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ACL
2012
7 years 19 days ago
Decoding Running Key Ciphers
There has been recent interest in the problem of decoding letter substitution ciphers using techniques inspired by natural language processing. We consider a different type of cla...
Sravana Reddy, Kevin Knight
CVPR
2012
IEEE
7 years 19 days ago
Bridging the past, present and future: Modeling scene activities from event relationships and global rules
This paper addresses the discovery of activities and learns the underlying processes that govern their occurrences over time in complex surveillance scenes. To this end, we propos...
Jagannadan Varadarajan, Rémi Emonet, Jean-M...
AAAI
2011
7 years 10 months ago
Mean Field Inference in Dependency Networks: An Empirical Study
Dependency networks are a compelling alternative to Bayesian networks for learning joint probability distributions from data and using them to compute probabilities. A dependency ...
Daniel Lowd, Arash Shamaei
SDM
2011
SIAM
284views Data Mining» more  SDM 2011»
8 years 1 months ago
The Network Completion Problem: Inferring Missing Nodes and Edges in Networks
While the social and information networks have become ubiquitous, the challenge of collecting complete network data still persists. Many times the collected network data is incomp...
Myunghwan Kim 0002, Jure Leskovec
ICANN
2010
Springer
8 years 11 months ago
Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines
Abstract. Learning algorithms relying on Gibbs sampling based stochastic approximations of the log-likelihood gradient have become a common way to train Restricted Boltzmann Machin...
Asja Fischer, Christian Igel
AAAI
1998
8 years 11 months ago
Knowledge Lean Word-Sense Disambiguation
We present a corpus{based approach to word{sense disambiguation that only requires information that can be automatically extracted from untagged text. We use unsupervised techniqu...
Ted Pedersen, Rebecca F. Bruce
SODA
2008
ACM
135views Algorithms» more  SODA 2008»
8 years 11 months ago
Rapid mixing of Gibbs sampling on graphs that are sparse on average
Gibbs sampling also known as Glauber dynamics is a popular technique for sampling high dimensional distributions defined on graphs. Of special interest is the behavior of Gibbs sa...
Elchanan Mossel, Allan Sly
NIPS
2007
8 years 11 months ago
Privacy-Preserving Belief Propagation and Sampling
We provide provably privacy-preserving versions of belief propagation, Gibbs sampling, and other local algorithms — distributed multiparty protocols in which each party or verte...
Michael Kearns, Jinsong Tan, Jennifer Wortman
ICLP
2010
Springer
9 years 1 months ago
Improving the Efficiency of Gibbs Sampling for Probabilistic Logical Models by Means of Program Specialization
Abstract. There is currently a large interest in probabilistic logical models. A popular algorithm for approximate probabilistic inference with such models is Gibbs sampling. From ...
Daan Fierens
INFOCOM
2003
IEEE
9 years 3 months ago
Server-based Inference of Internet Link Lossiness
— We investigate the problem of inferring the packet loss characteristics of Internet links using server-based measurements. Unlike much of existing work on network tomography th...
Venkata N. Padmanabhan, Lili Qiu, Helen J. Wang
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