tr t p rt t
play

tr t Prt - PowerPoint PPT Presentation

Jul 13, 2023 •249 likes •873 views

tr t Prt t ss r P

  1. ❈♦♥tr♦❧✲❋❧♦✇ ❘❡✜♥❡♠❡♥t ✈✐❛ P❛rt✐❛❧ ❊✈❛❧✉❛t✐♦♥ ❏❡sús ❏✳ ❉♦♠é♥❡❝❤ ✶ ❙❛♠✐r ●❡♥❛✐♠ ✶ ❛♥❞ ❏♦❤♥ P✳ ●❛❧❧❛❣❤❡r ✷ ✶ ❈♦♠♣❧✉t❡♥s❡ ❯♥✐✈❡rs✐t② ♦❢ ▼❛❞r✐❞ ✭❙♣❛✐♥✮ ✷ ❘♦s❦✐❧❞❡ ❯♥✐✈❡rs✐t② ✭❉❡♥♠❛r❦✮ ✷ ■▼❉❊❆ ❙♦❢t✇❛r❡ ■♥st✐t✉t❡ ✭❙♣❛✐♥✮ ■♥t❡r♥❛t✐♦♥❛❧ ❲♦r❦s❤♦♣ ♦♥ ❚❡r♠✐♥❛t✐♦♥ ❖①❢♦r❞✳ ❏✉❧②✱ ✷✵✶✽ ❏❡sús ❏✳ ❉♦♠é♥❡❝❤✱ ❯❈▼ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡✜♥❡♠❡♥t ✈✐❛ P❛rt✐❛❧ ❊✈❛❧✉❛t✐♦♥ ❲❙❚✬✶✽ ✶✴✶✸

  2. ❈♦♥tr♦❧✲❋❧♦✇ ❘❡❢✐♥❡♠❡♥t ✈✐❛ P❛rt✐❛❧ ❊✈❛❧✉❛t✐♦♥ ✶✳ ❈♦♥tr♦❧✲✢♦✇ ❘❡✜♥❡♠❡♥t ✷✳ P❛rt✐❛❧ ❊✈❛❧✉❛t✐♦♥ ✸✳ ❊①❛♠♣❧❡s ✹✳ ❊①♣❡r✐♠❡♥ts ✺✳ ❈♦♥❝❧✉s✐♦♥s ❛♥❞ ❢✉t✉r❡ ✇♦r❦ ❏❡sús ❏✳ ❉♦♠é♥❡❝❤✱ ❯❈▼ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡✜♥❡♠❡♥t ✈✐❛ P❛rt✐❛❧ ❊✈❛❧✉❛t✐♦♥ ❲❙❚✬✶✽ ✷✴✶✸

  3. ✵ ✴✴ ✐ ♥ t ① ✱ ② ✱ ③ ❀ ✶ ✇❤✐❧❡ ✭ ① ❃ ✵ ✫✫ ② ❁ ③ ✮ ②✰✰❀ ✷ ✸ ✹ ✇❤✐❧❡ ✭ ① ❃ ✵ ✫✫ ② ❃❂ ③ ✮ ① ❀ ✺ ❚✇♦ ❤✐❞❞❡♥ st❛❣❡s✳ ❚✇♦ ❡①♣❧✐❝✐t st❛❣❡s✳ ◆♦ ▲✐♥❡❛r ❘❛♥❦✐♥❣ ❋✉♥❝t✐♦♥✳ ▲✐♥❡❛r ❘❛♥❦✐♥❣ ❋✉♥❝t✐♦♥✳ ❯♥❦♥♦✇♥ ❝♦♠♣❧❡①✐t②✳ ▲✐♥❡❛r ❝♦♠♣❧❡①✐t②✳ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡❢✐♥❡♠❡♥t ✵ ✴✴ ✐ ♥ t ① ✱ ② ✱ ③ ❀ ✶ ✇❤✐❧❡ ✭ ① ❃ ✵✮ ✐ ❢ ✭ ② ❁ ③ ✮ ✷ ②✰✰❀ ✸ ❡ ❧ s ❡ ✹ ① −− ❀ ✺ ❏❡sús ❏✳ ❉♦♠é♥❡❝❤✱ ❯❈▼ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡✜♥❡♠❡♥t ✈✐❛ P❛rt✐❛❧ ❊✈❛❧✉❛t✐♦♥ ❲❙❚✬✶✽ ✸✴✶✸

