We present a new polynomial-space algorithm, called Adopt, for distributed constraint optimization (DCOP). DCOP is able to model a large class of collaboration problems in multi-a...
Pragnesh Jay Modi, Wei-Min Shen, Milind Tambe, Mak...
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
As national infrastructure becomes intertwined with emerging global data networks, the stability and integrity of the two have become synonymous. This connection, while necessary,...
Michael Bailey, Evan Cooke, Farnam Jahanian, Jose ...
The paper studies a distributed implementation method for the BIP (Behavior, Interaction, Priority) component framework for modeling heterogeneous systems. BIP offers two powerful ...
Ananda Basu, Philippe Bidinger, Marius Bozga, Jose...