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» The Inefficiency of Batch Training for Large Training Sets
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DMIN
2007
186views Data Mining» more  DMIN 2007»
13 years 10 months ago
Cost-Sensitive Learning vs. Sampling: Which is Best for Handling Unbalanced Classes with Unequal Error Costs?
- The classifier built from a data set with a highly skewed class distribution generally predicts the more frequently occurring classes much more often than the infrequently occurr...
Gary M. Weiss, Kate McCarthy, Bibi Zabar
LREC
2010
131views Education» more  LREC 2010»
13 years 10 months ago
A Semi-supervised Type-based Classification of Adjectives: Distinguishing Properties and Relations
We present a semi-supervised machine-learning approach for the classification of adjectives into property- vs. relationdenoting adjectives, a distinction that is highly relevant f...
Matthias Hartung, Anette Frank
EMNLP
2008
13 years 10 months ago
A Phrase-Based Alignment Model for Natural Language Inference
The alignment problem--establishing links between corresponding phrases in two related sentences--is as important in natural language inference (NLI) as it is in machine translati...
Bill MacCartney, Michel Galley, Christopher D. Man...
IJCAI
2007
13 years 10 months ago
WiFi-SLAM Using Gaussian Process Latent Variable Models
WiFi localization, the task of determining the physical location of a mobile device from wireless signal strengths, has been shown to be an accurate method of indoor and outdoor l...
Brian Ferris, Dieter Fox, Neil D. Lawrence
ACL
2006
13 years 10 months ago
An End-to-End Discriminative Approach to Machine Translation
We present a perceptron-style discriminative approach to machine translation in which large feature sets can be exploited. Unlike discriminative reranking approaches, our system c...
Percy Liang, Alexandre Bouchard-Côté,...