  4. ✵ ✴✴ ✐ ♥ t ① ✱ ② ✱ ③ ❀ ✶ ✇❤✐❧❡ ✭ ① ❃ ✵ ✫✫ ② ❁ ③ ✮ ②✰✰❀ ✷ ✸ ✹ ✇❤✐❧❡ ✭ ① ❃ ✵ ✫✫ ② ❃❂ ③ ✮ ① ❀ ✺ ❚✇♦ ❡①♣❧✐❝✐t st❛❣❡s✳ ◆♦ ▲✐♥❡❛r ❘❛♥❦✐♥❣ ❋✉♥❝t✐♦♥✳ ▲✐♥❡❛r ❘❛♥❦✐♥❣ ❋✉♥❝t✐♦♥✳ ❯♥❦♥♦✇♥ ❝♦♠♣❧❡①✐t②✳ ▲✐♥❡❛r ❝♦♠♣❧❡①✐t②✳ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡❢✐♥❡♠❡♥t ✵ ✴✴ ✐ ♥ t ① ✱ ② ✱ ③ ❀ ✶ ✇❤✐❧❡ ✭ ① ❃ ✵✮ ✐ ❢ ✭ ② ❁ ③ ✮ ✷ ②✰✰❀ ✸ ❡ ❧ s ❡ ✹ ① −− ❀ ✺ ❚✇♦ ❤✐❞❞❡♥ st❛❣❡s✳ ❏❡sús ❏✳ ❉♦♠é♥❡❝❤✱ ❯❈▼ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡✜♥❡♠❡♥t ✈✐❛ P❛rt✐❛❧ ❊✈❛❧✉❛t✐♦♥ ❲❙❚✬✶✽ ✸✴✶✸

  5. ✵ ✴✴ ✐ ♥ t ① ✱ ② ✱ ③ ❀ ✶ ✇❤✐❧❡ ✭ ① ❃ ✵ ✫✫ ② ❁ ③ ✮ ②✰✰❀ ✷ ✸ ✹ ✇❤✐❧❡ ✭ ① ❃ ✵ ✫✫ ② ❃❂ ③ ✮ ① ❀ ✺ ❚✇♦ ❡①♣❧✐❝✐t st❛❣❡s✳ ▲✐♥❡❛r ❘❛♥❦✐♥❣ ❋✉♥❝t✐♦♥✳ ❯♥❦♥♦✇♥ ❝♦♠♣❧❡①✐t②✳ ▲✐♥❡❛r ❝♦♠♣❧❡①✐t②✳ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡❢✐♥❡♠❡♥t ✵ ✴✴ ✐ ♥ t ① ✱ ② ✱ ③ ❀ ✶ ✇❤✐❧❡ ✭ ① ❃ ✵✮ ✐ ❢ ✭ ② ❁ ③ ✮ ✷ ②✰✰❀ ✸ ❡ ❧ s ❡ ✹ ① −− ❀ ✺ ❚✇♦ ❤✐❞❞❡♥ st❛❣❡s✳ ◆♦ ▲✐♥❡❛r ❘❛♥❦✐♥❣ ❋✉♥❝t✐♦♥✳ ❏❡sús ❏✳ ❉♦♠é♥❡❝❤✱ ❯❈▼ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡✜♥❡♠❡♥t ✈✐❛ P❛rt✐❛❧ ❊✈❛❧✉❛t✐♦♥ ❲❙❚✬✶✽ ✸✴✶✸

