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ML
2002
ACM
163views Machine Learning» more  ML 2002»
15 years 6 months ago
Structural Modelling with Sparse Kernels
A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A numb...
Steve R. Gunn, Jaz S. Kandola
HICSS
2005
IEEE
133views Biometrics» more  HICSS 2005»
15 years 12 months ago
Identifying Facilitators and Inhibitors of Market Structure Change: A Hybrid Theory of Unbiased Electronic Markets
The electronic markets hypothesis (EMH) in the information systems (IS) literature suggests that information technology (IT) will reduce coordination costs across firms, leading t...
Nelson F. Granados, Alok Gupta, Robert J. Kauffman
AAAI
2008
15 years 8 months ago
Structure Learning on Large Scale Common Sense Statistical Models of Human State
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes
CIBCB
2009
IEEE
15 years 7 months ago
Application of machine learning approaches on quantitative structure activity relationships
Machine Learning techniques are successfully applied to establish quantitative relations between chemical structure and biological activity (QSAR), i.e. classify compounds as activ...
Mariusz Butkiewicz, Ralf Mueller, Danilo Selic, Er...
EMNLP
2010
15 years 4 months ago
Multi-Level Structured Models for Document-Level Sentiment Classification
In this paper, we investigate structured models for document-level sentiment classification. When predicting the sentiment of a subjective document (e.g., as positive or negative)...
Ainur Yessenalina, Yisong Yue, Claire Cardie