Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained duri...
Privacy models such as k-anonymity and -diversity typically offer an aggregate or scalar notion of the privacy property that holds collectively on the entire anonymized data set....
With the ubiquity of information networks and their broad applications, the issue of similarity computation between entities of an information network arises and draws extensive r...
Peer production systems rely on users to self-select appropriate tasks and “scratch their personal itch”. However, many such systems require significant maintenance work, whic...
Aniket Kittur, Bryan A. Pendleton, Robert E. Kraut