  6. ✵ ✴✴ ✐ ♥ t ① ✱ ② ✱ ③ ❀ ✶ ✇❤✐❧❡ ✭ ① ❃ ✵ ✫✫ ② ❁ ③ ✮ ②✰✰❀ ✷ ✸ ✹ ✇❤✐❧❡ ✭ ① ❃ ✵ ✫✫ ② ❃❂ ③ ✮ ① ❀ ✺ ❚✇♦ ❡①♣❧✐❝✐t st❛❣❡s✳ ▲✐♥❡❛r ❘❛♥❦✐♥❣ ❋✉♥❝t✐♦♥✳ ▲✐♥❡❛r ❝♦♠♣❧❡①✐t②✳ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡❢✐♥❡♠❡♥t ✵ ✴✴ ✐ ♥ t ① ✱ ② ✱ ③ ❀ ✶ ✇❤✐❧❡ ✭ ① ❃ ✵✮ ✐ ❢ ✭ ② ❁ ③ ✮ ✷ ②✰✰❀ ✸ ❡ ❧ s ❡ ✹ ① −− ❀ ✺ ❚✇♦ ❤✐❞❞❡♥ st❛❣❡s✳ ◆♦ ▲✐♥❡❛r ❘❛♥❦✐♥❣ ❋✉♥❝t✐♦♥✳ ❯♥❦♥♦✇♥ ❝♦♠♣❧❡①✐t②✳ ❏❡sús ❏✳ ❉♦♠é♥❡❝❤✱ ❯❈▼ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡✜♥❡♠❡♥t ✈✐❛ P❛rt✐❛❧ ❊✈❛❧✉❛t✐♦♥ ❲❙❚✬✶✽ ✸✴✶✸

  7. ❚✇♦ ❡①♣❧✐❝✐t st❛❣❡s✳ ▲✐♥❡❛r ❘❛♥❦✐♥❣ ❋✉♥❝t✐♦♥✳ ▲✐♥❡❛r ❝♦♠♣❧❡①✐t②✳ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡❢✐♥❡♠❡♥t ✵ ✴✴ ✐ ♥ t ① ✱ ② ✱ ③ ❀ ✵ ✴✴ ✐ ♥ t ① ✱ ② ✱ ③ ❀ ✶ ✇❤✐❧❡ ✭ ① ❃ ✵✮ ✶ ✇❤✐❧❡ ✭ ① ❃ ✵ ✫✫ ② ❁ ③ ✮ ✐ ❢ ✭ ② ❁ ③ ✮ ②✰✰❀ ✷ ✷ ②✰✰❀ ✸ ✸ ❡ ❧ s ❡ ✹ ✇❤✐❧❡ ✭ ① ❃ ✵ ✫✫ ② ❃❂ ③ ✮ ✹ ① −− ❀ ① −− ❀ ✺ ✺ ❚✇♦ ❤✐❞❞❡♥ st❛❣❡s✳ ◆♦ ▲✐♥❡❛r ❘❛♥❦✐♥❣ ❋✉♥❝t✐♦♥✳ ❯♥❦♥♦✇♥ ❝♦♠♣❧❡①✐t②✳ ❏❡sús ❏✳ ❉♦♠é♥❡❝❤✱ ❯❈▼ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡✜♥❡♠❡♥t ✈✐❛ P❛rt✐❛❧ ❊✈❛❧✉❛t✐♦♥ ❲❙❚✬✶✽ ✸✴✶✸

