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JMLR
2011
148views more  JMLR 2011»
14 years 7 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara
ICML
2008
IEEE
16 years 1 months ago
Fast estimation of first-order clause coverage through randomization and maximum likelihood
In inductive logic programming, subsumption is a widely used coverage test. Unfortunately, testing -subsumption is NP-complete, which represents a crucial efficiency bottleneck fo...
Filip Zelezný, Ondrej Kuzelka
96
Voted
CORR
2007
Springer
140views Education» more  CORR 2007»
15 years 11 days ago
From the entropy to the statistical structure of spike trains
— We use statistical estimates of the entropy rate of spike train data in order to make inferences about the underlying structure of the spike train itself. We first examine a n...
Yun Gao, Ioannis Kontoyiannis, Elie Bienenstock
105
Voted
CORR
2007
Springer
128views Education» more  CORR 2007»
15 years 11 days ago
Model Selection Through Sparse Maximum Likelihood Estimation
We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting undirected graphical model is sparse. Our approach is to...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
TCOM
2011
155views more  TCOM 2011»
14 years 7 months ago
Asymptotically Optimal Model Estimation for Quantization
—Using high-rate theory approximations we introduce flexible practical quantizers based on possibly non-Gaussian models in both the constrained resolution (CR) and the constrain...
Alexey Ozerov, W. Bastiaan Kleijn