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NECO
2002
104views more  NECO 2002»
15 years 4 months ago
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Harri Valpola, Juha Karhunen
125
Voted
IMC
2005
ACM
15 years 10 months ago
Exploiting Underlying Structure for Detailed Reconstruction of an Internet-scale Event
Network “telescopes” that record packets sent to unused blocks of Internet address space have emerged as an important tool for observing Internet-scale events such as the spre...
Abhishek Kumar, Vern Paxson, Nicholas Weaver
AIR
2005
85views more  AIR 2005»
15 years 4 months ago
On Paradox of Fuzzy Modeling: Supervised Learning for Rectifying Fuzzy Membership Function
The paradox of fuzzy modeling is recognized due to the co-existence of its effectiveness of solving uncertain problems in the real world and the skepticism of its reasonability in ...
Shaopei Lin
152
Voted
CORR
2002
Springer
91views Education» more  CORR 2002»
15 years 4 months ago
Data Engineering for the Analysis of Semiconductor Manufacturing Data
We have analyzed manufacturing data from several different semiconductor manufacturing plants, using decision tree induction software called Q-YIELD. The software generates rules ...
Peter D. Turney
NIPS
2003
15 years 6 months ago
Multiple-Instance Learning via Disjunctive Programming Boosting
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
Stuart Andrews, Thomas Hofmann