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ALGORITHMICA
2004
84views more  ALGORITHMICA 2004»
15 years 3 months ago
Computing Diameter in the Streaming and Sliding-Window Models
We investigate the diameter problem in the streaming and slidingwindow models. We show that, for a stream of n points or a sliding window of size n, any exact algorithm for diamet...
Joan Feigenbaum, Sampath Kannan, Jian Zhang 0004
SDM
2004
SIAM
123views Data Mining» more  SDM 2004»
15 years 5 months ago
Nonlinear Manifold Learning for Data Stream
There has been a renewed interest in understanding the structure of high dimensional data set based on manifold learning. Examples include ISOMAP [25], LLE [20] and Laplacian Eige...
Martin H. C. Law, Nan Zhang 0002, Anil K. Jain
137
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JMLR
2010
130views more  JMLR 2010»
14 years 10 months ago
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA is designed to deal...
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, P...
SAC
2009
ACM
15 years 10 months ago
Evaluating algorithms that learn from data streams
In the past years, the theory and practice of machine learning and data mining have been focused on static and finite data sets from where learning algorithms generate a static m...
João Gama, Pedro Pereira Rodrigues, Raquel ...
129
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CORR
2012
Springer
209views Education» more  CORR 2012»
13 years 11 months ago
Densest Subgraph in Streaming and MapReduce
The problem of finding locally dense components of a graph is an important primitive in data analysis, with wide-ranging applications from community mining to spam detection and ...
Bahman Bahmani, Ravi Kumar, Sergei Vassilvitskii