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» Intelligent Selection of Language Model Training Data
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ICANN
2009
Springer
15 years 11 months ago
Selective Attention Improves Learning
Abstract. We demonstrate that selective attention can improve learning. Considerably fewer samples are needed to learn a source separation problem when the inputs are pre-segmented...
Antti Yli-Krekola, Jaakko Särelä, Harri ...
MICAI
2009
Springer
15 years 9 months ago
Using Nearest Neighbor Information to Improve Cross-Language Text Classification
Cross-language text classification (CLTC) aims to take advantage of existing training data from one language to construct a classifier for another language. In addition to the expe...
Adelina Escobar-Acevedo, Manuel Montes-y-Gó...
CSB
2004
IEEE
135views Bioinformatics» more  CSB 2004»
15 years 8 months ago
Selection of Patient Samples and Genes for Outcome Prediction
Gene expression profiles with clinical outcome data enable monitoring of disease progression and prediction of patient survival at the molecular level. We present a new computatio...
Huiqing Liu, Jinyan Li, Limsoon Wong
133
Voted
CIDM
2007
IEEE
15 years 11 months ago
A Prototype-driven Framework for Change Detection in Data Stream Classification
This paper presents a prototype-driven framework for classifying evolving data streams. Our framework uses cluster prototypes to summarize the data and to determine whether the cur...
Hamed Valizadegan, Pang-Ning Tan
78
Voted
NAACL
2007
15 years 6 months ago
Applying Many-to-Many Alignments and Hidden Markov Models to Letter-to-Phoneme Conversion
Letter-to-phoneme conversion generally requires aligned training data of letters and phonemes. Typically, the alignments are limited to one-to-one alignments. We present a novel t...
Sittichai Jiampojamarn, Grzegorz Kondrak, Tarek Sh...