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Temporal patterning of 'unlearnable' stimuli types does not always enable learning

Related publications (35)

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Robust Distributed Learning and Robust Learning Machines (Research Statement)

El Mahdi El Mhamdi

Whether it occurs in artificial or biological substrates, {\it learning} is a {distributed} phenomenon in at least two aspects. First, meaningful data and experiences are rarely found in one location, hence {\it learners} have a strong incentive to work to ...

2019

Learning Control

Sylvain Calinon

This chapter presents an overview of learning approaches for the acquisition of controllers and movement skills in humanoid robots. The term learning control refers to the process of acquiring a control strategy to achieve a task. While the definition is i ...

Springer2019

Learning Control

Sylvain Calinon

Springer2018

Evidence for eligibility traces in human learning

Michael Herzog, Wulfram Gerstner, Kerstin Preuschoff, Marco Philipp Lehmann, He Xu, Vasiliki Liakoni

Whether we prepare a coffee or navigate to a shop: in many tasks we make multiple decisions before reaching a goal. Learning such state-action sequences from sparse reward raises the problem of credit-assignment: which actions out of a long sequence should ...

arXiv2017

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

Learning from Examples in Optical Imaging

Michaël Unser, Demetri Psaltis, Cédric René Jean Vonesch, Ulugbek Kamilov

Imaging systems can be designed using examples and methods similar to the techniques used in deep learning. We describe experimental results demonstrating optical tomography based on the learning approach. ...

OSA2016

Bidirectional Learning of Handwriting Skill in Human-Robot Interaction

Aude Billard, Hang Yin, Ana Paiva

This paper describes the design of a robot agent and associated learning algorithms to help children in handwriting acquisition. The main issue lies in how to program a robot to obtain human-like handwriting and then exploit it to teach children. We propos ...

2015

Linking perceptual learning with identical stimuli to imagery perceptual learning

Michael Herzog, Lukasz Grzeczkowski, Fred Mast, Elisa Tartaglia

Perceptual learning is usually thought to be exclusively driven by the stimuli presented during training (and the underlying synaptic learning rules). In some way, we are slaves of our visual experiences. However, learning can occur even when no stimuli ar ...

Association for Research in Vision and Ophthalmology2015

Diffusion adaptation over networks

Ali H. Sayed

Adaptive networks are well-suited to perform decentralized information processing and optimization tasks and to model various types of self-organized and complex behavior encountered in nature. Adaptive networks consist of a collection of agents with proce ...

Elsevier2014

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