We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
The literature on algorithmic mechanism design is mostly concerned with game-theoretic versions of optimization problems to which standard economic money-based mechanisms cannot b...
Our proposed methods employ learning and search techniques to estimate outcome features of interest as a function of mechanism parameter settings. We illustrate our approach with ...
Yevgeniy Vorobeychik, Christopher Kiekintveld, Mic...
In this paper we propose an intrinsic developmental algorithm that is designed to allow a mobile robot to incrementally progress through levels of increasingly sophisticated behav...
Douglas S. Blank, Deepak Kumar, Lisa Meeden, James...
We study the role that privacy-preserving algorithms, which prevent the leakage of specific information about participants, can play in the design of mechanisms for strategic age...