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» Machine Learning by Function Decomposition
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HCI
2009
14 years 11 months ago
Combining Electroencephalograph and Functional Near Infrared Spectroscopy to Explore Users' Mental Workload
We discuss the physiological metrics that can be measured with electroencephalography (EEG) and functional near infrared spectroscopy (fNIRs). We address the functional and practic...
Leanne M. Hirshfield, Krysta Chauncey, Rebecca Gul...
ICML
2003
IEEE
16 years 2 months ago
Planning in the Presence of Cost Functions Controlled by an Adversary
We investigate methods for planning in a Markov Decision Process where the cost function is chosen by an adversary after we fix our policy. As a running example, we consider a rob...
H. Brendan McMahan, Geoffrey J. Gordon, Avrim Blum
COLT
2000
Springer
15 years 6 months ago
Entropy Numbers of Linear Function Classes
This paper collects together a miscellany of results originally motivated by the analysis of the generalization performance of the “maximum-margin” algorithm due to Vapnik and...
Robert C. Williamson, Alex J. Smola, Bernhard Sch&...
ICMLA
2009
14 years 11 months ago
Sensitivity Analysis of POMDP Value Functions
In sequential decision making under uncertainty, as in many other modeling endeavors, researchers observe a dynamical system and collect data measuring its behavior over time. The...
Stéphane Ross, Masoumeh T. Izadi, Mark Merc...
ICDM
2009
IEEE
160views Data Mining» more  ICDM 2009»
15 years 8 months ago
Fast Online Training of Ramp Loss Support Vector Machines
—A fast online algorithm OnlineSVMR for training Ramp-Loss Support Vector Machines (SVMR s) is proposed. It finds the optimal SVMR for t+1 training examples using SVMR built on t...
Zhuang Wang, Slobodan Vucetic