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» On Combining Dissimilarity Representations
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NIPS
2008
13 years 10 months ago
Natural Image Denoising with Convolutional Networks
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
Viren Jain, H. Sebastian Seung
DAGSTUHL
2006
13 years 10 months ago
Hierarchies Relating Topology and Geometry
Cognitive Vision has to represent, reason and learn about objects in its environment it has to manipulate and react to. There are deformable objects like humans which cannot be des...
Walter G. Kropatsch, Yll Haxhimusa, Pascal Lienhar...
IJCAI
2001
13 years 10 months ago
Executing Reactive, Model-based Programs through Graph-based Temporal Planning
In the future, webs of unmanned air and space vehicles will act together to robustly perform elaborate missions in uncertain environments. We coordinate these systems by introduci...
Phil Kim, Brian C. Williams, Mark Abramson
SDM
2004
SIAM
211views Data Mining» more  SDM 2004»
13 years 10 months ago
Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
Databases are a key technology for molecular biology which is a very data intensive discipline. Since molecular biological databases are rather heterogeneous, unification and data...
Hans-Peter Kriegel, Peer Kröger, Alexey Pryak...
AAAI
1997
13 years 10 months ago
Model Minimization in Markov Decision Processes
Many stochastic planning problems can be represented using Markov Decision Processes (MDPs). A difficulty with using these MDP representations is that the common algorithms for so...
Thomas Dean, Robert Givan