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» Input output behavior of supercomputing applications
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ESANN
2007
15 years 2 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
EKAW
2000
Springer
15 years 5 months ago
Torture Tests: A Quantitative Analysis for the Robustness of Knowledge-Based Systems
Abstract. The overall aim of this paper is to provide a general setting for quantitative quality measures of Knowledge-Based System behavior which is widely applicable to many Know...
Perry Groot, Frank van Harmelen, Annette ten Teije
SIGMOD
2010
ACM
259views Database» more  SIGMOD 2010»
15 years 5 months ago
An extensible test framework for the Microsoft StreamInsight query processor
Microsoft StreamInsight (StreamInsight, for brevity) is a platform for developing and deploying streaming applications. StreamInsight adopts a deterministic stream model that leve...
Alex Raizman, Asvin Ananthanarayan, Anton Kirilov,...
ICML
1998
IEEE
16 years 2 months ago
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions
This paper introduces a new algorithm, Q2, foroptimizingthe expected output ofamultiinput noisy continuous function. Q2 is designed to need only a few experiments, it avoids stron...
Andrew W. Moore, Jeff G. Schneider, Justin A. Boya...
EMSOFT
2009
Springer
15 years 8 months ago
Handling mixed-criticality in SoC-based real-time embedded systems
System-on-Chip (SoC) is a promising paradigm to implement safety-critical embedded systems, but it poses significant challenges from a design and verification point of view. In ...
Rodolfo Pellizzoni, Patrick O'Neil Meredith, Min-Y...