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IJON
2007
184views more  IJON 2007»
14 years 11 months ago
Convex incremental extreme learning machine
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Guang-Bin Huang, Lei Chen
98
Voted
NIPS
1998
15 years 1 months ago
Risk Sensitive Reinforcement Learning
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
Ralph Neuneier, Oliver Mihatsch
NIPS
2007
15 years 1 months ago
A New View of Automatic Relevance Determination
Automatic relevance determination (ARD) and the closely-related sparse Bayesian learning (SBL) framework are effective tools for pruning large numbers of irrelevant features leadi...
David P. Wipf, Srikantan S. Nagarajan
ISBI
2008
IEEE
16 years 12 days ago
Increased sensitivity in FMRI group analysis using mixed-effect modeling
In functional Magnetic Resonance Imaging group studies, uncertainties on the individual BOLD responses are not taken into account by standard detection procedures, which may limit...
Merlin Keller, Alexis Roche
STOC
2007
ACM
146views Algorithms» more  STOC 2007»
15 years 12 months ago
Playing games with approximation algorithms
In an online linear optimization problem, on each period t, an online algorithm chooses st S from a fixed (possibly infinite) set S of feasible decisions. Nature (who may be adve...
Sham M. Kakade, Adam Tauman Kalai, Katrina Ligett