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» SNPs Problems, Complexity, and Algorithms
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ICML
2009
IEEE
16 years 4 months ago
Robot trajectory optimization using approximate inference
The general stochastic optimal control (SOC) problem in robotics scenarios is often too complex to be solved exactly and in near real time. A classical approximate solution is to ...
Marc Toussaint
ICML
2008
IEEE
16 years 4 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...
ICCAD
2001
IEEE
101views Hardware» more  ICCAD 2001»
16 years 27 days ago
Instruction Generation for Hybrid Reconfigurable Systems
In this work, we present an algorithm for simultaneous template generation and matching. The algorithm profiles the graph and iteratively contracts edges to create the templates. ...
Ryan Kastner, Seda Ogrenci Memik, Elaheh Bozorgzad...
FOCS
2008
IEEE
15 years 10 months ago
The Bayesian Learner is Optimal for Noisy Binary Search (and Pretty Good for Quantum as Well)
We use a Bayesian approach to optimally solve problems in noisy binary search. We deal with two variants: • Each comparison is erroneous with independent probability 1 − p. â€...
Michael Ben-Or, Avinatan Hassidim
ICMCS
2008
IEEE
151views Multimedia» more  ICMCS 2008»
15 years 10 months ago
Fast keyword detection with sparse time-frequency models
We address the problem of keyword spotting in continuous speech streams when training and testing conditions can be different. We propose a keyword spotting algorithm based on spa...
Effrosini Kokiopoulou, Pascal Frossard, Olivier Ve...