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» Issues in Temporal and Causal Inference
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ECCV
2000
Springer
14 years 9 months ago
Learning Over Multiple Temporal Scales in Image Databases
Abstract. The ability to learn from user interaction is an important asset for content-based image retrieval (CBIR) systems. Over short times scales, it enables the integration of ...
Nuno Vasconcelos, Andrew Lippman
ASPLOS
2006
ACM
14 years 1 months ago
Type inference for unboxed types and first class mutability
Systems programs rely on fine-grain control of data representation and use of state to achieve performance, conformance to hardware specification, and temporal predictability. T...
Swaroop Sridhar, Jonathan S. Shapiro
NIPS
2004
13 years 8 months ago
Bayesian inference in spiking neurons
We propose a new interpretation of spiking neurons as Bayesian integrators accumulating evidence over time about events in the external world or the body, and communicating to oth...
Sophie Deneve
CVPR
2010
IEEE
14 years 3 months ago
Spike Train Driven Dynamical Models for Human Actions
We investigate dynamical models of human motion that can support both synthesis and analysis tasks. Unlike coarser discriminative models that work well when action classes are ...
Michalis Raptis, Kamil Wnuk , Stefano Soatto
BMCBI
2008
166views more  BMCBI 2008»
13 years 7 months ago
Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual informa
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
Weijun Luo, Kurt D. Hankenson, Peter J. Woolf