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ICML
2005
IEEE
14 years 9 months 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»
14 years 9 months 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
13 years 10 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
13 years 9 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»
13 years 3 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