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» Learning words from sights and sounds: a computational model
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93
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JCB
2008
91views more  JCB 2008»
14 years 11 months ago
Computational Quantification of Peptides from LC-MS Data
Liquid chromatography coupled to mass spectrometry (LC-MS) has become a major tool for the study of biological processes. High-throughput LC-MS experiments are frequently conducte...
Ole Schulz-Trieglaff, Rene Hussong, Clemens Gr&oum...
85
Voted
ICCV
2009
IEEE
16 years 4 months ago
Unlabeled data improves word prediction
Labeling image collections is a tedious task, especially when multiple labels have to be chosen for each image. In this paper we introduce a new framework that extends state of ...
Nicolas Loeff, Ali Farhadi, Ian Endres and David A...
ICS
2005
Tsinghua U.
15 years 5 months ago
What is worth learning from parallel workloads?: a user and session based analysis
Learning useful and predictable features from past workloads and exploiting them well is a major source of improvement in many operating system problems. We review known parallel ...
Julia Zilber, Ofer Amit, David Talby
112
Voted
COLING
2002
14 years 11 months ago
A Maximum Entropy-based Word Sense Disambiguation System
In this paper, a supervised learning system of word sense disambiguation is presented. It is based on conditional maximum entropy models. This system acquires the linguistic knowl...
Armando Suárez, Manuel Palomar
GFKL
2007
Springer
152views Data Mining» more  GFKL 2007»
15 years 5 months ago
Supporting Web-based Address Extraction with Unsupervised Tagging
Abstract. The manual acquisition and modeling of tourist information as e.g. addresses of points of interest is time and, therefore, cost intensive. Furthermore, the encoded inform...
Berenike Loos, Chris Biemann