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122
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STOC
1991
ACM
84views Algorithms» more  STOC 1991»
15 years 7 months ago
Self-Testing/Correcting for Polynomials and for Approximate Functions
The study of self-testing/correcting programs was introduced in [8] in order to allow one to use program P to compute function f without trusting that P works correctly. A self-te...
Peter Gemmell, Richard J. Lipton, Ronitt Rubinfeld...
135
Voted
AOSD
2009
ACM
15 years 6 months ago
Modular verification of dynamically adaptive systems
Cyber-physical systems increasingly rely on dynamically adaptive programs to respond to changes in their physical environment; examples include ecosystem monitoring and disaster r...
Ji Zhang, Heather Goldsby, Betty H. C. Cheng
135
Voted
JMLR
2006
108views more  JMLR 2006»
15 years 3 months ago
The Interplay of Optimization and Machine Learning Research
The fields of machine learning and mathematical programming are increasingly intertwined. Optimization problems lie at the heart of most machine learning approaches. The Special T...
Kristin P. Bennett, Emilio Parrado-Hernánde...
241
Voted
POPL
2008
ACM
16 years 3 months ago
Generating precise and concise procedure summaries
We present a framework for generating procedure summaries that are precise -- applying the summary in a given context yields the same result as re-analyzing the procedure in that ...
Greta Yorsh, Eran Yahav, Satish Chandra
178
Voted
CP
2005
Springer
15 years 9 months ago
Planning and Scheduling to Minimize Tardiness
We combine mixed integer linear programming (MILP) and constraint programming (CP) to minimize tardiness in planning and scheduling. Tasks are allocated to facilities using MILP an...
John N. Hooker