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» Approximation algorithms for budgeted learning problems
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ML
2006
ACM
13 years 6 months ago
Universal parameter optimisation in games based on SPSA
Most game programs have a large number of parameters that are crucial for their performance. While tuning these parameters by hand is rather difficult, efficient and easy to use ge...
Levente Kocsis, Csaba Szepesvári
UAI
2004
13 years 7 months ago
Recovering Articulated Object Models from 3D Range Data
We address the problem of unsupervised learning of complex articulated object models from 3D range data. We describe an algorithm whose input is a set of meshes corresponding to d...
Dragomir Anguelov, Daphne Koller, Hoi-Cheung Pang,...
SIGECOM
2010
ACM
183views ECommerce» more  SIGECOM 2010»
13 years 11 months ago
The unavailable candidate model: a decision-theoretic view of social choice
One of the fundamental problems in the theory of social choice is aggregating the rankings of a set of agents (or voters) into a consensus ranking. Rank aggregation has found appl...
Tyler Lu, Craig Boutilier
ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
14 years 19 days ago
A Bayesian approach to empirical local linearization for robotics
— Local linearizations are ubiquitous in the control of robotic systems. Analytical methods, if available, can be used to obtain the linearization, but in complex robotics system...
Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, St...
MMAS
2011
Springer
13 years 1 months ago
Scalable Bayesian Reduced-Order Models for Simulating High-Dimensional Multiscale Dynamical Systems
While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and thei...
Phaedon-Stelios Koutsourelakis, Elias Bilionis