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JMLR
2012
13 years 18 days ago
Deterministic Annealing for Semi-Supervised Structured Output Learning
In this paper we propose a new approach for semi-supervised structured output learning. Our approach uses relaxed labeling on unlabeled data to deal with the combinatorial nature ...
Paramveer S. Dhillon, S. Sathiya Keerthi, Kedar Be...
78
Voted
ICCV
2007
IEEE
16 years 3 days ago
Mixture-of-Parts Pictorial Structures for Objects with Variable Part Sets
For many multi-part object classes, the set of parts can vary not only in location but also in type. For example, player formations in American football involve various subsets of...
Robin Hess, Alan Fern, Eric N. Mortensen
ASPLOS
2006
ACM
15 years 1 months ago
Accurate and efficient regression modeling for microarchitectural performance and power prediction
We propose regression modeling as an efficient approach for accurately predicting performance and power for various applications executing on any microprocessor configuration in a...
Benjamin C. Lee, David M. Brooks
SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
14 years 11 months ago
Learning Markov Network Structure using Few Independence Tests
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Parichey Gandhi, Facundo Bromberg, Dimitris Margar...
NIPS
2004
14 years 11 months ago
Probabilistic Computation in Spiking Populations
As animals interact with their environments, they must constantly update estimates about their states. Bayesian models combine prior probabilities, a dynamical model and sensory e...
Richard S. Zemel, Quentin J. M. Huys, Rama Nataraj...