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JAIR
2002
134views more  JAIR 2002»
15 years 4 months ago
Specific-to-General Learning for Temporal Events with Application to Learning Event Definitions from Video
We develop, analyze, and evaluate a novel, supervised, specific-to-general learner for a simple temporal logic and use the resulting algorithm to learn visual event definitions fr...
Alan Fern, Robert Givan, Jeffrey Mark Siskind
TNN
2010
234views Management» more  TNN 2010»
14 years 11 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
SDM
2011
SIAM
269views Data Mining» more  SDM 2011»
14 years 7 months ago
Semi-Supervised Convolution Graph Kernels for Relation Extraction
Extracting semantic relations between entities is an important step towards automatic text understanding. In this paper, we propose a novel Semi-supervised Convolution Graph Kerne...
Xia Ning, Yanjun Qi
IUI
2011
ACM
14 years 7 months ago
Predicting and compensating for lexicon access errors
Learning a foreign language is a long, error-prone process, and much of a learner’s time is effectively spent studying vocabulary. Many errors occur because words are only partl...
Lars Yencken, Timothy Baldwin
ATAL
2009
Springer
15 years 11 months ago
Generalized model learning for reinforcement learning in factored domains
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
Todd Hester, Peter Stone