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IPMU
2010
Springer
13 years 8 months ago
Approximation of Data by Decomposable Belief Models
It is well known that among all probabilistic graphical Markov models the class of decomposable models is the most advantageous in the sense that the respective distributions can b...
Radim Jirousek
KDD
2007
ACM
167views Data Mining» more  KDD 2007»
14 years 10 months ago
Multiscale topic tomography
Modeling the evolution of topics with time is of great value in automatic summarization and analysis of large document collections. In this work, we propose a new probabilistic gr...
Ramesh Nallapati, Susan Ditmore, John D. Lafferty,...
AAAI
2008
14 years 12 hour ago
Structure Learning on Large Scale Common Sense Statistical Models of Human State
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes
ICDM
2010
IEEE
166views Data Mining» more  ICDM 2010»
13 years 7 months ago
Exponential Family Tensor Factorization for Missing-Values Prediction and Anomaly Detection
In this paper, we study probabilistic modeling of heterogeneously attributed multi-dimensional arrays. The model can manage the heterogeneity by employing an individual exponential...
Kohei Hayashi, Takashi Takenouchi, Tomohiro Shibat...
GLOBECOM
2006
IEEE
14 years 3 months ago
Integrated Data Delivery and Interest Dissemination Techniques for Wireless Sensor Networks
— The paper presents IRIS, an Integrated Routing and Interest dissemination System for wireless sensor networks. The proposed protocols are designed to work under very low duty c...
Michele Mastrogiovanni, Chiara Petrioli, Michele R...