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ECML
2006
Springer
13 years 11 months ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...
EMNLP
2007
13 years 9 months ago
Learning to Merge Word Senses
It has been widely observed that different NLP applications require different sense granularities in order to best exploit word sense distinctions, and that for many applications ...
Rion Snow, Sushant Prakash, Daniel Jurafsky, Andre...
AAAI
2010
13 years 9 months ago
The Model-Based Approach to Autonomous Behavior: A Personal View
The selection of the action to do next is one of the central problems faced by autonomous agents. In AI, three approaches have been used to address this problem: the programming-b...
Hector Geffner
ICASSP
2011
IEEE
12 years 11 months ago
Increasing discriminative capability on MAP-based mapping function estimation for acoustic model adaptation
In this study, we propose increasing discriminative power on the maximum a posteriori (MAP)-based mapping function estimation for acoustic model adaptation. Based on the effective...
Yu Tsao, Ryosuke Isotani, Hisashi Kawai, Satoshi N...
ICML
2004
IEEE
14 years 8 months ago
Improving SVM accuracy by training on auxiliary data sources
The standard model of supervised learning assumes that training and test data are drawn from the same underlying distribution. This paper explores an application in which a second...
Pengcheng Wu, Thomas G. Dietterich