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» Training a Selection Function for Extraction
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ESANN
2000
13 years 9 months ago
Algorithmic approaches to training Support Vector Machines: a survey
: Support Vector Machines (SVMs) have become an increasingly popular tool for machine learning tasks involving classi cation, regression or novelty detection. They exhibit good gen...
Colin Campbell
TPHOL
2007
IEEE
14 years 1 months ago
Extracting Purely Functional Contents from Logical Inductive Types
We propose a method to extract purely functional contents from logical inductive types in the context of the Calculus of Inductive Constructions. This method is based on a mode con...
David Delahaye, Catherine Dubois, Jean-Fréd...
NIPS
2007
13 years 9 months ago
Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition
We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...
Maryam Mahdaviani, Tanzeem Choudhury
ICASSP
2011
IEEE
12 years 11 months ago
Discriminatively trained Probabilistic Linear Discriminant Analysis for speaker verification
Recently, i-vector extraction and Probabilistic Linear Discriminant Analysis (PLDA) have proven to provide state-of-the-art speaker verification performance. In this paper, the s...
Lukas Burget, Oldrich Plchot, Sandro Cumani, Ondre...
AIPRF
2007
13 years 9 months ago
Evaluation of Different Approaches to Training a Genre Classifier
This paper presents experiments on classifying web pages by genre. Firstly, a corpus of 1539 manually labeled web pages was prepared. Secondly, 502 genre features were selected ba...
Vedrana Vidulin, Mitja Lustrek, Matjaz Gams