100 search results - page 1 / 20 » Is "best-so-far" a good algorithmic performance me... |
GECCO
2008
Springer
13 years 5 months ago
2008
Springer
In evolutionary computation, experimental results are commonly analyzed using an algorithmic performance metric called best-so-far. While best-so-far can be a useful metric, its u...
GECCO
2007
Springer
13 years 8 months ago
2007
Springer
We have developed a technique to characterize software developers' styles using a set of source code metrics. This style fingerprint can be used to identify the likely author...
NIPS
2008
13 years 6 months ago
2008
Metric learning algorithms can provide useful distance functions for a variety of domains, and recent work has shown good accuracy for problems where the learner can access all di...
COLT
2008
Springer
13 years 6 months ago
2008
Springer
We study the problem of clustering discrete probability distributions with respect to the Kullback-Leibler (KL) divergence. This problem arises naturally in many applications. Our...
CVPR
2007
IEEE
14 years 6 months ago
2007
IEEE
A good distance metric is crucial for unsupervised learning from high-dimensional data. To learn a metric without any constraint or class label information, most unsupervised metr...