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ICML
2010
IEEE
13 years 11 months ago
Hilbert Space Embeddings of Hidden Markov Models
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
Le Song, Sajid M. Siddiqi, Geoffrey J. Gordon, Ale...
ICML
2009
IEEE
14 years 11 months ago
Large margin training for hidden Markov models with partially observed states
Large margin learning of Continuous Density HMMs with a partially labeled dataset has been extensively studied in the speech and handwriting recognition fields. Yet due to the non...
Thierry Artières, Trinh Minh Tri Do
AIME
2007
Springer
14 years 4 months ago
A Causal Modeling Framework for Generating Clinical Practice Guidelines from Data
Abstract. The practice of medicine is becoming increasingly evidencebased and clinical practice guidelines (CPGs) are necessary for advancing evidence-based medicine (EBM). We hypo...
Subramani Mani, Constantin F. Aliferis
ICML
2003
IEEE
14 years 11 months ago
Using Linear-threshold Algorithms to Combine Multi-class Sub-experts
We present a new type of multi-class learning algorithm called a linear-max algorithm. Linearmax algorithms learn with a special type of attribute called a sub-expert. A sub-exper...
Chris Mesterharm
CIKM
2004
Springer
14 years 3 months ago
Hierarchical document categorization with support vector machines
Automatically categorizing documents into pre-defined topic hierarchies or taxonomies is a crucial step in knowledge and content management. Standard machine learning techniques ...
Lijuan Cai, Thomas Hofmann