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NAACL
2004
13 years 8 months ago
Exponential Priors for Maximum Entropy Models
Maximum entropy models are a common modeling technique, but prone to overfitting. We show that using an exponential distribution as a prior leads to bounded absolute discounting b...
Joshua Goodman
SIGIR
2005
ACM
14 years 1 months ago
The maximum entropy method for analyzing retrieval measures
We present a model, based on the maximum entropy method, for analyzing various measures of retrieval performance such as average precision, R-precision, and precision-at-cutoffs....
Javed A. Aslam, Emine Yilmaz, Virgiliu Pavlu
UAI
2004
13 years 8 months ago
The Minimum Information Principle for Discriminative Learning
Exponential models of distributions are widely used in machine learning for classification and modelling. It is well known that they can be interpreted as maximum entropy models u...
Amir Globerson, Naftali Tishby
NIPS
2007
13 years 9 months ago
Near-Maximum Entropy Models for Binary Neural Representations of Natural Images
Maximum entropy analysis of binary variables provides an elegant way for studying the role of pairwise correlations in neural populations. Unfortunately, these approaches suffer f...
Matthias Bethge, Philipp Berens
EMMCVPR
2003
Springer
14 years 21 days ago
Asymptotic Characterization of Log-Likelihood Maximization Based Algorithms and Applications
The asymptotic distribution of estimates that are based on a sub-optimal search for the maximum of the log-likelihood function is considered. In particular, estimation schemes that...
Doron Blatt, Alfred O. Hero