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KDD
2004
ACM
127views Data Mining» more  KDD 2004»
16 years 6 months ago
A generative probabilistic approach to visualizing sets of symbolic sequences
There is a notable interest in extending probabilistic generative modeling principles to accommodate for more complex structured data types. In this paper we develop a generative ...
Peter Tiño, Ata Kabán, Yi Sun
CLOR
2006
15 years 10 months ago
Comparison of Generative and Discriminative Techniques for Object Detection and Classification
Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the dis...
Ilkay Ulusoy, Christopher M. Bishop
COLT
2006
Springer
15 years 10 months ago
Discriminative Learning Can Succeed Where Generative Learning Fails
Generative algorithms for learning classifiers use training data to separately estimate a probability model for each class. New items are classified by comparing their probabiliti...
Philip M. Long, Rocco A. Servedio
ACSAC
2003
IEEE
15 years 11 months ago
Practical Random Number Generation in Software
There is a large gap between the theory and practice for random number generation. For example, on most operating systems, using /dev/random to generate a 256-bit AES key is highl...
John Viega
ICRA
2003
IEEE
137views Robotics» more  ICRA 2003»
15 years 11 months ago
Biped walking pattern generation by using preview control of zero-moment point
We introduce a new method of a biped walking pattern generation by using a preview control of the zeromoment point (ZMP). First, the dynamics of a biped robot is modeled as a runn...
Shuuji Kajita, Fumio Kanehiro, Kenji Kaneko, Kiyos...