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» The Use of Classifiers in Sequential Inference
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CSDA
2008
67views more  CSDA 2008»
13 years 7 months ago
How useful are approximations to mean and variance of the index of dissimilarity?
Sociologists, demographers, and economists often use the index of dissimilarity, D, to describe the extent of racial, ethnic, spatial, or areal dissimilarity (or segregation) of d...
Madhuri S. Mulekar, John C. Knutson, Jyoti A. Cham...
UAI
2008
13 years 9 months ago
Learning Hidden Markov Models for Regression using Path Aggregation
We consider the task of learning mappings from sequential data to real-valued responses. We present and evaluate an approach to learning a type of hidden Markov model (HMM) for re...
Keith Noto, Mark Craven
ECOOP
2005
Springer
14 years 1 months ago
Towards Type Inference for JavaScript
Object-oriented scripting languages like JavaScript and Python are popular partly because of their dynamic features. These include the runtime modification of objects and classes ...
Christopher Anderson, Paola Giannini, Sophia Dross...
AAAI
2007
13 years 9 months ago
Cautious Inference in Collective Classification
Collective classification can significantly improve accuracy by exploiting relationships among instances. Although several collective inference procedures have been reported, they...
Luke McDowell, Kalyan Moy Gupta, David W. Aha
PAMI
2010
168views more  PAMI 2010»
13 years 5 months ago
Dynamic Hybrid Algorithms for MAP Inference in Discrete MRFs
—In this paper, we present novel techniques that improve the computational and memory efficiency of algorithms for solving multi-label energy functions arising from discrete MRF...
Karteek Alahari, Pushmeet Kohli, Philip H. S. Torr