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» MultiK-MHKS: A Novel Multiple Kernel Learning Algorithm
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EMNLP
2011
13 years 11 months ago
Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions
We introduce a novel machine learning framework based on recursive autoencoders for sentence-level prediction of sentiment label distributions. Our method learns vector space repr...
Richard Socher, Jeffrey Pennington, Eric H. Huang,...
ICDE
2010
IEEE
290views Database» more  ICDE 2010»
15 years 3 months ago
The Model-Summary Problem and a Solution for Trees
Modern science is collecting massive amounts of data from sensors, instruments, and through computer simulation. It is widely believed that analysis of this data will hold the key ...
Biswanath Panda, Mirek Riedewald, Daniel Fink
IPMI
2007
Springer
16 years 17 days ago
Robust Parametric Modeling Approach Based on Domain Knowledge for Computer Aided Detection of Vertebrae Column Metastases in MRI
This study evaluates a robust parametric modeling approach for computer-aided detection (CAD) of vertebrae column metastases in whole-body MRI. Our method involves constructing a m...
Anna K. Jerebko, G. P. Schmidt, Xiang Sean Zhou, J...
NIPS
2003
15 years 1 months ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller
RECOMB
2004
Springer
16 years 1 days ago
Predicting Genetic Regulatory Response Using Classification: Yeast Stress Response
We present a novel classification-based algorithm called GeneClass for learning to predict gene regulatory response. Our approach is motivated by the hypothesis that in simple orga...
Manuel Middendorf, Anshul Kundaje, Chris Wiggins, ...