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» Improved bounds on the sample complexity of learning
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UAI
2000
13 years 8 months ago
PEGASUS: A policy search method for large MDPs and POMDPs
We propose a new approach to the problem of searching a space of policies for a Markov decision process (MDP) or a partially observable Markov decision process (POMDP), given a mo...
Andrew Y. Ng, Michael I. Jordan
SIAMCOMP
1998
92views more  SIAMCOMP 1998»
13 years 7 months ago
Surface Approximation and Geometric Partitions
Motivated by applications in computer graphics, visualization, and scienti c computation, we study the computational complexity of the following problem: Given a set S of n points...
Pankaj K. Agarwal, Subhash Suri
ICALP
2010
Springer
14 years 8 days ago
Network Design via Core Detouring for Problems without a Core
Some of the currently best-known approximation algorithms for network design are based on random sampling. One of the key steps of such algorithms is connecting a set of source nod...
Fabrizio Grandoni, Thomas Rothvoß
AIPS
2009
13 years 8 months ago
Information-Theoretic Approach to Efficient Adaptive Path Planning for Mobile Robotic Environmental Sensing
Recent research in robot exploration and mapping has focused on sampling environmental hotspot fields. This exploration task is formalized by Low, Dolan, and Khosla (2008) in a se...
Kian Hsiang Low, John M. Dolan, Pradeep K. Khosla
COLT
2007
Springer
13 years 11 months ago
An Efficient Re-scaled Perceptron Algorithm for Conic Systems
Abstract. The classical perceptron algorithm is an elementary algorithm for solving a homogeneous linear inequality system Ax > 0, with many important applications in learning t...
Alexandre Belloni, Robert M. Freund, Santosh Vempa...