Motivated by sensor networks, we consider the fusion storage of correlated sources in a database, such that any subset of them may be efficiently retrieved in the future. Only st...
The typical workload in a database system consists of a mixture of multiple queries of different types, running concurrently and interacting with each other. Hence, optimizing per...
Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
Motivated by the study of algorithmic problems in the domain of information security, in this paper, we study the complexity of a new class of computations over a collection of va...
We present a unifying framework for information theoretic feature selection, bringing almost two decades of research on heuristic filter criteria under a single theoretical inter...
Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luj...