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» Level-set methods for convex optimization
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DAGM
2008
Springer
15 years 3 months ago
Approximate Parameter Learning in Conditional Random Fields: An Empirical Investigation
We investigate maximum likelihood parameter learning in Conditional Random Fields (CRF) and present an empirical study of pseudo-likelihood (PL) based approximations of the paramet...
Filip Korc, Wolfgang Förstner
NIPS
2007
15 years 3 months ago
Predictive Matrix-Variate t Models
It is becoming increasingly important to learn from a partially-observed random matrix and predict its missing elements. We assume that the entire matrix is a single sample drawn ...
Shenghuo Zhu, Kai Yu, Yihong Gong
AUTOMATICA
2004
113views more  AUTOMATICA 2004»
15 years 1 months ago
Ellipsoidal bounds for uncertain linear equations and dynamical systems
In this paper, we discuss semidefinite relaxation techniques for computing minimal size ellipsoids that bound the solution set of a system of uncertain linear equations. The propo...
Giuseppe Carlo Calafiore, Laurent El Ghaoui
EMNLP
2010
14 years 12 months ago
Turbo Parsers: Dependency Parsing by Approximate Variational Inference
We present a unified view of two state-of-theart non-projective dependency parsers, both approximate: the loopy belief propagation parser of Smith and Eisner (2008) and the relaxe...
André F. T. Martins, Noah A. Smith, Eric P....
ACCV
2010
Springer
14 years 9 months ago
Image-Based 3D Modeling via Cheeger Sets
We propose a novel variational formulation for generating 3D models of objects from a single view. Based on a few user scribbles in an image, the algorithm automatically extracts t...
Eno Töppe, Martin R. Oswald, Daniel Cremers, ...