHYSICA A 297
, 2000
"... ..."
A Statistical Mechanics Approach to Large Deviation Theorems
"... Chernoff bounds and related large deviation bounds have a wide variety of applications in statistics and learning theory. This paper proves that for any realvalued random variable X the probability of a deviation to value x is bounded by e ..."
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Cited by 4 (0 self)
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Chernoff bounds and related large deviation bounds have a wide variety of applications in statistics and learning theory. This paper proves that for any realvalued random variable X the probability of a deviation to value x is bounded by e
Statistical mechanics approach to the probability distribution of money
, 1007
"... This Chapter reviews statistical models for the probability distribution of money developed in the econophysics literature since the late 1990s. In these models, economic transactions are modeled as random transfers of money between the agents in payment for goods and services. Starting from the ini ..."
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Cited by 3 (1 self)
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This Chapter reviews statistical models for the probability distribution of money developed in the econophysics literature since the late 1990s. In these models, economic transactions are modeled as random transfers of money between the agents in payment for goods and services. Starting from
Polynomial Invariants For Trees. A Statistical Mechanics Approach
 ACCEPTED FOR PUBLICATION BY "DISCRETE MATHEMATICS", JUNE 97
, 1997
"... We introduce two "polynomial invariants" for rooted trees and discuss their properties. A statistical mechanics interpretation is pointed out. In particular we show that the partition function of the Ising model, in the simple surface separation ensemble, is a complete invariant.
..."
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We introduce two "polynomial invariants" for rooted trees and discuss their properties. A statistical mechanics interpretation is pointed out. In particular we show that the partition function of the Ising model, in the simple surface separation ensemble, is a complete invariant.
Statistical mechanics approach to sparse noise denoising
 in Proc. European Sign. Proc. Conf
"... Abstract—Reconstruction fidelity of sparse signals contaminated by sparse noise is considered. Statistical mechanics inspired tools are used to show that the `1norm based convex optimization algorithm exhibits a phase transition between the possibility of perfect and imperfect reconstruction. Cond ..."
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Cited by 1 (1 self)
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Abstract—Reconstruction fidelity of sparse signals contaminated by sparse noise is considered. Statistical mechanics inspired tools are used to show that the `1norm based convex optimization algorithm exhibits a phase transition between the possibility of perfect and imperfect reconstruction
Statistical Mechanics Approaches to the Modeling of Nonlinear Earthquake
 Physics, Conference proceedings of the International Union of Geodesy and Geophysics
, 2003
"... Abstract. We discuss the problem of earthquake forecasting in the context of new models for the dynamics based on statistical physics. Here we focus on new, topologically realistic systemlevel approaches to the modeling of earthquake faults. We show that the frictional failure physics of earthquake ..."
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Abstract. We discuss the problem of earthquake forecasting in the context of new models for the dynamics based on statistical physics. Here we focus on new, topologically realistic systemlevel approaches to the modeling of earthquake faults. We show that the frictional failure physics
Results 1  10
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116,888