  8. ▲✐♥❡❛r ❘❛♥❦✐♥❣ ❋✉♥❝t✐♦♥✳ ▲✐♥❡❛r ❝♦♠♣❧❡①✐t②✳ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡❢✐♥❡♠❡♥t ✵ ✴✴ ✐ ♥ t ① ✱ ② ✱ ③ ❀ ✵ ✴✴ ✐ ♥ t ① ✱ ② ✱ ③ ❀ ✶ ✇❤✐❧❡ ✭ ① ❃ ✵✮ ✶ ✇❤✐❧❡ ✭ ① ❃ ✵ ✫✫ ② ❁ ③ ✮ ✐ ❢ ✭ ② ❁ ③ ✮ ②✰✰❀ ✷ ✷ ②✰✰❀ ✸ ✸ ❡ ❧ s ❡ ✹ ✇❤✐❧❡ ✭ ① ❃ ✵ ✫✫ ② ❃❂ ③ ✮ ✹ ① −− ❀ ① −− ❀ ✺ ✺ ❚✇♦ ❤✐❞❞❡♥ st❛❣❡s✳ ❚✇♦ ❡①♣❧✐❝✐t st❛❣❡s✳ ◆♦ ▲✐♥❡❛r ❘❛♥❦✐♥❣ ❋✉♥❝t✐♦♥✳ ❯♥❦♥♦✇♥ ❝♦♠♣❧❡①✐t②✳ ❏❡sús ❏✳ ❉♦♠é♥❡❝❤✱ ❯❈▼ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡✜♥❡♠❡♥t ✈✐❛ P❛rt✐❛❧ ❊✈❛❧✉❛t✐♦♥ ❲❙❚✬✶✽ ✸✴✶✸

  9. ▲✐♥❡❛r ❝♦♠♣❧❡①✐t②✳ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡❢✐♥❡♠❡♥t ✵ ✴✴ ✐ ♥ t ① ✱ ② ✱ ③ ❀ ✵ ✴✴ ✐ ♥ t ① ✱ ② ✱ ③ ❀ ✶ ✇❤✐❧❡ ✭ ① ❃ ✵✮ ✶ ✇❤✐❧❡ ✭ ① ❃ ✵ ✫✫ ② ❁ ③ ✮ ✐ ❢ ✭ ② ❁ ③ ✮ ②✰✰❀ ✷ ✷ ②✰✰❀ ✸ ✸ ❡ ❧ s ❡ ✹ ✇❤✐❧❡ ✭ ① ❃ ✵ ✫✫ ② ❃❂ ③ ✮ ✹ ① −− ❀ ① −− ❀ ✺ ✺ ❚✇♦ ❤✐❞❞❡♥ st❛❣❡s✳ ❚✇♦ ❡①♣❧✐❝✐t st❛❣❡s✳ ◆♦ ▲✐♥❡❛r ❘❛♥❦✐♥❣ ❋✉♥❝t✐♦♥✳ ▲✐♥❡❛r ❘❛♥❦✐♥❣ ❋✉♥❝t✐♦♥✳ ❯♥❦♥♦✇♥ ❝♦♠♣❧❡①✐t②✳ ❏❡sús ❏✳ ❉♦♠é♥❡❝❤✱ ❯❈▼ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡✜♥❡♠❡♥t ✈✐❛ P❛rt✐❛❧ ❊✈❛❧✉❛t✐♦♥ ❲❙❚✬✶✽ ✸✴✶✸

  10. ❈♦♥tr♦❧✲❋❧♦✇ ❘❡❢✐♥❡♠❡♥t ✵ ✴✴ ✐ ♥ t ① ✱ ② ✱ ③ ❀ ✵ ✴✴ ✐ ♥ t ① ✱ ② ✱ ③ ❀ ✶ ✇❤✐❧❡ ✭ ① ❃ ✵✮ ✶ ✇❤✐❧❡ ✭ ① ❃ ✵ ✫✫ ② ❁ ③ ✮ ✐ ❢ ✭ ② ❁ ③ ✮ ②✰✰❀ ✷ ✷ ②✰✰❀ ✸ ✸ ❡ ❧ s ❡ ✹ ✇❤✐❧❡ ✭ ① ❃ ✵ ✫✫ ② ❃❂ ③ ✮ ✹ ① −− ❀ ① −− ❀ ✺ ✺ ❚✇♦ ❤✐❞❞❡♥ st❛❣❡s✳ ❚✇♦ ❡①♣❧✐❝✐t st❛❣❡s✳ ◆♦ ▲✐♥❡❛r ❘❛♥❦✐♥❣ ❋✉♥❝t✐♦♥✳ ▲✐♥❡❛r ❘❛♥❦✐♥❣ ❋✉♥❝t✐♦♥✳ ❯♥❦♥♦✇♥ ❝♦♠♣❧❡①✐t②✳ ▲✐♥❡❛r ❝♦♠♣❧❡①✐t②✳ ❏❡sús ❏✳ ❉♦♠é♥❡❝❤✱ ❯❈▼ ❈♦♥tr♦❧✲❋❧♦✇ ❘❡✜♥❡♠❡♥t ✈✐❛ P❛rt✐❛❧ ❊✈❛❧✉❛t✐♦♥ ❲❙❚✬✶✽ ✸✴✶✸

