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CVPR
2011
IEEE
13 years 3 months ago
Combining Randomization and Discrimination for Fine-Grained Image Categorization
In this paper, we study the problem of fine-grained image categorization. The goal of our method is to explore fine image statistics and identify the discriminative image patche...
Bangpeng Yao, Aditya Khosla, Li Fei-Fei
JAIR
2011
187views more  JAIR 2011»
13 years 2 months ago
A Monte-Carlo AIXI Approximation
This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
Joel Veness, Kee Siong Ng, Marcus Hutter, William ...
INFOCOM
2011
IEEE
12 years 11 months ago
Forwarding anomalies in Bloom filter-based multicast
Abstract—Several recently proposed multicast protocols use inpacket Bloom filters to encode multicast trees. These mechanisms are in principle highly scalable because no per-fl...
Mikko Särelä, Christian Esteve Rothenber...
ML
2012
ACM
413views Machine Learning» more  ML 2012»
12 years 3 months ago
Gradient-based boosting for statistical relational learning: The relational dependency network case
Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are...
Sriraam Natarajan, Tushar Khot, Kristian Kersting,...
CVPR
2008
IEEE
14 years 9 months ago
Learning and using taxonomies for fast visual categorization
The computational complexity of current visual categorization algorithms scales linearly at best with the number of categories. The goal of classifying simultaneously Ncat = 104 -...
Gregory Griffin, Darya Perona