Quality assurance (QA) tasks, such as testing, profiling, and performance evaluation, have historically been done in-house on developer-generated workloads and regression suites. ...
Arvind S. Krishna, Douglas C. Schmidt, Atif M. Mem...
Effective learning in multi-label classification (MLC) requires an ate level of abstraction for representing the relationship between each instance and multiple categories. Curren...
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
In this paper we introduce a novel architecture for data processing, based on a functional fusion between a data and a computation layer. We show how such an architecture can be le...
Radu Sion, Ramesh Natarajan, Inderpal Narang, Wen-...