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» Evaluating algorithms that learn from data streams
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ATAL
2007
Springer
16 years 19 days ago
Sharing experiences to learn user characteristics in dynamic environments with sparse data
This paper investigates the problem of estimating the value of probabilistic parameters needed for decision making in environments in which an agent, operating within a multi-agen...
David Sarne, Barbara J. Grosz
GIS
2007
ACM
16 years 7 months ago
Approximate order-k Voronoi cells over positional streams
Handling streams of positional updates from numerous moving objects has become a challenging task for many monitoring applications. Several algorithms have been recently proposed ...
Kostas Patroumpas, Theofanis Minogiannis, Timos K....
JMLR
2002
106views more  JMLR 2002»
15 years 6 months ago
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
PE
2008
Springer
108views Optimization» more  PE 2008»
15 years 6 months ago
Rate-optimal schemes for Peer-to-Peer live streaming
In this paper we consider the problem of sending data in real time from information sources to sets of receivers, using peer-to-peer communications. We consider several models of ...
Laurent Massoulié, Andrew Twigg
FOIKS
2008
Springer
16 years 3 months ago
Cost-minimising strategies for data labelling : optimal stopping and active learning
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
Christos Dimitrakakis, Christian Savu-Krohn