INVITED SPEAKERS
|
|
|
Marco Gori (Dipartimento di Ingegneria dell'Informazione - Università
di Siena) |
|
|
|
Diffusion learning
by prior and acquired links |
|
A remarkable limitation of most supervised approaches to
machine learning is that they need a lot of labeled examples to attain a
satisfactory generalization to new examples. In order to face this relevant
problem, a number of methods have been devised that operate under the
framework of transductive or semi-supervised
learning. Starting from these premises, I this talk I show the crucial role
of links, either given in advance or properly acquired by unsupervised
learning, for learning in huge collections of data (e.g. in the Web). I
introduce the notion of diffusion learning, whose computational scheme is
very much related to Web ranking algorithms based on link analysis. Diffusion
learning is based on supervision that involves both the content and the
links. The diffusion mechanisms are proposed in a unified view, in which the
prior information expressed by the links turns out to spread evidence through
the entire data collection, regardless of the presence of supervision. I give
very promising experimental results on the learning of functions used in link
analysis, like PageRank, and show the effectiveness
of the proposed theory especially when the rank depends jointly on the page
content and on the links. Finally, I argue that the propagation of the
relationships expressed by the links reduces dramatically the sample
complexity with respect to traditional learning machines operating on vector
spaces, thus opening the doors to the solution of remarkable large scale
real-world problems involving ranking, classification, and link prediction. |
|
|
|
Marco Gori received the Ph.D.
degree in 1990 from Università di Bologna, |
|
|
|
|
|
Massimo Paolucci (DoCoMo Euro-labs) |
|
|
|
On
bringing AI to the street level |
|
We are living in a world in which digital services are
increasingly provided at the “street level”. Such services which include
information services such as public transport information, payment systems,
and ticketing are becoming one of the media through which we interact with
the environment in which we live. In this trend, mobile phones are the tool
through which we gain access to these services, and through them to operate
in the real world. Artificial intelligence has developed a great deal of
theories on how computers can deal autonomously with the real world out
there. Such theories ranging from planning to learning and knowledge
representation can play a crucial role in the development of mobile
computing. In this talk I will discuss our experience with developing a
mobile platform to deploy on mobile phones that for intelligent service provisioning
and I will try to highlight the emerging challenges for the different areas
of AI. |
|
|
|
Massimo Paolucci is a senior
researcher at DOCOMO Euro-labs where he is conducting research on service
provisioning and composition to mobile users exploiting web services, and
semantic web technology. Before joining DOCOMO he worked on semantic web
services and agent technology at |
|
|
|
|
|
|