Background: Data generated using `omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of...
Yu Guo, Armin Graber, Robert N. McBurney, Raji Bal...
Abstract. In this paper, we give streaming algorithms for some problems which are known to be in deterministic log-space, when the number of passes made on the input is unbounded. ...
HyperNEAT, a generative encoding for evolving artificial neural networks (ANNs), has the unique and powerful ability to exploit the geometry of a problem (e.g., symmetries) by enc...
We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptograph...
The microeconomic framework for data mining [7] assumes that an enterprise chooses a decision maximizing the overall utility over all customers where the contribution of a custome...