Object-oriented programs often require large heaps to run properly or meet performance goals. They use high-overhead collections, bulky data models, and large caches. Discovering t...
Abstract— Making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy de...
Training datasets for learning of object categories are often contaminated or imperfect. We explore an approach to automatically identify examples that are noisy or troublesome fo...
Anelia Angelova, Yaser S. Abu-Mostafa, Pietro Pero...
We introduce a novel active-learning scenario in which a user wants to work with a learning algorithm to identify useful anomalies. These are distinguished from the traditional st...
Uknown to us, an axially-symmetric surface is broken into disjoint pieces along a set of break-curves, i.e., the curves along which the surface locally breaks into two pieces. A s...