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NIPS
2004
15 years 1 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
NIPS
2004
15 years 1 months ago
Bayesian inference in spiking neurons
We propose a new interpretation of spiking neurons as Bayesian integrators accumulating evidence over time about events in the external world or the body, and communicating to oth...
Sophie Deneve
ATAL
2010
Springer
14 years 12 months ago
Inter-robot transfer learning for perceptual classification
We introduce the novel problem of inter-robot transfer learning for perceptual classification of objects, where multiple heterogeneous robots communicate and transfer learned obje...
Zsolt Kira
MM
2010
ACM
163views Multimedia» more  MM 2010»
14 years 12 months ago
Sonify your face: facial expressions for sound generation
We present a novel visual creativity tool that automatically recognizes facial expressions and tracks facial muscle movements in real time to produce sounds. The facial expression...
Roberto Valenti, Alejandro Jaimes, Nicu Sebe
AROBOTS
2007
159views more  AROBOTS 2007»
14 years 12 months ago
Structure-based color learning on a mobile robot under changing illumination
— A central goal of robotics and AI is to be able to deploy an agent to act autonomously in the real world over an extended period of time. To operate in the real world, autonomo...
Mohan Sridharan, Peter Stone
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