MLAC 2011 - International Workshop on Machine Learning for Affective Computing (MLAC)

Machine Learning for Affective Computing (MLAC)

Affective computing (AC) is a unique discipline which attempts to model affect using one or multiple modalities by drawing on techniques from many different fields. AC often deals with problems that are known to be very complex and multi-dimensional, involving different kinds of data (numeric, symbolic, visual etc.). However, with the advancement of machine learning techniques, a lot of those problems are now becoming more tractable.

The purpose of this workshop is to engage the machine learning and affective computing communities towards solving the most pressing problems relating to understanding and modeling affect. We welcome the participation of researchers from diverse fields, including signal processing and pattern recognition, statistical machine learning, human-computer interaction, human-robot interaction, robotics, conversational agents, experimental psychology, and decision making.

Website: http://mlac.media.mit.edu/

Organizers:
M. Ehsan Hoque, MIT, USA
Dan McDuff, MIT, USA
Louis Philippe Morency, USC, USA
Rosalind Picard, MIT, USA