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A consistent semantics of self-adjusting computation

UMUT A. ACAR, MATTHIAS BLUME, JACOB DONHAM
2013 Journal of functional programming  
This paper presents a semantics of self-adjusting computation and proves that the semantics is correct and consistent.  ...  During evaluation, reuse of a computation via memoization triggers a change propagation that adjusts the reused computation to reflect the mutated memory.  ...  By automating the process of adjusting to any data change, self-adjusting computation generalizes incremental computation (e.g., [10, 18, 19, 12, 11, 17] ).  ... 
doi:10.1017/s0956796813000099 fatcat:idxbpn6ejrfx5mr3g6t5sxa2ta

A Consistent Semantics of Self-Adjusting Computation [article]

Umut A. Acar and Matthias Blume and Jacob Donham
2011 arXiv   pre-print
This paper presents a semantics of self-adjusting computation and proves that the semantics are correct and consistent.  ...  During evaluation, reuse of a computation via memoization triggers a change propagation that adjusts the reused computation to reflect the mutated memory.  ...  The presented semantics forms the foundation for nearly all the followup work on self-adjusting computation.  ... 
arXiv:1106.0478v1 fatcat:wppuyv4abbferf2hza26obcg3u

A Consistent Semantics of Self-adjusting Computation [chapter]

Umut A. Acar, Matthias Blume, Jacob Donham
2007 Lecture Notes in Computer Science  
This paper presents a semantics of self-adjusting computation and proves that the semantics is correct and consistent.  ...  During evaluation, reuse of a computation via memoization triggers a change propagation that adjusts the reused computation to reflect the mutated memory.  ...  By automating the process of adjusting to any data change, self-adjusting computation generalizes incremental computation (e.g., [10, 18, 19, 12, 11, 17] ).  ... 
doi:10.1007/978-3-540-71316-6_31 fatcat:i42tspqferecfguxwyagvmpb64

A consistent semantics of self-adjusting computation

Umut A. Acar, Matthias Blume, Jacob Donham
2018
This paper presents a semantics of self-adjusting computation and proves that the semantics is correct and consistent.  ...  of the computation.  ...  Consistent Semantics of Self-Adjusting Computation 29 5.1.6 Proof of Lemma 9 (changeable hit-elimination) • write: We have e = write(v) and T 0 = T = write v.  ... 
doi:10.1184/r1/6587312 fatcat:g33n35jzhnb47jby6q75j7svjy

Self-adjusting stack machines

Matthew A. Hammer, Georg Neis, Yan Chen, Umut A. Acar
2011 Proceedings of the 2011 ACM international conference on Object oriented programming systems languages and applications - OOPSLA '11  
Self-adjusting computation is a language-based technique to derive dynamic programs from static programs. Summary of contributions: A self-adjusting semantics for low-level programs.  ...  This semantics defines self-adjusting stack machines. A compiler and run-time that implement the semantics. A front end that embeds much of C.  ...  Our Contributions A consistent self-adjusting semantics for low-level programs Our abstract machine semantics Describes trace editing & memory management implementation of run-time system But requires  ... 
doi:10.1145/2048066.2048124 dblp:conf/oopsla/HammerNCA11 fatcat:2bpr6pwunrd5nmfw5cwlxeoyku

Self-adjusting stack machines

Matthew A. Hammer, Georg Neis, Yan Chen, Umut A. Acar
2011 SIGPLAN notices  
Self-adjusting computation is a language-based technique to derive dynamic programs from static programs. Summary of contributions: A self-adjusting semantics for low-level programs.  ...  This semantics defines self-adjusting stack machines. A compiler and run-time that implement the semantics. A front end that embeds much of C.  ...  Our Contributions A consistent self-adjusting semantics for low-level programs Our abstract machine semantics Describes trace editing & memory management implementation of run-time system But requires  ... 
doi:10.1145/2076021.2048124 fatcat:ksnj4mr6aza2lhvmmx7qlykzcy

A proposal for parallel self-adjusting computation

Matthew Hammer, Umut A. Acar, Mohan Rajagopalan, Anwar Ghuloum
2007 Proceedings of the 2007 workshop on Declarative aspects of multicore architectures - DAMP '07  
We present an overview of our ongoing work on parallelizing self-adjusting-computation techniques.  ...  In self-adjusting computation, programs can respond to changes to their data (e.g., inputs, outcomes of comparisons) automatically by running a change-propagation algorithm.  ...  A key challenge for parallelizing self-adjusting computations is the fact that existing techniques have been crafted assuming sequential execution semantics.  ... 
doi:10.1145/1248648.1248651 dblp:conf/popl/HammerARG07 fatcat:sqaypue2wnatvkd642gmiq7eja

