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» Evaluating algorithms that learn from data streams
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NOSSDAV
2004
Springer
15 years 9 months ago
AMPS: a flexible, scalable proxy testbed for implementing streaming services
— We present the design, implementation, and performance evaluation of AMPS — a flexible, scalable proxy testbed that supports a wide and extensible set of next-generation pro...
Xiaolan (Ellen) Zhang, Michael K. Bradshaw, Yang G...
ICML
2002
IEEE
16 years 5 months ago
Learning from Scarce Experience
Searching the space of policies directly for the optimal policy has been one popular method for solving partially observable reinforcement learning problems. Typically, with each ...
Leonid Peshkin, Christian R. Shelton
NIPS
1994
15 years 5 months ago
Factorial Learning and the EM Algorithm
Many real world learning problems are best characterized by an interaction of multiple independent causes or factors. Discovering such causal structure from the data is the focus ...
Zoubin Ghahramani
ALT
2007
Springer
16 years 1 months ago
Learning Kernel Perceptrons on Noisy Data Using Random Projections
In this paper, we address the issue of learning nonlinearly separable concepts with a kernel classifier in the situation where the data at hand are altered by a uniform classific...
Guillaume Stempfel, Liva Ralaivola
ADMA
2006
Springer
121views Data Mining» more  ADMA 2006»
15 years 10 months ago
A New Polynomial Time Algorithm for Bayesian Network Structure Learning
We propose a new algorithm called SCD for learning the structure of a Bayesian network. The algorithm is a kind of constraintbased algorithm. By taking advantage of variable orderi...
Sanghack Lee, Jihoon Yang, Sungyong Park