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» Level-set methods for convex optimization
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DAGM
2008
Springer
15 years 5 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
109
Voted
NIPS
2007
15 years 5 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
120
Voted
AUTOMATICA
2004
113views more  AUTOMATICA 2004»
15 years 3 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
132
Voted
EMNLP
2010
15 years 1 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....
146
Voted
ACCV
2010
Springer
14 years 10 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, ...