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ICPR
2008
IEEE
16 years 7 months ago
Component-wise parameter smoothing for learning mixture models
In this paper, we propose a novel component-wise smoothing algorithm that constructs a hierarchy (or family) of smoothened log-likelihood surfaces. Our approach first smoothens th...
Bala Rajaratnam, Chandan K. Reddy
SIGIR
2009
ACM
16 years 1 months ago
Reciprocal rank fusion outperforms condorcet and individual rank learning methods
Reciprocal Rank Fusion (RRF), a simple method for combining the document rankings from multiple IR systems, consistently yields better results than any individual system, and bett...
Gordon V. Cormack, Charles L. A. Clarke, Stefan B&...
CIMCA
2005
IEEE
16 years 4 days ago
Learning to feel the physics of a body
Despite the tremendous progress in robotic hardware and in both sensorial and computing efficiencies the performance of contemporary autonomous robots is still far below that of ...
Ralf Der, Frank Hesse, Georg Martius
AAAI
2007
15 years 8 months ago
Learning and Inference for Hierarchically Split PCFGs
Treebank parsing can be seen as the search for an optimally refined grammar consistent with a coarse training treebank. We describe a method in which a minimal grammar is hierarc...
Slav Petrov, Dan Klein
ECIR
2007
Springer
15 years 8 months ago
A Bayesian Approach for Learning Document Type Relevance
Retrieval accuracy can be improved by considering which document type should be filtered out and which should be ranked higher in the result list. Hence, document type can be used...
Peter C. K. Yeung, Stefan Büttcher, Charles L...