Results 1  10
of
7,577
26.1 Review of Last Class
"... We defined PAClearnability as follows: Definition 26.1.1 A concept class C is PAClearnable if there is an algorithm A such that for all ǫ> 0 and δ> 0, for all distributions D on the domain, and for all target functions f ∈ C, given a sample S drawn from D, A produces a hypothesis h in some c ..."
Abstract
 Add to MetaCart
We defined PAClearnability as follows: Definition 26.1.1 A concept class C is PAClearnable if there is an algorithm A such that for all ǫ> 0 and δ> 0, for all distributions D on the domain, and for all target functions f ∈ C, given a sample S drawn from D, A produces a hypothesis h in some
Hierarchical Models of Object Recognition in Cortex
, 1999
"... The classical model of visual processing in cortex is a hierarchy of increasingly sophisticated representations, extending in a natural way the model of simple to complex cells of Hubel and Wiesel. Somewhat surprisingly, little quantitative modeling has been done in the last 15 years to explore th ..."
Abstract

Cited by 836 (84 self)
 Add to MetaCart
The classical model of visual processing in cortex is a hierarchy of increasingly sophisticated representations, extending in a natural way the model of simple to complex cells of Hubel and Wiesel. Somewhat surprisingly, little quantitative modeling has been done in the last 15 years to explore
On Sequential Monte Carlo Sampling Methods for Bayesian Filtering
 STATISTICS AND COMPUTING
, 2000
"... In this article, we present an overview of methods for sequential simulation from posterior distributions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically nonlinear and nonGaussian. A general importance sampling framework is develop ..."
Abstract

Cited by 1051 (76 self)
 Add to MetaCart
is developed that unifies many of the methods which have been proposed over the last few decades in several different scientific disciplines. Novel extensions to the existing methods are also proposed. We show in particular how to incorporate local linearisation methods similar to those which have previously
TimingSync Protocol for Sensor Networks
 The First ACM Conference on Embedded Networked Sensor System (SenSys
, 2003
"... Wireless adhoc sensor networks have emerged as an interesting and important research area in the last few years. The applications envisioned for such networks require collaborative execution of a distributed task amongst a large set of sensor nodes. This is realized by exchanging messages that are ..."
Abstract

Cited by 515 (8 self)
 Add to MetaCart
Wireless adhoc sensor networks have emerged as an interesting and important research area in the last few years. The applications envisioned for such networks require collaborative execution of a distributed task amongst a large set of sensor nodes. This is realized by exchanging messages
Probabilistic Inference Using Markov Chain Monte Carlo Methods
, 1993
"... Probabilistic inference is an attractive approach to uncertain reasoning and empirical learning in artificial intelligence. Computational difficulties arise, however, because probabilistic models with the necessary realism and flexibility lead to complex distributions over highdimensional spaces. R ..."
Abstract

Cited by 736 (24 self)
 Add to MetaCart
physics for over forty years, and, in the last few years, the related method of "Gibbs sampling" has been applied to problems of statistical inference. Concurrently, an alternative method for solving problems in statistical physics by means of dynamical simulation has been developed as well
Loopy belief propagation for approximate inference: An empirical study. In:
 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 errorcorrecting codes. The most dramatic instance of this is the near Shannonlimit performanc ..."
Abstract

Cited by 676 (15 self)
 Add to MetaCart
nothing directly to do with coding or decoding will show that in some sense belief propagation "converges with high probability to a nearoptimum value" of the desired belief on a class of loopy DAGs Progress in the analysis of loopy belief propagation has been made for the case of networks
Minimax Programs
 University of California Press
, 1997
"... We introduce an optimization problem called a minimax program that is similar to a linear program, except that the addition operator is replaced in the constraint equations by the maximum operator. We clarify the relation of this problem to some betterknown problems. We identify an interesting spec ..."
Abstract

Cited by 482 (5 self)
 Add to MetaCart
special case and present an efficient algorithm for its solution. 1 Introduction Over the last fifty years, thousands of problems of practical interest have been formulated as a linear program. Not only has the linear programming model proven to be widely applicable, but ongoing research has discovered
The Lasting Impact of Childhood Health and Circumstance
 Journal of Health Economics
, 2005
"... We quantify the lasting effects of childhood health and economic circumstances on adult health, employment and socioeconomic status, using data fromabirth cohort that has been followed frombirth into middle age. Controlling for parental income, education and social class, children who experience poo ..."
Abstract

Cited by 293 (6 self)
 Add to MetaCart
We quantify the lasting effects of childhood health and economic circumstances on adult health, employment and socioeconomic status, using data fromabirth cohort that has been followed frombirth into middle age. Controlling for parental income, education and social class, children who experience
Digraphs  Theory, Algorithms and Applications
, 2007
"... Graph theory is a very popular area of discrete mathematics with not only numerous theoretical developments, but also countless applications to practical problems. As a research area, graph theory is still relatively young, but it is maturing rapidly with many deep results having been discovered o ..."
Abstract

Cited by 377 (48 self)
 Add to MetaCart
over the last couple of decades. The theory of graphs can be roughly partitioned into two branches: the areas of undirected graphs and directed graphs (digraphs). Even though both areas have numerous important applications, for various reasons, undirected graphs have been studied much more extensively
Results 1  10
of
7,577