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PLDI
2003
ACM
15 years 11 months ago
A compiler framework for speculative analysis and optimizations
Speculative execution, such as control speculation and data speculation, is an effective way to improve program performance. Using edge/path profile information or simple heuristi...
Jin Lin, Tong Chen, Wei-Chung Hsu, Pen-Chung Yew, ...
SAS
1994
Springer
159views Formal Methods» more  SAS 1994»
15 years 10 months ago
Iterative Fixed Point Computation for Type-Based Strictness Analysis
Amtoft has formulated an "on-line" constraint normalization method for solving a strictness inference problem inspired by Wright. From the syntactic form of the normaliz...
Fritz Henglein
STOC
1991
ACM
84views Algorithms» more  STOC 1991»
15 years 10 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...
AOSD
2009
ACM
15 years 9 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
JMLR
2006
108views more  JMLR 2006»
15 years 6 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...