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...
Grid search and manual search are the most widely used strategies for hyper-parameter optimization. This paper shows empirically and theoretically that randomly chosen trials are ...
We consider a model for which it is important, early in processing, to estimate some variables with high precision, but perhaps at relatively low recall. If some variables can be ...
Gary B. Huang, Andrew Kae, Carl Doersch, Erik G. L...
We consider the task of estimating, from observed data, a probabilistic model that is parameterized by a finite number of parameters. In particular, we are considering the situat...
In object-oriented systems, runtime memory is composed of an object graph in which objects refer to other objects. This graph of objects evolves while the system is running. Graph...