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» Polynomial Learning of Distribution Families
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IJON
2007
184views more  IJON 2007»
13 years 9 months ago
Convex incremental extreme learning machine
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Guang-Bin Huang, Lei Chen
BMCBI
2010
152views more  BMCBI 2010»
13 years 10 months ago
Apples and oranges: avoiding different priors in Bayesian DNA sequence analysis
Background: One of the challenges of bioinformatics remains the recognition of short signal sequences in genomic DNA such as donor or acceptor splice sites, splicing enhancers or ...
Jens Keilwagen, Jan Grau, Stefan Posch, Ivo Grosse
JMLR
2012
12 years 8 days ago
Max-Margin Min-Entropy Models
We propose a new family of latent variable models called max-margin min-entropy (m3e) models, which define a distribution over the output and the hidden variables conditioned on ...
Kevin Miller, M. Pawan Kumar, Benjamin Packer, Dan...
PODS
2008
ACM
174views Database» more  PODS 2008»
14 years 10 months ago
Epistemic privacy
We present a novel definition of privacy in the framework of offline (retroactive) database query auditing. Given information about the database, a description of sensitive data, ...
Alexandre V. Evfimievski, Ronald Fagin, David P. W...
ICML
2005
IEEE
14 years 10 months ago
Bayesian hierarchical clustering
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
Katherine A. Heller, Zoubin Ghahramani