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JMLR
2012
11 years 11 months ago
Deep Boltzmann Machines as Feed-Forward Hierarchies
The deep Boltzmann machine is a powerful model that extracts the hierarchical structure of observed data. While inference is typically slow due to its undirected nature, we argue ...
Grégoire Montavon, Mikio L. Braun, Klaus-Ro...
INTERSPEECH
2010
13 years 3 months ago
Using dependency parsing and machine learning for factoid question answering on spoken documents
This paper presents our experiments in question answering for speech corpora. These experiments focus on improving the answer extraction step of the QA process. We present two app...
Pere Comas, Jordi Turmo, Lluís Màrqu...
ICIP
2002
IEEE
14 years 10 months ago
Rule-based scene extraction from video
Instead of clustering video shots into scenes using low level image features, in this paper, we propose a rule-based model to extract simple dialog or action scenes. Through analy...
Lei Chen 0002, M. Tamer Özsu
CN
2007
129views more  CN 2007»
13 years 9 months ago
Machine-learnt versus analytical models of TCP throughput
We first study the accuracy of two well-known analytical models of the average throughput of long-term TCP flows, namely the so-called SQRT and PFTK models, and show that these ...
Ibtissam El Khayat, Pierre Geurts, Guy Leduc
ICML
2009
IEEE
14 years 10 months ago
MedLDA: maximum margin supervised topic models for regression and classification
Supervised topic models utilize document's side information for discovering predictive low dimensional representations of documents; and existing models apply likelihoodbased...
Jun Zhu, Amr Ahmed, Eric P. Xing