Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
Programming specialized network processors (NPU) is inherently difficult. Unlike mainstream processors where architectural features such as out-of-order execution and caches hide ...
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...
The goal of the Parfait project is to find bugs in C source code in a scalable and precise way. To this end, Parfait was designed as a framework with layers of sound program anal...
Cristina Cifuentes, Nathan Keynes, Lian Li, Bernha...