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79
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ICML
2009
IEEE
16 years 1 months ago
The Bayesian group-Lasso for analyzing contingency tables
Group-Lasso estimators, useful in many applications, suffer from lack of meaningful variance estimates for regression coefficients. To overcome such problems, we propose a full Ba...
Sudhir Raman, Thomas J. Fuchs, Peter J. Wild, Edga...
106
Voted
IROS
2007
IEEE
165views Robotics» more  IROS 2007»
15 years 7 months ago
A bayesian conceptualization of space for mobile robots
Abstract— The future of robots, as our companions is dependent on their ability to understand, interpret and represent the environment in a human compatible manner. Towards this ...
Shrihari Vasudevan, Roland Siegwart
113
Voted
ICANN
2003
Springer
15 years 6 months ago
Sparse Coding with Invariance Constraints
We suggest a new approach to optimize the learning of sparse features under the constraints of explicit transformation symmetries imposed on the set of feature vectors. Given a set...
Heiko Wersing, Julian Eggert, Edgar Körner
101
Voted
IJCAI
2007
15 years 2 months ago
Incremental Construction of Structured Hidden Markov Models
This paper presents an algorithm for inferring a Structured Hidden Markov Model (S-HMM) from a set of sequences. The S-HMMs are a sub-class of the Hierarchical Hidden Markov Model...
Ugo Galassi, Attilio Giordana, Lorenza Saitta
95
Voted
ACL
2004
15 years 2 months ago
Unsupervised Sense Disambiguation Using Bilingual Probabilistic Models
We describe two probabilistic models for unsupervised word-sense disambiguation using parallel corpora. The first model, which we call the Sense model, builds on the work of Diab ...
Indrajit Bhattacharya, Lise Getoor, Yoshua Bengio