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

Generic Programming, Partial Evaluation, and a New Programming Paradigm Dr. Christopher Landauer

Generic Programming, Partial Evaluation, and a New Programming Paradigm Dr. Christopher Landauer

vg-gppe.txt Sun Jan 3 20:59:22 1999 1 Generic Programming, Partial Evaluation, and a New Programming Paradigm Dr. Christopher Landauer Aerospace Integration Science Center The Aerospace Corporation cal@aero.org Dr. Kirstie L.

515 views • 22 slides
CS 525: Advanced Database convert answer Organisation logical query plan execute apply laws

CS 525: Advanced Database convert answer Organisation logical query plan execute apply laws

SQL query parse parse tree CS 525: Advanced Database convert answer Organisation logical query plan execute apply laws 08: Query Processing statistics Pi improved l.q.p Parsing and Analysis pick best estimate result sizes

323 views • 18 slides
Programming Abstractions Week 7-2: MiniScheme A and B Stephen Checkoway Structure of MiniScheme

Programming Abstractions Week 7-2: MiniScheme A and B Stephen Checkoway Structure of MiniScheme

Programming Abstractions Week 7-2: MiniScheme A and B Stephen Checkoway Structure of MiniScheme Environment env.rkt Contains the environment data type (env list-of-symbols list-of-values previous-env) Contains other procedures to

542 views • 24 slides
CS525: Advanced Database Organization Notes 6: Query Processing Parsing and pre-processing

CS525: Advanced Database Organization Notes 6: Query Processing Parsing and pre-processing

CS525: Advanced Database Organization Notes 6: Query Processing Parsing and pre-processing Yousef M. Elmehdwi Department of Computer Science Illinois Institute of Technology yelmehdwi@iit.edu October 9, 2018 Slides: adapted from a course

807 views • 33 slides
COMBINING PARTIAL EVALUATION AND SYMBOLIC EXECUTION Reiner Hhnle & Richard Bubel Chalmers

COMBINING PARTIAL EVALUATION AND SYMBOLIC EXECUTION Reiner Hhnle & Richard Bubel Chalmers

COMBINING PARTIAL EVALUATION AND SYMBOLIC EXECUTION Reiner Hhnle & Richard Bubel Chalmers University Symposium09 Speyer CONTROL CIRCUIT y = 80; threshold = 100; if (y > threshold) { decrease = true; } else { decrease = false;

598 views • 23 slides
Occam : Automated Software Winnowing Gregory Malecha 1 Ashish Gehani 2 Natarajan Shankar 2 1

Occam : Automated Software Winnowing Gregory Malecha 1 Ashish Gehani 2 Natarajan Shankar 2 1

Occam : Automated Software Winnowing Gregory Malecha 1 Ashish Gehani 2 Natarajan Shankar 2 1 Harvard 2 SRI Malecha, Gehani, Shankar Occam : Automated Software Winnowing 1 / 18 A story of success... Software engineering has been so successful

1.25k views • 27 slides
Symbolic Evaluation/Execution Todays Reading Material L. A. Clarke and D. J. Richardson,

Symbolic Evaluation/Execution Todays Reading Material L. A. Clarke and D. J. Richardson,

Symbolic Evaluation/Execution Todays Reading Material L. A. Clarke and D. J. Richardson, "Applications of Symbolic Evaluation," Journal of Systems and Software, 5 (1), January 1985, pp.15-35. Symbolic Evaluation/Execution

