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» Machine-Learning Applications of Algorithmic Randomness
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CVPR
2004
IEEE
14 years 10 months ago
Incremental Density Approximation and Kernel-Based Bayesian Filtering for Object Tracking
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...
SSDBM
2007
IEEE
212views Database» more  SSDBM 2007»
14 years 2 months ago
Adaptive-Size Reservoir Sampling over Data Streams
Reservoir sampling is a well-known technique for sequential random sampling over data streams. Conventional reservoir sampling assumes a fixed-size reservoir. There are situation...
Mohammed Al-Kateb, Byung Suk Lee, Xiaoyang Sean Wa...
GLOBECOM
2010
IEEE
13 years 6 months ago
A Distributed Wake-Up Scheduling for Opportunistic Forwarding in Wireless Sensor Networks
In wireless sensor networks (WSNs), sensor nodes are typically subjected to energy constraints and often prone to topology changes. While duty cycling has been widely used for ener...
Chul-Ho Lee, Do Young Eun
APPROX
2004
Springer
121views Algorithms» more  APPROX 2004»
14 years 1 months ago
Small Pseudo-random Families of Matrices: Derandomizing Approximate Quantum Encryption
A quantum encryption scheme (also called private quantum channel, or state randomization protocol) is a one-time pad for quantum messages. If two parties share a classical random s...
Andris Ambainis, Adam Smith
EOR
2010
88views more  EOR 2010»
13 years 8 months ago
Mathematical programming approaches for generating p-efficient points
Abstract: Probabilistically constrained problems, in which the random variables are finitely distributed, are nonconvex in general and hard to solve. The p-efficiency concept has b...
Miguel A. Lejeune, Nilay Noyan