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141
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ICVGIP
2004
15 years 5 months ago
On Learning Shapes from Shades
Shape from Shading (SFS) is one of the most extensively studied problems in Computer Vision. However, most of the approaches only deal with Lambertian or other specific shading mo...
Subhajit Sanyal, Mayank Bansal, Subhashis Banerjee...
144
Voted
EMNLP
2010
15 years 1 months ago
Efficient Graph-Based Semi-Supervised Learning of Structured Tagging Models
We describe a new scalable algorithm for semi-supervised training of conditional random fields (CRF) and its application to partof-speech (POS) tagging. The algorithm uses a simil...
Amarnag Subramanya, Slav Petrov, Fernando Pereira
111
Voted
ICML
2001
IEEE
16 years 4 months ago
Expectation Maximization for Weakly Labeled Data
We call data weakly labeled if it has no exact label but rather a numerical indication of correctness of the label "guessed" by the learning algorithm - a situation comm...
Yuri A. Ivanov, Bruce Blumberg, Alex Pentland
122
Voted
APPROX
2004
Springer
135views Algorithms» more  APPROX 2004»
15 years 9 months ago
The Diameter of Randomly Perturbed Digraphs and Some Applications.
The central observation of this paper is that if ǫn random arcs are added to any n-node strongly connected digraph with bounded degree then the resulting graph has diameter O(ln ...
Abraham Flaxman, Alan M. Frieze
112
Voted
CCS
2009
ACM
15 years 10 months ago
A framework for quantitative security analysis of machine learning
We propose a framework for quantitative security analysis of machine learning methods. Key issus of this framework are a formal specification of the deployed learning model and a...
Pavel Laskov, Marius Kloft