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ICASSP
2010
IEEE
13 years 8 months ago
A minimax approach to Bayesian estimation with partial knowledge of the observation model
We address the problem of Bayesian estimation where the statistical relation between the signal and measurements is only partially known. We propose modeling partial Baysian knowl...
Tomer Michaeli, Yonina C. Eldar
CJ
2010
131views more  CJ 2010»
13 years 6 months ago
Probabilistic Approaches to Estimating the Quality of Information in Military Sensor Networks
an be used to abstract away from the physical reality by describing it as components that exist in discrete states with probabilistically invoked actions that change the state. The...
Duncan Gillies, David Thornley, Chatschik Bisdikia...
PAMI
2008
162views more  PAMI 2008»
13 years 8 months ago
Dimensionality Reduction of Clustered Data Sets
We present a novel probabilistic latent variable model to perform linear dimensionality reduction on data sets which contain clusters. We prove that the maximum likelihood solution...
Guido Sanguinetti
DATE
2004
IEEE
114views Hardware» more  DATE 2004»
14 years 12 days ago
Workload Characterization Model for Tasks with Variable Execution Demand
The analysis of real-time properties of an embedded system usually relies on the worst-case execution times (WCET) of the tasks to be executed. In contrast to that, in real world ...
Alexander Maxiaguine, Simon Künzli, Lothar Th...
ICML
2010
IEEE
13 years 9 months ago
Gaussian Processes Multiple Instance Learning
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
Minyoung Kim, Fernando De la Torre