SuperDP refutes ε-DP via simultaneous synthesis of input pairs and witness functions using upper expectation supermartingales and lower expectation submartingales, delivering the first fully automated, sound, and semi-complete method applicable to both discrete and continuous stochastic mechanisms.
InProceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation(Phoenix, AZ, USA)(PLDI 2019)
6 Pith papers cite this work. Polarity classification is still indexing.
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PopPy combines an ahead-of-time compiler and runtime to extract parallelism from Python compound AI applications, delivering up to 6.4x end-to-end speedups while preserving sequential semantics.
Generalized ranking supermartingales witness uniqueness of fixed points and thereby enable unified lower-bound verification for termination probability, weakest preexpectation, expected runtime, higher moments, and conditional weakest preexpectation in probabilistic programs.
Typed extended decision diagrams enable scalable deductive verification of probabilistic programs by compactly representing weakest pre-expectations.
Quokka# is a Python library that converts quantum circuit analysis tasks into #SAT problems, offering multiple encodings, approximate equivalence checking, and depth-optimal synthesis.
Modern benchmarks confirm that region-based custom allocators retain locality advantages over state-of-the-art general-purpose allocators, extending the original 2000 conclusions with new applications and fragmentation analysis.
citing papers explorer
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SuperDP: Differential Privacy Refutation via Supermartingales
SuperDP refutes ε-DP via simultaneous synthesis of input pairs and witness functions using upper expectation supermartingales and lower expectation submartingales, delivering the first fully automated, sound, and semi-complete method applicable to both discrete and continuous stochastic mechanisms.
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PopPy: Opportunistically Exploiting Parallelism in Python Compound AI Applications
PopPy combines an ahead-of-time compiler and runtime to extract parallelism from Python compound AI applications, delivering up to 6.4x end-to-end speedups while preserving sequential semantics.
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Scalable Probabilistic Program Verification via Typed Extended Decision Diagrams
Typed extended decision diagrams enable scalable deductive verification of probabilistic programs by compactly representing weakest pre-expectations.
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Quokka#: Quantum Computing with #SAT
Quokka# is a Python library that converts quantum circuit analysis tasks into #SAT problems, offering multiple encodings, approximate equivalence checking, and depth-optimal synthesis.
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Reconsidering "Reconsidering Custom Memory Allocation"
Modern benchmarks confirm that region-based custom allocators retain locality advantages over state-of-the-art general-purpose allocators, extending the original 2000 conclusions with new applications and fragmentation analysis.