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KDD
2005
ACM
149views Data Mining» more  KDD 2005»
14 years 2 months ago
A distributed learning framework for heterogeneous data sources
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Srujana Merugu, Joydeep Ghosh
FTML
2008
185views more  FTML 2008»
13 years 8 months ago
Graphical Models, Exponential Families, and Variational Inference
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
Martin J. Wainwright, Michael I. Jordan
GLOBECOM
2007
IEEE
14 years 2 months ago
Extension and Comparison of QoS-Enabled Wi-Fi Models in the Presence of Errors
—In this paper we compare and enhance the three prevailing approaches of IEEE 802.11e Performance analysis. Specifically, the first model utilizes a Markov Chain to describe th...
Ioannis Papapanagiotou, Georgios S. Paschos, Stavr...
POPL
2007
ACM
14 years 8 months ago
Program verification as probabilistic inference
In this paper, we propose a new algorithm for proving the validity or invalidity of a pre/postcondition pair for a program. The algorithm is motivated by the success of the algori...
Sumit Gulwani, Nebojsa Jojic
SIGMOD
2011
ACM
250views Database» more  SIGMOD 2011»
12 years 11 months ago
Hybrid in-database inference for declarative information extraction
In the database community, work on information extraction (IE) has centered on two themes: how to effectively manage IE tasks, and how to manage the uncertainties that arise in th...
Daisy Zhe Wang, Michael J. Franklin, Minos N. Garo...