Marco Gori – författare

Web Dragons offers a perspective on the world of Web search and the effects of search engines and information availability on the present and future world.In the blink of an eye since the turn of the millennium, the lives of people who work with information have been utterly transformed. Everything we need to know is on the web. It's where we learn and play, shop and do business, keep up with old friends and meet new ones. Search engines make it possible for us to find the stuff we need to know. Search engines — web dragons — are the portals through which we access society's treasure trove of information. How do they stack up against librarians, the gatekeepers over centuries past? What role will libraries play in a world whose information is ruled by the web? How is the web organized? Who controls its contents, and how do they do it? How do search engines work? How can web visibility be exploited by those who want to sell us their wares? What's coming tomorrow, and can we influence it?As we witness the dawn of a new era, this book shows readers what it will look like and how it will change their world. Whoever you are: if you care about information, this book will open your eyes and make you blink.

Machine Learning: A Constraint-Based Approach, Second Edition provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that include neural networks and kernel machines. The book presents the information in a truly unified manner that is based on the notion of learning from environmental constraints. It draws a path towards deep integration with machine learning that relies on the idea of adopting multivalued logic formalisms, such as in fuzzy systems. Special attention is given to deep learning, which nicely fits the constrained-based approach followed in this book.The book presents a simpler unified notion of regularization, which is strictly connected with the parsimony principle, including many solved exercises that are classified according to the Donald Knuth ranking of difficulty, which essentially consists of a mix of warm-up exercises that lead to deeper research problems. A software simulator is also included. Presents, in a unified manner, fundamental machine learning concepts, such as neural networks and kernel machines Provides in-depth coverage of unsupervised and semi-supervised learning, with new content in hot growth areas such as deep learning Includes a software simulator for kernel machines and learning from constraints that also covers exercises to facilitate learning Contains hundreds of solved examples and exercises chosen particularly for their progression of difficulty from simple to complex Supported by a free, downloadable companion book designed to facilitate students' acquisition of experimental skills

The remarkable progress in computer vision over the last few years is, by and large, attributed to deep learning, fueled by the availability of huge sets of labeled data, and paired with the explosive growth of the GPU paradigm. While subscribing to this view, this work criticizes the supposed scientific progress in the field, and proposes the investigation of vision within the framework of information-based laws of nature.This work poses fundamental questions about vision that remain far from understood, leading the reader on a journey populated by novel challenges resonating with the foundations of machine learning. The central thesis proposed is that for a deeper understanding of visual computational processes, it is necessary to look beyond the applications of general purpose machine learning algorithms, and focus instead on appropriate learning theories that take into account the spatiotemporal nature of the visual signal.Serving to inspire and stimulate critical reflection and discussion, yet requiring no prior advanced technical knowledge, the text can naturally be paired with classic textbooks on computer vision to better frame the current state of the art, open problems, and novel potential solutions. As such, it will be of great benefit to graduate and advanced undergraduate students in computer science, computational neuroscience, physics, and other related disciplines.

This book constitutes the refereed proceedings of the 15th International Conference of the Italian Association for Artificial Intelligence, AI*IA 2016, held in Genova, Italy, in November/December 2016. The 39 full papers presented were carefully reviewed and selected from 53 submissions.

This book presents the refereed proceedings of the 4th Congress of the Italian Association for Artificial Intelligence, AI*IA '95, held in Florence, Italy, in October 1995.The 31 revised full papers and the 12 short presentations contained in the volume were selected from a total of 101 submissions on the basis of a careful reviewing process. The papers are organized in sections on natural language processing, fuzzy systems, machine learning, knowledge representation, automated reasoning, cognitive models, robotics and planning, connectionist models, model-based reasoning, and distributed artificial intelligence.