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ICML
2007
IEEE
16 years 7 months ago
Efficiently computing minimax expected-size confidence regions
Given observed data and a collection of parameterized candidate models, a 1- confidence region in parameter space provides useful insight as to those models which are a good fit t...
Brent Bryan, H. Brendan McMahan, Chad M. Schafer, ...
ICML
2008
IEEE
16 years 7 months ago
Fast incremental proximity search in large graphs
In this paper we investigate two aspects of ranking problems on large graphs. First, we augment the deterministic pruning algorithm in Sarkar and Moore (2007) with sampling techni...
Purnamrita Sarkar, Andrew W. Moore, Amit Prakash
ICML
1999
IEEE
16 years 7 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
WWW
2005
ACM
16 years 7 months ago
TotalRank: ranking without damping
PageRank is defined as the stationary state of a Markov chain obtained by perturbing the transition matrix of a web graph with a damping factor that spreads part of the rank. The...
Paolo Boldi
STOC
2003
ACM
142views Algorithms» more  STOC 2003»
16 years 7 months ago
Optimal probabilistic fingerprint codes
We construct binary codes for fingerprinting. Our codes for n users that are -secure against c pirates have length O(c2 log(n/ )). This improves the codes proposed by Boneh and Sh...
Gábor Tardos