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IDA
2005
Springer
15 years 9 months ago
Removing Statistical Biases in Unsupervised Sequence Learning
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize the...
Yoav Horman, Gal A. Kaminka
PCI
2005
Springer
15 years 9 months ago
Gossip-Based Greedy Gaussian Mixture Learning
Abstract. It has been recently demonstrated that the classical EM algorithm for learning Gaussian mixture models can be successfully implemented in a decentralized manner by resort...
Nikos A. Vlassis, Yiannis Sfakianakis, Wojtek Kowa...
AAAI
2007
15 years 5 months ago
Learning Language Semantics from Ambiguous Supervision
This paper presents a method for learning a semantic parser from ambiguous supervision. Training data consists of natural language sentences annotated with multiple potential mean...
Rohit J. Kate, Raymond J. Mooney
ESANN
2008
15 years 4 months ago
Learning Data Representations with Sparse Coding Neural Gas
Abstract. We consider the problem of learning an unknown (overcomplete) basis from an unknown sparse linear combination. Introducing the "sparse coding neural gas" algori...
Kai Labusch, Erhardt Barth, Thomas Martinetz
128
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UAI
2008
15 years 4 months ago
Multi-View Learning over Structured and Non-Identical Outputs
In many machine learning problems, labeled training data is limited but unlabeled data is ample. Some of these problems have instances that can be factored into multiple views, ea...
Kuzman Ganchev, João Graça, John Bli...