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» Using Machine Learning to Support Debugging with Tarantula
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158
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CIVR
2005
Springer
123views Image Analysis» more  CIVR 2005»
15 years 8 months ago
Region-Based Image Clustering and Retrieval Using Multiple Instance Learning
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
Chengcui Zhang, Xin Chen
146
Voted
ASWEC
2009
IEEE
15 years 16 days ago
From Requirements to Embedded Software - Formalising the Key Steps
Failure of a design to satisfy a system's requirements can result in schedule and cost overruns. When using current approaches, ensuring requirements are satisfied is often d...
Toby Myers, R. Geoff Dromey
106
Voted
CHI
2007
ACM
16 years 3 months ago
Toolkit support for developing and deploying sensor-based statistical models of human situations
Sensor-based statistical models promise to support a variety of advances in human-computer interaction, but building applications that use them is currently difficult and potentia...
James Fogarty, Scott E. Hudson
124
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ENTCS
2007
113views more  ENTCS 2007»
15 years 2 months ago
The Interactive Curry Observation Debugger iCODE
Debugging by observing the evaluation of expressions and functions is a useful approach for finding bugs in lazy functional and functional logic programs. However, adding and rem...
Parissa H. Sadeghi, Frank Huch
120
Voted
ML
2006
ACM
15 years 8 months ago
Seminal: searching for ML type-error messages
We present a new way to generate type-error messages in a polymorphic, implicitly, and strongly typed language (specifically Caml). Our method separates error-message generation ...
Benjamin S. Lerner, Dan Grossman, Craig Chambers