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PAKDD
2010
ACM
212views Data Mining» more  PAKDD 2010»
15 years 8 months ago
Fast Perceptron Decision Tree Learning from Evolving Data Streams
Abstract. Mining of data streams must balance three evaluation dimensions: accuracy, time and memory. Excellent accuracy on data streams has been obtained with Naive Bayes Hoeffdi...
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer...
130
Voted
CF
2010
ACM
15 years 7 months ago
Towards chip-on-chip neuroscience: fast mining of neuronal spike streams using graphics hardware
Computational neuroscience is being revolutionized with the advent of multi-electrode arrays that provide real-time, dynamic perspectives into brain function. Mining neuronal spik...
Yong Cao, Debprakash Patnaik, Sean P. Ponce, Jerem...
128
Voted
ICPR
2010
IEEE
15 years 6 months ago
Fast Training of Object Detection Using Stochastic Gradient Descent
Training datasets for object detection problems are typically very large and Support Vector Machine (SVM) implementations are computationally complex. As opposed to these complex ...
Rob Wijnhoven, Peter H. N. De With
127
Voted
ECCV
2010
Springer
15 years 5 months ago
A coarse-to-fine taxonomy of constellations for fast multi-class object detection
In order for recognition systems to scale to a larger number of object categories building visual class taxonomies is important to achieve running times logarithmic in the number o...
167
Voted
ADHOCNOW
2010
Springer
15 years 5 months ago
Coverage-Adaptive Random Walks for Fast Sensory Data Collection
Random walks in wireless sensor networks can serve as fully local, very simple strategies for sink motion that reduce energy dissipation a lot but increase the latency of data coll...
Constantinos Marios Angelopoulos, Sotiris E. Nikol...