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» Budgeted Nonparametric Learning from Data Streams
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PAKDD
2004
ACM
137views Data Mining» more  PAKDD 2004»
15 years 5 months ago
Fast and Light Boosting for Adaptive Mining of Data Streams
Supporting continuous mining queries on data streams requires algorithms that (i) are fast, (ii) make light demands on memory resources, and (iii) are easily to adapt to concept dr...
Fang Chu, Carlo Zaniolo
FLAIRS
2007
15 years 2 months ago
Mining Sequences in Distributed Sensors Data for Energy Production
The desire to predict power generation at a given point in time is essential to power scheduling, energy trading, and availability modeling. The research conducted within is conce...
Mehmed M. Kantardzic, John Gant
SDM
2012
SIAM
355views Data Mining» more  SDM 2012»
13 years 2 months ago
Granger Causality Analysis in Irregular Time Series
Learning temporal causal structures between time series is one of the key tools for analyzing time series data. In many real-world applications, we are confronted with Irregular T...
Mohammad Taha Bahadori, Yan Liu
ICCV
2009
IEEE
16 years 4 months ago
Detection of Human Actions From A Single Example
We present an algorithm for detecting human actions based upon a single given video example of such actions. The proposed method is unsupervised, does not require learning, segm...
Hae Jong Seo, Peyman Milanfar
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
16 years 3 days ago
Practical learning from one-sided feedback
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...
D. Sculley