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ACL
2006
13 years 10 months ago
URES : an Unsupervised Web Relation Extraction System
Most information extraction systems either use hand written extraction patterns or use a machine learning algorithm that is trained on a manually annotated corpus. Both of these a...
Binyamin Rosenfeld, Ronen Feldman
GECCO
2008
Springer
261views Optimization» more  GECCO 2008»
13 years 9 months ago
SSNNS -: a suite of tools to explore spiking neural networks
We are interested in engineering smart machines that enable backtracking of emergent behaviors. Our SSNNS simulator consists of hand-picked tools to explore spiking neural network...
Heike Sichtig, J. David Schaffer, Craig B. Laramee
SSPR
2010
Springer
13 years 7 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...
GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
14 years 7 days ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa
EMNLP
2009
13 years 6 months ago
Improving Web Search Relevance with Semantic Features
Most existing information retrieval (IR) systems do not take much advantage of natural language processing (NLP) techniques due to the complexity and limited observed effectivenes...
Yumao Lu, Fuchun Peng, Gilad Mishne, Xing Wei, Ben...