Jean-Daniel Zucker

AAMAS Conference 2013 Conference Paper

GAMA: Multi-Level and Complex Environment for Agent-Based Models and Simulations

• Alexis Drogoul
• Edouard Amouroux
• Philippe Caillou
• Benoit Gaudou
• Arnaud Grignard
• Nicolas Marilleau
• Patrick Taillandier
• Maroussia Vavasseur

Agent-based models are now used in numerous application domains (ecology, social sciences, etc.) but their use is still impeded by the lack of generic yet ready-to-use tools supporting the design and the simulation of complex models integrating multiple level of agency and realistic environments. The GAMA modeling and simulation platform is proposed to address such issues. It allows modelers to build complex models thanks to high-level modeling language, various agent architectures and advanced environment representations and built-in multi-level support.

ICML Conference 2013 Conference Paper

Rounding Methods for Discrete Linear Classification

• Yann Chevaleyre
• Frédéric Koriche
• Jean-Daniel Zucker

Learning discrete linear functions is a notoriously difficult challenge. In this paper, the learning task is cast as combinatorial optimization problem: given a set of positive and negative feature vectors in the Euclidean space, the goal is to find a discrete linear function that minimizes the cumulative hinge loss of this training set. Since this problem is NP-hard, we propose two simple rounding algorithms that discretize the fractional solution of the problem. Generalization bounds are derived for two important classes of binary-weighted linear functions, by establishing the Rademacher complexity of these classes and proving approximation bounds for rounding methods. These methods are compared on both synthetic and real-world data.

ICML Conference 2000 Conference Paper

Solving the Multiple-Instance Problem: A Lazy Learning Approach

• Jun Wang
• Jean-Daniel Zucker

ICML Conference 1996 Conference Paper

Representation Changes for Efficient Learning in Structural Domains

• Jean-Daniel Zucker
• Jean-Gabriel Ganascia

ICML Conference 1994 Conference Paper

Selective Reformulation of Examples in Concept Learning

• Jean-Daniel Zucker
• Jean-Gabriel Ganascia