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AAAI
2012
6 years 11 months ago
An Object-Based Bayesian Framework for Top-Down Visual Attention
We introduce a new task-independent framework to model top-down overt visual attention based on graphical models for probabilistic inference and reasoning. We describe a Dynamic B...
Ali Borji, Dicky N. Sihite, Laurent Itti
AAAI
2012
6 years 11 months ago
A Tractable First-Order Probabilistic Logic
Tractable subsets of first-order logic are a central topic in AI research. Several of these formalisms have been used as the basis for first-order probabilistic languages. Howev...
Pedro Domingos, William Austin Webb
IUI
2012
ACM
7 years 5 months ago
Probabilistic pointing target prediction via inverse optimal control
Numerous interaction techniques have been developed that make “virtual” pointing at targets in graphical user interfaces easier than analogous physical pointing tasks by invok...
Brian D. Ziebart, Anind K. Dey, J. Andrew Bagnell
FTCGV
2011
122views more  FTCGV 2011»
8 years 27 days ago
Structured Learning and Prediction in Computer Vision
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structur...
Sebastian Nowozin, Christoph H. Lampert
CVIU
2011
8 years 28 days ago
Single and sparse view 3D reconstruction by learning shape priors
In this paper, we aim to reconstruct free-form 3D models from only one or few silhouettes by learning the prior knowledge of a specific class of objects. Instead of heuristically...
Yu Chen, Roberto Cipolla
CHI
2011
ACM
8 years 1 months ago
AnglePose: robust, precise capacitive touch tracking via 3d orientation estimation
We present a finger-tracking system for touch-based interaction which can track 3D finger angle in addition to position, using low-resolution conventional capacitive sensors, th...
Simon Rogers, John Williamson, Craig Stewart, Rode...
AI
2002
Springer
8 years 9 months ago
On the Role of Contextual Weak Independence in Probabilistic Inference
Previous experimental results have clearly demonstrated the effectiveness of utilizing context-specific independence (CSI) in probabilistic inference. However, CSI is a special cas...
Cory J. Butz, Manon J. Sanscartier
ECAI
2010
Springer
8 years 10 months ago
Context-Specific Independence in Directed Relational Probabilistic Models and its Influence on the Efficiency of Gibbs Sampling
Abstract. There is currently a large interest in relational probabilistic models. While the concept of context-specific independence (CSI) has been well-studied for models such as ...
Daan Fierens
AAAI
1990
8 years 10 months ago
Symbolic Probabilistic Inference in Belief Networks
The Symbolic Probabilistic Inference (SPI) Algorithm [D'Ambrosio, 19891 provides an efficient framework for resolving general queries on a belief network. It applies the conc...
Ross D. Shachter, Bruce D'Ambrosio, Brendan Del Fa...
UAI
1998
8 years 10 months ago
Context-specific approximation in probabilistic inference
There is evidence that the numbers in probabilistic inference don't really matter. This paper considers the idea that we can make a probabilistic model simpler by making fewe...
David Poole
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