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SIGMETRICS
2011
ACM
208views Hardware» more  SIGMETRICS 2011»
14 years 3 months ago
Structure-aware sampling on data streams
The massive data streams observed in network monitoring, data processing and scientific studies are typically too large to store. For many applications over such data, we must ob...
Edith Cohen, Graham Cormode, Nick G. Duffield
117
Voted
ECCV
2006
Springer
16 years 2 months ago
Sampling Strategies for Bag-of-Features Image Classification
Abstract. Bag-of-features representations have recently become popular for content based image classification owing to their simplicity and good performance. They evolved from text...
Eric Nowak, Frédéric Jurie, Bill Tri...
BMCBI
2006
165views more  BMCBI 2006»
15 years 20 days ago
Improved variance estimation of classification performance via reduction of bias caused by small sample size
Background: Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm tha...
Ulrika Wickenberg-Bolin, Hanna Göransson, M&a...
SODA
2008
ACM
88views Algorithms» more  SODA 2008»
15 years 2 months ago
Sampling stable marriages: why spouse-swapping won't work
We study the behavior of random walks along the edges of the stable marriage lattice for various restricted families of allowable preference sets. In the "k-attribute model,&...
Nayantara Bhatnagar, Sam Greenberg, Dana Randall
107
Voted
NIPS
1998
15 years 1 months ago
Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms
In this paper, we address two issues of long-standing interest in the reinforcement learning literature. First, what kinds of performance guarantees can be made for Q-learning aft...
Michael J. Kearns, Satinder P. Singh