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IJAR
2008
155views more  IJAR 2008»
15 years 6 months ago
Estimation of causal effects using linear non-Gaussian causal models with hidden variables
The task of estimating causal effects from non-experimental data is notoriously difficult and unreliable. Nevertheless, precisely such estimates are commonly required in many fiel...
Patrik O. Hoyer, Shohei Shimizu, Antti J. Kerminen...
JMLR
2008
209views more  JMLR 2008»
15 years 6 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
OOPSLA
2007
Springer
16 years 8 days ago
IAnticorruption: a domain-driven design approach to more robust integration
Custom House's new currency exchange system is integrated with a legacy system. After a few years of growth, the two systems were so intricately tangled that even small chang...
Sam Peng, Ying Hu
CVPR
2003
IEEE
15 years 11 months ago
Bayesian Human Segmentation in Crowded Situations
Problem of segmenting individual humans in crowded situations from stationary video camera sequences is exacerbated by object inter-occlusion. We pose this problem as a “model-b...
Tao Zhao, Ramakant Nevatia
191
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ACMACE
2009
ACM
15 years 7 months ago
Developing multiplayer pervasive games and networked interactive installations using ad hoc mobile sensor nets
We here present Fun in Numbers (FinN), a framework for developing pervasive applications and interactive installations for entertainment and educational purposes. Using ad hoc mob...
Orestis Akribopoulos, Marios Logaras, Nikos Vasila...