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JMLR
2012
11 years 11 months ago
Low rank continuous-space graphical models
Constructing tractable dependent probability distributions over structured continuous random vectors is a central problem in statistics and machine learning. It has proven diffic...
Carl Smith, Frank Wood, Liam Paninski
BMCBI
2008
171views more  BMCBI 2008»
13 years 8 months ago
A general approach to simultaneous model fitting and variable elimination in response models for biological data with many more
Background: With the advent of high throughput biotechnology data acquisition platforms such as micro arrays, SNP chips and mass spectrometers, data sets with many more variables ...
Harri T. Kiiveri
AAAI
2006
13 years 10 months ago
Embedding Heterogeneous Data Using Statistical Models
Embedding algorithms are a method for revealing low dimensional structure in complex data. Most embedding algorithms are designed to handle objects of a single type for which pair...
Amir Globerson, Gal Chechik, Fernando Pereira, Naf...
PLPV
2009
ACM
14 years 5 months ago
Embedding a logical theory of constructions in Agda
We propose a new way to reason about general recursive functional programs in the dependently typed programming language Agda, which is based on Martin-L¨of’s intuitionistic ty...
Ana Bove, Peter Dybjer, Andrés Sicard-Ram&i...
COLING
2010
13 years 3 months ago
Dependency Forest for Statistical Machine Translation
We propose a structure called dependency forest for statistical machine translation. A dependency forest compactly represents multiple dependency trees. We develop new algorithms ...
Zhaopeng Tu, Yang Liu, Young-Sook Hwang, Qun Liu, ...