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SODA
2008
ACM
111views Algorithms» more  SODA 2008»
13 years 9 months ago
On distance to monotonicity and longest increasing subsequence of a data stream
In this paper we consider problems related to the sortedness of a data stream. First we investigate the problem of estimating the distance to monotonicity; given a sequence of len...
Funda Ergün, Hossein Jowhari
TIP
2008
133views more  TIP 2008»
13 years 7 months ago
A Recursive Model-Reduction Method for Approximate Inference in Gaussian Markov Random Fields
This paper presents recursive cavity modeling--a principled, tractable approach to approximate, near-optimal inference for large Gauss-Markov random fields. The main idea is to su...
Jason K. Johnson, Alan S. Willsky
NIPS
2003
13 years 8 months ago
Sample Propagation
Rao–Blackwellization is an approximation technique for probabilistic inference that flexibly combines exact inference with sampling. It is useful in models where conditioning o...
Mark A. Paskin
JMLR
2010
192views more  JMLR 2010»
13 years 2 months ago
Efficient Learning of Deep Boltzmann Machines
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
Ruslan Salakhutdinov, Hugo Larochelle
AINA
2009
IEEE
13 years 5 months ago
Approximating Travel Times Using Opportunistic Networking
Determining the time and means by which to travel from location A to location B for a person utilising a MANET requires the dissemination of both realtime and historic data. In thi...
Rudi Ball, Naranker Dulay