Results 1  10
of
728,760
Perseus: Randomized pointbased value iteration for POMDPs
 Journal of Artificial Intelligence Research
, 2005
"... Partially observable Markov decision processes (POMDPs) form an attractive and principled framework for agent planning under uncertainty. Pointbased approximate techniques for POMDPs compute a policy based on a finite set of points collected in advance from the agent’s belief space. We present a ra ..."
Abstract

Cited by 204 (17 self)
 Add to MetaCart
randomized pointbased value iteration algorithm called Perseus. The algorithm performs approximate value backup stages, ensuring that in each backup stage the value of each point in the belief set is improved; the key observation is that a single backup may improve the value of many belief points. Contrary
A Critical Point For Random Graphs With A Given Degree Sequence
, 2000
"... Given a sequence of nonnegative real numbers 0 ; 1 ; : : : which sum to 1, we consider random graphs having approximately i n vertices of degree i. Essentially, we show that if P i(i \Gamma 2) i ? 0 then such graphs almost surely have a giant component, while if P i(i \Gamma 2) i ! 0 the ..."
Abstract

Cited by 507 (8 self)
 Add to MetaCart
Given a sequence of nonnegative real numbers 0 ; 1 ; : : : which sum to 1, we consider random graphs having approximately i n vertices of degree i. Essentially, we show that if P i(i \Gamma 2) i ? 0 then such graphs almost surely have a giant component, while if P i(i \Gamma 2) i ! 0
random point field By
"... We investigate the variance of linear statistics of the Ginibre random point field. We generalize the result obtained by the second author to higher order moments and also to functions with rotational and radial perturbations. Our result is motivated by the construction of a solution of the infinite ..."
Abstract
 Add to MetaCart
We investigate the variance of linear statistics of the Ginibre random point field. We generalize the result obtained by the second author to higher order moments and also to functions with rotational and radial perturbations. Our result is motivated by the construction of a solution
Clustering by passing messages between data points
 Science
, 2007
"... Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Such “exemplars ” can be found by randomly choosing an initial subset of data points and then iteratively refining it, but this works well only if that initi ..."
Abstract

Cited by 696 (8 self)
 Add to MetaCart
Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Such “exemplars ” can be found by randomly choosing an initial subset of data points and then iteratively refining it, but this works well only
Effects with Random Assignment: Results for Dartmouth Roommates
, 2001
"... This paper uses a unique data set to measure peer effects among college roommates. Freshman year roommates and dormmates are randomly assigned at Dartmouth College. I find that peers have an impact on grade point average and on decisions to join social groups such as fraternities. Residential peer e ..."
Abstract

Cited by 554 (6 self)
 Add to MetaCart
This paper uses a unique data set to measure peer effects among college roommates. Freshman year roommates and dormmates are randomly assigned at Dartmouth College. I find that peers have an impact on grade point average and on decisions to join social groups such as fraternities. Residential peer
Fast and robust fixedpoint algorithms for independent component analysis
 IEEE TRANS. NEURAL NETW
, 1999
"... Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into components that are statistically as independent from each other as possible. In this paper, we use a combination of two different approaches for linear ICA: Comon’s informat ..."
Abstract

Cited by 884 (34 self)
 Add to MetaCart
Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into components that are statistically as independent from each other as possible. In this paper, we use a combination of two different approaches for linear ICA: Comon’s
Indexing schemes for random points
 In Proc. 10th ACMSIAM Symp. Discrete Algorithms
, 1999
"... Abstract We investigate the tradeoff between storage redundancy and access overhead for indexing random ddimensional point sets. We show that with high probability a rangequery workload of n random points has polylogarithmic tradeoff; more precisely, there is a constant cB;d such that every index ..."
Abstract

Cited by 2 (1 self)
 Add to MetaCart
Abstract We investigate the tradeoff between storage redundancy and access overhead for indexing random ddimensional point sets. We show that with high probability a rangequery workload of n random points has polylogarithmic tradeoff; more precisely, there is a constant cB;d such that every
Dynamics of Random Early Detection
 In Proceedings of ACM SIGCOMM
, 1997
"... In this paper we evaluate the effectiveness of Random Early Detection (RED) over traffic types categorized as nonadaptive, fragile and robust, according to their responses to congestion. We point out that RED allows unfair bandwidth sharing when a mixture of the three traffic types shares a link Thi ..."
Abstract

Cited by 465 (1 self)
 Add to MetaCart
In this paper we evaluate the effectiveness of Random Early Detection (RED) over traffic types categorized as nonadaptive, fragile and robust, according to their responses to congestion. We point out that RED allows unfair bandwidth sharing when a mixture of the three traffic types shares a link
GEOMETRICAL PROBABILITY AND RANDOM POINTS ON
"... 0. Summary. This paper is concerned with the properties of convex cones and their dual cones generated by points randomly distributed on the surface of a dsphere. For radially symmetric distributions on the points, the expected nGmber of kfaces and natural measure of the set of kfaces will be fou ..."
Abstract
 Add to MetaCart
0. Summary. This paper is concerned with the properties of convex cones and their dual cones generated by points randomly distributed on the surface of a dsphere. For radially symmetric distributions on the points, the expected nGmber of kfaces and natural measure of the set of k
Results 1  10
of
728,760