1.07k views • 60 slides
Normalization by Evaluation for Martin-Lf Type Theory with One Universe Peter Dybjer,

Normalization by Evaluation for Martin-Lf Type Theory with One Universe Peter Dybjer,

Normalization Martin-Lf type theory Normalization algorithm Decidability of equality Normalization by Evaluation for Martin-Lf Type Theory with One Universe Peter Dybjer, Gteborg (with Andreas Abel, Munich, and Klaus Aehlig, Swansea)

616 views • 28 slides
Towards a Formal Semantics for FHM: Part 2 Joey Capper and Henrik Nilsson School of Computer

Towards a Formal Semantics for FHM: Part 2 Joey Capper and Henrik Nilsson School of Computer

Towards a Formal Semantics for FHM: Part 2 Joey Capper and Henrik Nilsson School of Computer Science, University of Nottingham FPLab Away Day, Buxton, 8th of July 2011 Joey Capper and Henrik Nilsson (UoN) Verified FHM Semantics FPLab Away Day

544 views • 30 slides
Verifying Bit-Manipulations of Floating-P oint Wonyeol Lee Rahul Sharma Alex Aiken

Verifying Bit-Manipulations of Floating-P oint Wonyeol Lee Rahul Sharma Alex Aiken

Verifying Bit-Manipulations of Floating-P oint Wonyeol Lee Rahul Sharma Alex Aiken Stanford University PLDI 2016 This Talk Example: mathematical specification Goal: Bound the difference between spec and implementation

1.22k views • 111 slides
Fold-Based Fusion as a Library A Generative Programming Pearl Manohar Jonnalagedda, Sandro

Fold-Based Fusion as a Library A Generative Programming Pearl Manohar Jonnalagedda, Sandro

Fold-Based Fusion as a Library A Generative Programming Pearl Manohar Jonnalagedda, Sandro Stucki, EPFL Scala 15, Portland, June 13 2015 An Example val people2Movies: List[( String , List[ String ])] = List( (Sbastien, List(Hunger

631 views • 50 slides
December 5, 2019 Zach Tatlock OctoML Lets Get in the Wayback Machine 2018 Lets Get in

December 5, 2019 Zach Tatlock OctoML Lets Get in the Wayback Machine 2018 Lets Get in

2nd TVM and Deep Learning Compilation Conference December 5, 2019 Zach Tatlock OctoML Lets Get in the Wayback Machine 2018 Lets Get in the Wayback Machine 2018 Challenges for Deep Learning IRs State-of-the-art models increasingly

483 views • 17 slides
On the Operational Meaning of the Bar Construction ...with an application to Probability Paolo

On the Operational Meaning of the Bar Construction ...with an application to Probability Paolo

On the Operational Meaning of the Bar Construction ...with an application to Probability Paolo Perrone Joint work with Tobias Fritz Max Planck Institute for Mathematics in the Sciences Leipzig, Germany Category Theory 2018 Monads and formal

1.77k views • 142 slides
Programming with Boolean Satisfaction Michael Codish Department of Computer Science Ben Gurion

Programming with Boolean Satisfaction Michael Codish Department of Computer Science Ben Gurion

Programming with Boolean Satisfaction Michael Codish Department of Computer Science Ben Gurion University Beer-Sheva , Israel Joint work with: Vitaly Lagoon, Amit Metodi & Peter Stuckey CP meets CAV - 2012 I. Its all about solving hard

572 views • 54 slides
I dont care! On Incompleteness in Abstract Argumentation (and Belief Revision?) Pietro

I dont care! On Incompleteness in Abstract Argumentation (and Belief Revision?) Pietro

I dont care! On Incompleteness in Abstract Argumentation (and Belief Revision?) Pietro Baroni DII - Dip. di Ingegneria dellInformazione University of Brescia (Italy) Based on joint work with Massimiliano Giacomin and Beishui Liao

1.2k views • 67 slides
Instrew: Leveraging LLVM for High Performance Dynamic Binary Instrumentation Alexis Engelke

