Building useful classification models can be a challenging endeavor, especially when training data is imbalanced. Class imbalance presents a problem when traditional classificatio...
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van H...
In nature, one finds large collections of different protein sequences exhibiting roughly the same three-dimensional structure, and this observation underpins the study of structur...
Leonid Meyerguz, David Kempe, Jon M. Kleinberg, Ro...
Devising an efficient deterministic – or even a nondeterministic sub-exponential time – algorithm for testing polynomial identities is a fundamental problem in algebraic comp...
In transfer learning the aim is to solve new learning tasks using fewer examples by using information gained from solving related tasks. Existing transfer learning methods have be...
We investigate deterministically simulating (i.e., solving the membership problem for) nondeterministic finite automata (NFA), relying solely on the NFA’s resources (states and ...