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» Structural Modelling with Sparse Kernels
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DCC
2007
IEEE
15 years 9 months ago
Spatial Sparsity Induced Temporal Prediction for Hybrid Video Compression
In this paper we propose a new motion compensated prediction technique that enables successful predictive encoding during fades, blended scenes, temporally decorrelated noise, and...
Gang Hua, Onur G. Guleryuz
ICML
2009
IEEE
15 years 10 months ago
Nonparametric factor analysis with beta process priors
We propose a nonparametric extension to the factor analysis problem using a beta process prior. This beta process factor analysis (BPFA) model allows for a dataset to be decompose...
John William Paisley, Lawrence Carin
IJON
2006
123views more  IJON 2006»
14 years 10 months ago
Attractor neural networks with patchy connectivity
The neurons in the mammalian visual cortex are arranged in columnar structures, and the synaptic contacts of the pyramidal neurons in layer II/III are clustered into patches that ...
Christopher Johansson, Martin Rehn, Anders Lansner
JMLR
2006
190views more  JMLR 2006»
14 years 9 months ago
Causal Graph Based Decomposition of Factored MDPs
We present Variable Influence Structure Analysis, or VISA, an algorithm that performs hierarchical decomposition of factored Markov decision processes. VISA uses a dynamic Bayesia...
Anders Jonsson, Andrew G. Barto
CORR
2010
Springer
163views Education» more  CORR 2010»
14 years 8 months ago
Faster Rates for training Max-Margin Markov Networks
Structured output prediction is an important machine learning problem both in theory and practice, and the max-margin Markov network (M3 N) is an effective approach. All state-of-...
Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan