CoLISD 2012 - International Workshop on Collective Learning and Inference on Structured Data

Classical ML techniques assume the data to be iid, but the real world data is inherently relational and can generally be represented using graphs or some variants of them. The importance of modelling structured data is evident from its increasing presence: WWW, social networks, organizational network, image, protein sequence, relational data etc. This field has been recently receiving a lot of attention in the community under different themes depending on the problem addressed and the nature of solution. Variants include iterative classification, structured prediction, relational learning, etc. While there are other issues such as learning the network structure, CoLISD focuses on the within-network learning and inference tasks with special emphasis on collective inference.