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POPL
2008
ACM
14 years 8 months ago
Imperative self-adjusting computation
Self-adjusting computation enables writing programs that can automatically and efficiently respond to changes to their data (e.g., inputs). The idea behind the approach is to stor...
Umut A. Acar, Amal Ahmed, Matthias Blume
ICML
2004
IEEE
14 years 8 months ago
Learning first-order rules from data with multiple parts: applications on mining chemical compound data
Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorl...
Cholwich Nattee, Sukree Sinthupinyo, Masayuki Numa...
ICFP
2004
ACM
14 years 7 months ago
Types, potency, and idempotency: why nonlinearity and amnesia make a type system work
Useful type inference must be faster than normalization. Otherwise, you could check safety conditions by running the program. We analyze the relationship between bounds on normali...
Harry G. Mairson, Peter Møller Neergaard
POPL
2010
ACM
14 years 5 months ago
Generating Compiler Optimizations from Proofs
We present an automated technique for generating compiler optimizations from examples of concrete programs before and after improvements have been made to them. The key technical ...
Ross Tate, Michael Stepp, Sorin Lerner
ASPLOS
2006
ACM
14 years 1 months ago
Type inference for unboxed types and first class mutability
Systems programs rely on fine-grain control of data representation and use of state to achieve performance, conformance to hardware specification, and temporal predictability. T...
Swaroop Sridhar, Jonathan S. Shapiro