Many machine learning algorithms require the summation of Gaussian kernel
functions, an expensive operation if implemented straightforwardly. Several methods
have been proposed t...
Vlad I. Morariu1, Balaji V. Srinivasan, Vikas C. R...
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
Rank correlation measures are known for their resilience to perturbations in numeric values and are widely used in many evaluation metrics. Such ordinal measures have rarely been ...
Jay Yagnik, Dennis Strelow, David Ross, Ruei-sung ...
We present an approach to reconstructing chemical reaction networks from time series measurements of the concentrations of the molecules involved. Our solution strategy combines t...
Multi-class classification algorithms are very widely used, but we argue that they are not always ideal from a theoretical perspective, because they assume all classes are characte...