Instrew: Leveraging LLVM for High Performance Dynamic Binary Instrumentation Alexis Engelke

Instrew: Leveraging LLVM for High Performance Dynamic Binary Instrumentation Alexis Engelke Martin Schulz Chair of Computer Architecture and Parallel Systems TUM Department of Informatics Technical University of Munich VEE 2020, virtual

396 views • 25 slides
On Completion of Constraint Handling Rules Slim Abdennadher and Thom Fr uhwirth Computer

On Completion of Constraint Handling Rules Slim Abdennadher and Thom Fr uhwirth Computer

On Completion of Constraint Handling Rules Slim Abdennadher and Thom Fr uhwirth Computer Science Department University of Munich Oettingenstr. 67, 80538 Munich, Germany 1 6 Architecture of Constraint Programs application (e.g. in a CLP

258 views • 23 slides
Module 7 Policy Iteration CS 886 Sequential Decision Making and Reinforcement Learning

Module 7 Policy Iteration CS 886 Sequential Decision Making and Reinforcement Learning

Module 7 Policy Iteration CS 886 Sequential Decision Making and Reinforcement Learning University of Waterloo Policy Optimization Value iteration Optimize value function Extract induced policy Can we directly optimize the

589 views • 12 slides
Boosting Verifiable Computation on Encrypted Data PKC 2020 Dario Fiore, Anca Nitulescu , David

Boosting Verifiable Computation on Encrypted Data PKC 2020 Dario Fiore, Anca Nitulescu , David

Boosting Verifiable Computation on Encrypted Data PKC 2020 Dario Fiore, Anca Nitulescu , David Pointcheval Motivational Tale: The Bare Necessities of a Cloud User (In times of a Pandemic) 2 Pandemics biometric surveillance systems data

1k views • 51 slides
Concepts of Programming Design Scala and Lightweight Modular Staging (LMS) Alexey Rodriguez

Concepts of Programming Design Scala and Lightweight Modular Staging (LMS) Alexey Rodriguez

Concepts of Programming Design Scala and Lightweight Modular Staging (LMS) Alexey Rodriguez Blanter, Ferenc Balla, Matthijs Steen, Ruben Meerkerk, Ratih Ngestrini [ Faculty of Science Information and Computing Sciences] 1 Scala and Lightweight

1.33k views • 56 slides
In tro duction to F unctional Programming: Lecture 6 1 In tro duction to F unctional

In tro duction to F unctional Programming: Lecture 6 1 In tro duction to F unctional

In tro duction to F unctional Programming: Lecture 6 1 In tro duction to F unctional Programming John Harrison Univ ersit y of Cam bridge Lecture 6 Eectiv e ML T opics co v ered: Using standard com

302 views • 18 slides
Lesson 23 Linear partial differential equations 1 We have seen that ODEs can be reduced to

Lesson 23 Linear partial differential equations 1 We have seen that ODEs can be reduced to

Lesson 23 Linear partial differential equations 1 We have seen that ODEs can be reduced to almost banded infinite-dimensional equations using Chebyshev and ultraspherical polynomials These infinite-dimensional equations can be solved

878 views • 76 slides
Deep Learning for Partial Differential Equations William Wei National Center for Supercomputing

Deep Learning for Partial Differential Equations William Wei National Center for Supercomputing

Deep Learning for Partial Differential Equations William Wei National Center for Supercomputing Applications Center for Artificial Intelligence Innovation Department of Physics, University of Illinois Urban-Champaign Reference:

159 views • 12 slides
Linear algebra and differential equations (Math 54): Lecture 24 Vivek Shende April 23, 2019

Linear algebra and differential equations (Math 54): Lecture 24 Vivek Shende April 23, 2019

Linear algebra and differential equations (Math 54): Lecture 24 Vivek Shende April 23, 2019 Hello and welcome to class! Hello and welcome to class! For some time now Hello and welcome to class! For some time now We have been studying linear

1.05k views • 83 slides

More recommend