36 search results - page 1 / 8 » Worst-Case Analysis of the Perceptron and Exponentiated Upda... |
AI
1998
Springer
14 years 9 months ago
1998
Springer
The absolute loss is the absolute difference between the desired and predicted outcome. This paper demonstrates worst-case upper bounds on the absolute loss for the Perceptron le...
86
Voted
AAAI
1997
14 years 11 months ago
1997
The absolute loss is the absolute difference between the desired and predicted outcome. I demonstrateworst-case upper bounds on the absolute loss for the perceptron algorithm and ...
ISAAC
2009
Springer
15 years 4 months ago
2009
Springer
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
STACS
2005
Springer
15 years 3 months ago
2005
Springer
Abstract. In recent years, probabilistic analyses of algorithms have received increasing attention. Despite results on the average-case complexity and smoothed complexity of exact ...
COLT
2005
Springer
15 years 3 months ago
2005
Springer
Abstract. We present a generalization of the Perceptron algorithm. The new algorithm performs a Perceptron-style update whenever the margin of an example is smaller than a predefi...