Results 1  10
of
776
Convergence rates for Bayesian density estimation of infinitedimensional exponential families
 Ann. Statist
, 2006
"... We study the rate of convergence of posterior distributions in density estimation problems for logdensities in periodic Sobolev classes characterized by a smoothness parameter p. The posterior expected density provides a nonparametric estimation procedure attaining the optimal minimax rate of conve ..."
Abstract

Cited by 11 (1 self)
 Add to MetaCart
We study the rate of convergence of posterior distributions in density estimation problems for logdensities in periodic Sobolev classes characterized by a smoothness parameter p. The posterior expected density provides a nonparametric estimation procedure attaining the optimal minimax rate
Relative Loss Bounds for Online Density Estimation with the Exponential Family of Distributions
 MACHINE LEARNING
, 2000
"... We consider online density estimation with a parameterized density from the exponential family. The online algorithm receives one example at a time and maintains a parameter that is essentially an average of the past examples. After receiving an example the algorithm incurs a loss, which is the n ..."
Abstract

Cited by 152 (12 self)
 Add to MetaCart
We consider online density estimation with a parameterized density from the exponential family. The online algorithm receives one example at a time and maintains a parameter that is essentially an average of the past examples. After receiving an example the algorithm incurs a loss, which
Analysis of sumproduct decoding of lowdensity paritycheck codes using a Gaussian approximation
 IEEE TRANS. INFORM. THEORY
, 2001
"... Density evolution is an algorithm for computing the capacity of lowdensity paritycheck (LDPC) codes under messagepassing decoding. For memoryless binaryinput continuousoutput additive white Gaussian noise (AWGN) channels and sumproduct decoders, we use a Gaussian approximation for message densi ..."
Abstract

Cited by 244 (2 self)
 Add to MetaCart
densities under density evolution to simplify the analysis of the decoding algorithm. We convert the infinitedimensional problem of iteratively calculating message densities, which is needed to find the exact threshold, to a onedimensional problem of updating means of Gaussian densities
Generalized Maximum Likelihood Estimates for Infinite Dimensional Exponential Families
, 2006
"... The notion of generalized maximum likelihood estimate for finite dimensional canonically convex exponential families, studied in detail in previous works of the authors, is extended to an infinite dimensional setting. Existence of the estimate when a generalized loglikelihood function is bounded ab ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
The notion of generalized maximum likelihood estimate for finite dimensional canonically convex exponential families, studied in detail in previous works of the authors, is extended to an infinite dimensional setting. Existence of the estimate when a generalized loglikelihood function is bounded
A finite dimensional filter with exponential conditional density
 IN PROCEEDINGS OF THE 1997 IEEE CONFERENCE ON DECISION AND CONTROL (CDC
, 1997
"... In this paper we consider the continuous–time nonlinear filtering problem, which has an infinite–dimensional solution in general, as proved by Chaleyat–Maurel and Michel. There are few examples of nonlinear systems for which the optimal filter is finite dimensional, in particular Kalman’s, Beneˇs’, ..."
Abstract

Cited by 7 (0 self)
 Add to MetaCart
family of probability densities. We construct a drift for the state equation such that the resulting nonlinear filtering problem admits a finite–dimensional filter evolving in the prescribed exponential family augmented by the observaton function and its square.
Improved fast Gauss transform and efficient kernel density estimation
 In ICCV
, 2003
"... Evaluating sums of multivariate Gaussians is a common computational task in computer vision and pattern recognition, including in the general and powerful kernel density estimation technique. The quadratic computational complexity of the summation is a significant barrier to the scalability of this ..."
Abstract

Cited by 154 (8 self)
 Add to MetaCart
of this algorithm to practical applications. The fast Gauss transform (FGT) has successfully accelerated the kernel density estimation to linear running time for lowdimensional problems. Unfortunately, the cost of a direct extension of the FGT to higherdimensional problems grows exponentially with dimension
: The exponential,
"... , progress of electronics may be continued beyond the 10nm frontier if the currently dominant CMOS technology is replaced by hybrid CMOL circuits combining a silicon MOSFET stack and a few layers of parallel nanowires connected by selfassembled molecular electronic devices. Such hybrids promise ..."
Abstract
 Add to MetaCart
neuromorphic circuits with high component density. Preliminary estimates show that this approach may eventually allow us to place a cortexscale circuit with about 10
Approximating Directional Densities by Sequences of Exponential Families
, 1998
"... This paper develops approximation techniques for directional densities by finite dimensional exponential densities. The methodology is to use expansions with respect to classical spherical harmonics followed by estimating the unknown parameters by maximum likelihood. The advantage of this approach i ..."
Abstract
 Add to MetaCart
This paper develops approximation techniques for directional densities by finite dimensional exponential densities. The methodology is to use expansions with respect to classical spherical harmonics followed by estimating the unknown parameters by maximum likelihood. The advantage of this approach
Results 1  10
of
776