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An online framework for learning novel concepts over multiple cues

Publications associées (69)

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Theory of representation learning in cortical neural networks

Carlos Stein Naves de Brito

Our brain continuously self-organizes to construct and maintain an internal representation of the world based on the information arriving through sensory stimuli. Remarkably, cortical areas related to different sensory modalities appear to share the same f ...

EPFL2016

Big-Data Streaming Applications Scheduling Based on Staged Multi-armed Bandits

David Atienza Alonso, Karim Kanoun, Cem Tekin

Several techniques have been recently proposed to adapt Big-Data streaming applications to existing many core platforms. Among these techniques, online reinforcement learning methods have been proposed that learn how to adapt at run-time the throughput and ...

Institute of Electrical and Electronics Engineers2016

Big-Data Streaming Applications Scheduling Based on Staged Multi-Armed Bandits

David Atienza Alonso, Karim Kanoun, Cem Tekin

Institute of Electrical and Electronics Engineers2016

Learning of Closed-Loop Motion Control

Jonas Buchli, Farbod Farshidian

Learning motion control as a unified process of designing the reference trajectory and the controller is one of the most challenging problems in robotics. The complexity of the problem prevents most of the existing optimization algorithms from giving satis ...

2014

Perceptual Learning With Indiscriminable Stimuli

Lukasz Grzeczkowski, Fred Mast, Elisa Tartaglia

Perceptual learning is learning to perceive. For example, in a bisection task three parallel lines are presented. The central line is slightly offset towards the right or the left outer line. Observers indicate the offset direction. Training greatly improv ...

2014

Perceptual Learning With Only One Stimulus

Michael Herzog, Lukasz Grzeczkowski, Fred Mast, Elisa Tartaglia

Perceptual learning is learning to see. For example in a bisection task, three parallel lines are presented with the central line slightly offset towards the right or the left outer line. Participants indicate the offset direction. Training gradually impro ...

2014

Assistive technology for supporting learning numeracy

Calculation depends on the majority of the abilities within the domain of general intelligence (Blair et al., 2005). Most major theories of intelligence include numeracy or quantitative thinking as one aspect of general cognitive skills (Kaufman et al., 20 ...

Psychology Press2014

Performance analysis of multitask diffusion adaptation over asynchronous networks

Ali H. Sayed, Roula Nassif

The multitask diffusion LMS algorithm is an efficient strategy to address distributed estimation problems that are multitask-oriented in the sense that the optimum parameter vector may not be the same for every cluster of nodes. In this work, we explore th ...

IEEE2014

Stable Myoelectric Control of a Hand Prosthesis using Non-Linear Incremental Learning

Barbara Caputo

Stable myoelectric control of hand prostheses remains an open problem. The only successful human–machine interface is surface electromyography, typically allowing control of a few degrees of freedom. Machine learning techniques may have the potential to re ...

2014

Autonomous reinforcement learning with experience replay

Ajay Kumar Tanwani

This paper considers the issues of efficiency and autonomy that are required to make reinforcement learning suitable for real-life control tasks. A real-time reinforcement learning algorithm is presented that repeatedly adjusts the control policy with the ...

Pergamon-Elsevier Science Ltd2013