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OSDI
2008
ACM
14 years 10 months ago
Finding Similar Failures Using Callstack Similarity
We develop a machine-learned similarity metric for Windows failure reports using telemetry data gathered from clients describing the failures. The key feature is a tuned callstack...
Kevin Bartz, Jack W. Stokes, John C. Platt, Ryan K...
ICDE
2012
IEEE
267views Database» more  ICDE 2012»
12 years 15 days ago
Scalable and Numerically Stable Descriptive Statistics in SystemML
—With the exponential growth in the amount of data that is being generated in recent years, there is a pressing need for applying machine learning algorithms to large data sets. ...
Yuanyuan Tian, Shirish Tatikonda, Berthold Reinwal...
CEC
2005
IEEE
14 years 3 months ago
Effects of experience bias when seeding with prior results
Abstract- Seeding the population of an evolutionary algorithm with solutions from previous runs has proved to be useful when learning control strategies for agents operating in a c...
Mitchell A. Potter, R. Paul Wiegand, H. Joseph Blu...
ECCV
2006
Springer
14 years 12 months ago
Tracking Objects Across Cameras by Incrementally Learning Inter-camera Colour Calibration and Patterns of Activity
This paper presents a scalable solution to the problem of tracking objects across spatially separated, uncalibrated, non-overlapping cameras. Unlike other approaches this technique...
Andrew Gilbert, Richard Bowden
CEC
2005
IEEE
14 years 14 hour ago
Population based incremental learning with guided mutation versus genetic algorithms: iterated prisoners dilemma
Axelrod’s original experiments for evolving IPD player strategies involved the use of a basic GA. In this paper we examine how well a simple GA performs against the more recent P...
Timothy Gosling, Nanlin Jin, Edward P. K. Tsang