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» Algorithm Selection using Reinforcement Learning
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KDD
2004
ACM
135views Data Mining» more  KDD 2004»
14 years 11 months ago
Discovering additive structure in black box functions
Many automated learning procedures lack interpretability, operating effectively as a black box: providing a prediction tool but no explanation of the underlying dynamics that driv...
Giles Hooker
MM
2006
ACM
158views Multimedia» more  MM 2006»
14 years 4 months ago
Extreme video retrieval: joint maximization of human and computer performance
We present an efficient system for video search that maximizes the use of human bandwidth, while at the same time exploiting the machine’s ability to learn in real-time from use...
Alexander G. Hauptmann, Wei-Hao Lin, Rong Yan, Jun...
ICCV
2007
IEEE
15 years 26 days ago
Applications of parametric maxflow in computer vision
The maximum flow algorithm for minimizing energy functions of binary variables has become a standard tool in computer vision. In many cases, unary costs of the energy depend linea...
Vladimir Kolmogorov, Yuri Boykov, Carsten Rother
PVLDB
2010
175views more  PVLDB 2010»
13 years 9 months ago
Dynamic Join Optimization in Multi-Hop Wireless Sensor Networks
To enable smart environments and self-tuning data centers, we are developing the Aspen system for integrating physical sensor data, as well as stream data coming from machine logi...
Svilen R. Mihaylov, Marie Jacob, Zachary G. Ives, ...
NIPS
2007
14 years 10 days ago
A New View of Automatic Relevance Determination
Automatic relevance determination (ARD) and the closely-related sparse Bayesian learning (SBL) framework are effective tools for pruning large numbers of irrelevant features leadi...
David P. Wipf, Srikantan S. Nagarajan