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ESOP
2011
Springer
14 years 6 months ago
Measure Transformer Semantics for Bayesian Machine Learning
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Johannes Borgström, Andrew D. Gordon, Michael...
KDD
1999
ACM
104views Data Mining» more  KDD 1999»
15 years 7 months ago
Learning Rules from Distributed Data
In this paper a concern about the accuracy (as a function of parallelism) of a certain class of distributed learning algorithms is raised, and one proposed improvement is illustrat...
Lawrence O. Hall, Nitesh V. Chawla, Kevin W. Bowye...
ACL
2001
15 years 4 months ago
Detecting Problematic Turns in Human-Machine Interactions: Rule-induction Versus Memory-based Learning Approaches
We address the issue of on-line detection of communication problems in spoken dialogue systems. The usefulness is investigated of the sequence of system question types and the wor...
Antal van den Bosch, Emiel Krahmer, Marc Swerts
CIKM
2009
Springer
15 years 9 months ago
A machine learning approach for improved BM25 retrieval
Despite the widespread use of BM25, there have been few studies examining its effectiveness on a document description over single and multiple field combinations. We determine t...
Krysta Marie Svore, Christopher J. C. Burges
BMCBI
2008
123views more  BMCBI 2008»
15 years 3 months ago
Pol II promoter prediction using characteristic 4-mer motifs: a machine learning approach
Background: Eukaryotic promoter prediction using computational analysis techniques is one of the most difficult jobs in computational genomics that is essential for constructing a...
Firoz Anwar, Syed Murtuza Baker, Taskeed Jabid, Md...