Machine learning day

Organizers

RBCS(1), TERA(2), Plus Lab(3), Slipguru(4)

(1) Robotics, Brain and Cognitive Science Department, Italian Institute of Technology (IIT), Via Morego, 30 16163 Genova, Italy. Ph: +39 010 71781411, contact email: giorgio.metta_(at)_iit.it

(2) Telerobotics and applications, Italian Institute of Technology (IIT), Via Morego, 30 16163 Genova, Italy. Ph: +39 010 71781401, contact email: jean-guy.fontaine_(at)_iit.it

(3) Pattern analysis, Learning, and image Understanding Systems lab, Italian Institute of Technology (IIT), Via Morego, 30 16163 Genova, Italy. Ph: +39 010 71781504, contact email: vittorio.murino_(at)_iit.it

(4) Slipguru, University of Genoa, Via Dodecaneso, 35 16146 Genova, Italy Ph: +39 010 3536667, contact email: verri_(at)_disi.unige.it

When and where

The workshop is held at IIT (meeting room 4th floor) on June 8th, 2010. Overhead projectors are available. The meeting might be video recorded.

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Agenda This is a tentative agenda. We need to close by 5pm (a few people have to catch a plane). Time Speaker, title, affiliation Notes 10.00-10.15 Giorgio Metta: Welcome and introduction RBCS 10.15-10.30 Alessandro Verri: A brief introduction to Slipguru Slipguru 10.30-10.50 Curzio Basso: Slipguru approach to learning Slipguru -pdf- 10.50-11.30 Coffee break 3rd floor RBCS 11.30-12.00 Alessio Del Bue: Large-scale optimisation of bilinear models with manifold constraints in Computer Vision abstract, Plus -pdf- 12.00-12.20 Francesca Odone: What we did and do in computer vision Slipguru -pdf- 12.20-13.30 Lunch break 3rd floor RBCS 13.30-14.00 Stephn Hart: Learning Generalizable Control Programs abstract, RBCS -pdf- 14.00-14.20 Matteo Santoro: Learning algorithms for medical image analysis Slipguru -pdf- 14.20-14.50 Arjan Gijsberts: Incremental Learning of Robot Dynamics with Constant Complexity RBCS -pdf- 14.50-15.10 Annalisa Barla: How we learned to cope with molecular biology data Slipguru -pdf- 15.10-15.40 Coffee break 15.40-16.10 Carlo Ciliberto: Recognition of self-controllable body parts via online Multiple Instance Learning abstract, RBCS -pdf- 16.10-17.00 Concluding remarks (time allowance for possible delays)

Objectives

• To mutually understand activities in machine learning and computer vision
• To look for potential overlap of activities and collaborations
• To learn!

Intended audience

This workshop has a broad audience, IIT or DISI people are welcome to attend. Our PhD students are especially encouraged to participate.

Acknowledgements

All the participants.

References

• [1] Nosengo N.. "Robotics: The bot that plays ball" Nature Vol 460, 1076-1078 (2009) doi:10.1038/4601076a.