Sciweavers

1020 search results - page 49 / 204
» Learning to Use Operational Advice
Sort
View
99
Voted
OSDI
2008
ACM
16 years 3 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...
167
Voted
ICDE
2012
IEEE
267views Database» more  ICDE 2012»
13 years 5 months 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...
97
Voted
CEC
2005
IEEE
15 years 8 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...
122
Voted
ECCV
2006
Springer
16 years 4 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
100
Voted
CEC
2005
IEEE
15 years 4 months 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