296 search results - page 9 / 60 » How to process uncertainty in machine learning |
KI
2008
Springer
13 years 8 months ago
2008
Springer
Music production relies increasingly on advanced hardware and software tools that makes the creative process more flexible and versatile. The advancement of these tools helps reduc...
DSMML
2004
Springer
14 years 2 months ago
2004
Springer
The equivalent kernel [1] is a way of understanding how Gaussian process regression works for large sample sizes based on a continuum limit. In this paper we show how to approximat...
Presentation
Computer vision has been studied for more than 40 years. Due to the increasingly diverse and rapidly developed topics in vision and the related fields (e.g., machine learning, sign...
ICIAP
2009
ACM
14 years 9 months ago
2009
ACM
Abstract. Score functions induced by generative models extract fixeddimensions feature vectors from different-length data observations by subsuming the process of data generation, ...
AAAI
2000
13 years 10 months ago
2000
Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...