Luc De Raedt
homepage:http://www.cs.kuleuven.be/~lucdr/
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Description

Luc De Raedt is a full professor (of research) at the University of Leuven (KU Leuven) in the Department of Computer Science and a former chair of Machine Learning at the Albert-Ludwigs-University in Freiburg.

Luc De Raedt has been working in the areas of artificial intelligence and computer science, especially on computational logic, machine learning and data mining, probabilistic reasoning and constraint programming and their applications in bio- and chemoinformatics, vision and robotics, natural language processing, and engineering. His work has typically crossed boundaries between different research areas, often working towards an integration of their principles. He is well-known for his early work on inductive logic programming (combining logic with learning). Since 2000, he has been working towards a further integration of logical and relational learning with probabilistic reasoning (statistical relational learning and probabilistic programming) and on inductive querying in databases. During the last three years he has been fascinated by the possibility of combining constraint programming principles with data mining and machine learning. He is currently coordinating a European IST FET project in this area (ICON — Inductive Constraint Programming) and is the program chair of the 20th European Conference on Artificial Intelligence (Montpellier, 2012). He was a program co-chair of ICML 2005 and ECML/PKDD 2001.


Lectures:

keynote
flag Declarative Modeling For Machine Learning and Data Mining
as author at  European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Bristol 2012,
4652 views
  invited talk
flag ProbLog and its Application to Link Mining in Biological Networks
as author at  5th International Workshop on Mining and Learning with Graphs (MLG), Firenze 2007,
5119 views
panel
flag Panel Discussion
as author at  ILP/MLG/SRL collocated International conferences/workshops on learning from relational, graph-based and probabilistic knowledge, Leuven 2009,
together with: Pedro Domingos, Stephen Muggleton, Kristian Kersting, Thomas Gartner, Karsten Michael Borgwardt, C. David Page Jr., Paolo Frasconi,
3937 views
  lecture
flag Parameter Learning in Probabilistic Databases: A Least Squares Approach
as author at  European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Antwerp 2008,
together with: Bernd Gutmann, Angelika Kimmig, Kristian Kersting,
3850 views
keynote
flag From Inductive Querying to Declarative Modeling for Data Mining
as author at  Practical Theories for Exploratory Data Mining (PTDM), Brussels 2012,
2763 views
  lecture
flag Probabilistic and Logical Inference for Network Mining
as author at  Workshops,
3275 views
lecture
flag A Simple Model for Sequences of Relational State Descriptions
as author at  European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Antwerp 2008,
together with: Ingo Thon, Niels Landwehr,
3431 views