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ICML
2005
IEEE
16 years 13 days ago
Bayesian hierarchical clustering
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
Katherine A. Heller, Zoubin Ghahramani
VLSID
2009
IEEE
115views VLSI» more  VLSID 2009»
16 years 7 days ago
Efficient Techniques for Directed Test Generation Using Incremental Satisfiability
Functional validation is a major bottleneck in the current SOC design methodology. While specification-based validation techniques have proposed several promising ideas, the time ...
Prabhat Mishra, Mingsong Chen
AAAI
2007
15 years 2 months ago
Restart Schedules for Ensembles of Problem Instances
The mean running time of a Las Vegas algorithm can often be dramatically reduced by periodically restarting it with a fresh random seed. The optimal restart schedule depends on th...
Matthew J. Streeter, Daniel Golovin, Stephen F. Sm...
WSC
2004
15 years 1 months ago
Function-Approximation-Based Importance Sampling for Pricing American Options
Monte Carlo simulation techniques that use function approximations have been successfully applied to approximately price multi-dimensional American options. However, for many pric...
Nomesh Bolia, Sandeep Juneja, Paul Glasserman
ML
2010
ACM
163views Machine Learning» more  ML 2010»
14 years 6 months ago
Classification with guaranteed probability of error
We introduce a general-purpose learning machine that we call the Guaranteed Error Machine, or GEM, and two learning algorithms, a real GEM algorithm and an ideal GEM algorithm. Th...
Marco C. Campi