Invited Talk - Riccardo Guidotti

Title: Exploiting Auto-Encoders for Explaining Black Box Classifiers

Download Slides

Bio: Riccardo Guidotti was born in 1988 in Pitigliano (GR) Italy. In 2013 and 2010 he graduated cum laude in Computer Science (MS and BS) at University of Pisa. He received the PhD in Computer Science with a thesis on Personal Data Analytics in the same institution. He is currently an Assistant Professor (RTD-A) at the Department of Computer Science University of Pisa, Italy and a member of the Knowledge Discovery and Data Mining Laboratory (KDDLab), a joint research group with the Information Science and Technology Institute of the National Research Council in Pisa. He won the IBM fellowship program and has been an intern in IBM Research Dublin, Ireland in 2015. His research interests are in personal data mining, clustering, explainable models, analysis of transactional data.

Invited Talk - Anna Monreale

Title: Interplay between interpretability and privacy

Download Slides

Bio: Anna Monreale is an associate professor at the Computer Science Department of the University of Pisa and a member of the Knowledge Discovery and Data Mining Laboratory (KDD-Lab), a joint research group with the Information Science and Technology Institute of the National Research Council in Pisa. She has been a visiting student at Department of Computer Science of the Stevens Institute of Technology (Hoboken, NewJersey, USA) (2010). Her research interests include big data analytics, social networks and the privacy issues raising in mining these kinds of social and human sensitive data. In particular, she is interested in the evaluation of privacy risks during analytical processes and in the design of privacy-by-design technologies in the era of big data. She earned her Ph.D. in computer science from the University of Pisa in June 2011 and her dissertation was about privacy-by-design in data mining.

Accepted Papers

• Alain Starke, Martijn Willemsen and Chris Snijders: "Using Explanations as Energy-Saving Frames: A User-Centric Recommender Study"
  


• Mouadh Guesmi, Mohamed Amine Chatti, Laura Vorgerd, Shoeb Joarder, Shadi Zumor, Yiqi Sun, Fangzheng Ji and Arham Muslim: "On-demand Personalized Explanation for Transparent Recommendation"
  


• Noemi Mauro, Zhongli Filippo Hu, Liliana Ardissono and Gianmarco Izzi: "A Service-oriented Perspective on the Summarization of Recommendations: Preliminary Experiment"
  


• Melanie Heck, Paulina Sonntag and Christian Becker: "Is This Really Relevant? A Guide to Best Practice Gaze-based Relevance Prediction Research"
  


• Run Yu, Zach Pardos, Hung Chau and Peter Brusilovsky: "Orienting Students to Course Recommendations Using Three Types of Explanation"