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» On the efficiency of adaptive MCMC algorithms
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SAS
1994
Springer
136views Formal Methods» more  SAS 1994»
15 years 10 months ago
Constraint-Based Type Inference and Parametric Polymorphism
Constraint-based analysis is a technique for inferring implementation types. Traditionally it has been described using mathematical formalisms. We explain it in a different and mor...
Ole Agesen
ICML
2006
IEEE
16 years 7 months ago
Totally corrective boosting algorithms that maximize the margin
We consider boosting algorithms that maintain a distribution over a set of examples. At each iteration a weak hypothesis is received and the distribution is updated. We motivate t...
Gunnar Rätsch, Jun Liao, Manfred K. Warmuth
ICML
2008
IEEE
16 years 7 months ago
Empirical Bernstein stopping
Sampling is a popular way of scaling up machine learning algorithms to large datasets. The question often is how many samples are needed. Adaptive stopping algorithms monitor the ...
Csaba Szepesvári, Jean-Yves Audibert, Volod...
CVPR
2003
IEEE
16 years 8 months ago
Mean-shift Blob Tracking through Scale Space
The mean-shift algorithm is an efficient technique for tracking 2D blobs through an image. Although the scale of the mean-shift kernel is a crucial parameter, there is presently n...
Robert T. Collins
JCP
2006
111views more  JCP 2006»
15 years 6 months ago
Mining Developing Trends of Dynamic Spatiotemporal Data Streams
This paper1 presents an efficient modeling technique for data streams in a dynamic spatiotemporal environment and its suitability for mining developing trends. The streaming data a...
Yu Meng, Margaret H. Dunham