The Potential Of Non-Semantic Features For Uav'S Remote Sensing Data Fusion

Eduard Angelats, Eulàlia Parès, Ismael Colomina
2016 Zenodo  
These payloads can consist, for example, of several cameras sensing different spectral bands and/or lightweight, low cost laser scanners.  ...  The use of fused data from these sensors can boost the use of UAVs for environmental mapping purposes such as landslide volumetric estimation, biomass estimation or forestry management, to mention a few  ...  This last step is also based in a least squares adjustment and is a complex process with a high computational burden.  ... 
doi:10.5281/zenodo.827198 fatcat:fnylquzjfbffjof2dpsknwp6t4

Page 4498 of Mathematical Reviews Vol. , Issue 97G [page]

1997 Mathematical Reviews  
Our analysis proves that a self-adjusting linear list algorithm, MP, is competitive to a large class of offline adver- saries, where the operations are successful searches, unsuccessful searches, and insertions  ...  Algorithms 15 (1993), no. 3, 447-481], we designed and analyzed efficient self-adjusting linear list algorithms.  ... 

Imperative self-adjusting computation

Umut A. Acar, Amal Ahmed, Matthias Blume
2008 Proceedings of the 35th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages - POPL '08  
All previous work on self-adjusting computation, however, relied on a purely functional programming model.  ...  Recent work on self-adjusting computation showed how to systematically write programs that respond efficiently to incremental changes in their inputs.  ...  Conclusions Self-adjusting computation has been a success story so far.  ... 
doi:10.1145/1328438.1328476 dblp:conf/popl/AcarAB08 fatcat:c75hhva3cvdp3d5yp6xx3guxti

Imperative self-adjusting computation

Umut A. Acar, Amal Ahmed, Matthias Blume
2008 SIGPLAN notices  
All previous work on self-adjusting computation, however, relied on a purely functional programming model.  ...  Recent work on self-adjusting computation showed how to systematically write programs that respond efficiently to incremental changes in their inputs.  ...  Conclusions Self-adjusting computation has been a success story so far.  ... 
doi:10.1145/1328897.1328476 fatcat:af627tpl3vhmrhapxexzflorha

Non-monotonic Self-Adjusting Computation [chapter]

Ruy Ley-Wild, Umut A. Acar, Guy Blelloch
2012 Lecture Notes in Computer Science  
Self-adjusting computation is a language-based approach to writing programs that respond dynamically to input changes by maintaining a trace of the computation consistent with the input, thus also updating  ...  We show that the translation asymptotically preserves the semantics and trace distance, that the cost of update coincides with trace distance, and that updating produces the same answer as a from-scratch  ...  Self-adjusting programs construct and maintain a trace that records data and control dependencies of the computation.  ... 
doi:10.1007/978-3-642-28869-2_24 fatcat:payxcagbwrez7mmcqwkrmc4db4

SIGN: Spatial-information Incorporated Generative Network for Generalized Zero-shot Semantic Segmentation [article]

Jiaxin Cheng, Soumyaroop Nandi, Prem Natarajan, Wael Abd-Almageed
2021 arXiv   pre-print
Unlike conventional zero-shot classification, zero-shot semantic segmentation predicts a class label at the pixel level instead of the image level.  ...  Furthermore, while self-training is widely used in zero-shot semantic segmentation to generate pseudo-labels, we propose a new knowledge-distillation-inspired self-training strategy, namely Annealed Self-Training  ...  The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, eigher expressed or implied, of Air  ... 
arXiv:2108.12517v1 fatcat:ui7no7xnxvhuxfzdrv7l7iq2w4

Preserved Self-Evaluation in Amnesia Supports Access to the Self through Introspective Computation

Aurelija Juskenaite, Peggy Quinette, Mickaël Laisney, Marie-Loup Eustache, Béatrice Desgranges, Fausto Viader, Francis Eustache
2016 Frontiers in Human Neuroscience  
In this review article, we discuss prevailing explanations for preserved self-evaluation in amnesia and propose an alternative one, based on the concept of introspective computation.  ...  We also consider molecular and anatomical aspects of brain functioning that potentially support introspective computation.  ...  We suggest that introspective computation, which does not rely on personal information stored in semantic or episodic memory, is a cognitive strategy that consists in simulating one's behavioral tendencies  ... 
doi:10.3389/fnhum.2016.00462 pmid:27695407 pmcid:PMC5025446 fatcat:svbqk5onxzfkxi7jzb6fa2b6li

CEAL

Matthew A. Hammer, Umut A. Acar, Yan Chen
2009 Proceedings of the 2009 ACM SIGPLAN conference on Programming language design and implementation - PLDI '09  
We describe the design and implementation of CEAL: a C-based language for self-adjusting computation.  ...  The language is fully general and extends C with a small number of primitives to enable writing self-adjusting programs in a style similar to conventional C programs.  ...  Reflecting the structure of self-adjusting programs, CEAL consists of a meta language for writing mutators and a core language for writing core programs.  ... 
doi:10.1145/1542476.1542480 dblp:conf/pldi/HammerAC09 fatcat:pygxm2kolbhvfiyinptlqzjsca
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