2245 search results - page 192 / 449 » Metrics that Learn Relevance |
107
Voted
NIPS
2004
15 years 2 months ago
2004
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
113
click to vote
IJCAI
1997
15 years 2 months ago
1997
cal maps provide a useful abstraction for robotic navigation and planning. Although stochastic mapscan theoreticallybe learned using the Baum-Welch algorithm,without strong prior ...
87
Voted
CORR
2010
Springer
15 years 26 days ago
2010
Springer
Knowing the largest rate at which data can be sent on an end-to-end path such that the egress rate is equal to the ingress rate with high probability can be very practical when ch...
82
Voted
ICASSP
2011
IEEE
14 years 4 months ago
2011
IEEE
In semi-supervised classification boosting, a similarity measure is demanded in order to measure the distance between samples (both labeled and unlabeled). However, most of the e...
95
Voted
AGILEDC
2007
IEEE
15 years 7 months ago
2007
IEEE
This report examines how the VeriSign Managed Security Services team (MSS) has successfully extended agile software development practices to deal with a complex, multi-product dev...