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NECO
2010
103views more  NECO 2010»
13 years 5 months ago
Posterior Weighted Reinforcement Learning with State Uncertainty
Reinforcement learning models generally assume that a stimulus is presented that allows a learner to unambiguously identify the state of nature, and the reward received is drawn f...
Tobias Larsen, David S. Leslie, Edmund J. Collins,...
CDC
2008
IEEE
129views Control Systems» more  CDC 2008»
14 years 1 months ago
Rate of Convergence for Consensus with Delays
— We study the problem of reaching a consensus in the values of a distributed system of agents with time-varying connectivity in the presence of delays. We consider a widely stud...
Pierre-Alexandre Bliman, Angelia Nedic, Asuman E. ...
IJON
1998
163views more  IJON 1998»
13 years 7 months ago
Normalized Gaussian Radial Basis Function networks
: The performances of Normalised RBF (NRBF) nets and standard RBF nets are compared in simple classification and mapping problems. In Normalized RBF networks, the traditional roles...
Guido Bugmann
PODC
2010
ACM
13 years 9 months ago
Distributed data classification in sensor networks
Low overhead analysis of large distributed data sets is necessary for current data centers and for future sensor networks. In such systems, each node holds some data value, e.g., ...
Ittay Eyal, Idit Keidar, Raphael Rom
GLVLSI
1998
IEEE
124views VLSI» more  GLVLSI 1998»
13 years 11 months ago
Non-Refreshing Analog Neural Storage Tailored for On-Chip Learning
In this research, we devised a new simple technique for statically holding analog weights, which does not require periodic refreshing. It further contains a mechanism to locally u...
Bassem A. Alhalabi, Qutaibah M. Malluhi, Rafic A. ...