realistic analysis of algorithms application to some
play

Realistic analysis of algorithms Application to some popular - PowerPoint PPT Presentation

Jun 26, 2023 •361 likes •1.15k views

Realistic analysis of algorithms Application to some popular algorithms Julien Clment (GREYC, CNRS, Univ. Caen, France) with Thu Hien Nguyen Thi and Brigitte Valle (and initiated with Philippe Flajolet) CanaDAM 2013

  1. “Realistic” analysis of algorithms Application to some popular algorithms Julien Clément (GREYC, CNRS, Univ. Caen, France) with Thu Hien Nguyen Thi and Brigitte Vallée (and initiated with Philippe Flajolet) CanaDAM 2013

  2. ❆♥❛❧②s✐s ♦❢ ❛❧❣♦r✐t❤♠s ❊①tr❡♠❛❧ ❝❛s❡s ✭✇♦rst✲❝❛s❡✱ ❜❡st✲❝❛s❡✮ ❖♥ t❤❡ ❛✈❡r❛❣❡ ✭♠♦r❡ r❡♣r❡s❡♥t❛t✐✈❡ ❢r♦♠ t❤❡ ✏❣❡♥❡r✐❝ ❝❛s❡✑❄✮ ■♥ ❞✐str✐❜✉t✐♦♥ ✭■♥♣✉ts ❞✐str✐❜✉t✐♦♥❄✮ ❲❤②❄ ❱❛❧✐❞❛t❡ ❛♥ ❛❧❣♦r✐t❤♠ ✭s❝❛❧✐♥❣✮✱ ❡st✐♠❛t❡ r✉♥♥✐♥❣ t✐♠❡ ❉❡s✐❣♥✐♥❣ ❛♥❞ ✉♥❞❡rst❛♥❞✐♥❣ ❛❧❣♦r✐t❤♠s ❖♣t✐♠✐③❛t✐♦♥ ❉❡✈❡❧♦♣ t♦♦❧s ❛♥❞ t❡❝❤♥✐q✉❡s ❍♦✇❄ ❆ ❧♦t ♦❢ t♦♦❧s ❛♥❞ t❡❝❤♥✐q✉❡s ✭❝♦♠❜✐♥❛t♦r✐❝s✱ ♣r♦❜❛❜✐❧✐t✐❡s✮ ❬❝❢✳ ❉✳ ❑♥✉t❤✱ P❤✳ ❋❧❛❥♦❧❡t❪ ❆♥❛❧②t✐❝ ❝♦♠❜✐♥❛t♦r✐❝s ✭❋❧❛❥♦❧❡t✲❙❡❞❣❡✇✐❝❦✮ ❋r❡❡❧② ❞♦✇♥❧♦❛❞❛❜❧❡✦ ✭❝❢✳ ❙❡❞❣❡✇✐❝❦✬s t❛❧❦✮ Introduction ❙t✉❞② t❤❡ ♣❡r❢♦r♠❛♥❝❡ ♦❢ ❛❧❣♦r✐t❤♠s

  3. ❲❤②❄ ❱❛❧✐❞❛t❡ ❛♥ ❛❧❣♦r✐t❤♠ ✭s❝❛❧✐♥❣✮✱ ❡st✐♠❛t❡ r✉♥♥✐♥❣ t✐♠❡ ❉❡s✐❣♥✐♥❣ ❛♥❞ ✉♥❞❡rst❛♥❞✐♥❣ ❛❧❣♦r✐t❤♠s ❖♣t✐♠✐③❛t✐♦♥ ❉❡✈❡❧♦♣ t♦♦❧s ❛♥❞ t❡❝❤♥✐q✉❡s ❍♦✇❄ ❆ ❧♦t ♦❢ t♦♦❧s ❛♥❞ t❡❝❤♥✐q✉❡s ✭❝♦♠❜✐♥❛t♦r✐❝s✱ ♣r♦❜❛❜✐❧✐t✐❡s✮ ❬❝❢✳ ❉✳ ❑♥✉t❤✱ P❤✳ ❋❧❛❥♦❧❡t❪ ❆♥❛❧②t✐❝ ❝♦♠❜✐♥❛t♦r✐❝s ✭❋❧❛❥♦❧❡t✲❙❡❞❣❡✇✐❝❦✮ ❋r❡❡❧② ❞♦✇♥❧♦❛❞❛❜❧❡✦ ✭❝❢✳ ❙❡❞❣❡✇✐❝❦✬s t❛❧❦✮ Introduction ❙t✉❞② t❤❡ ♣❡r❢♦r♠❛♥❝❡ ♦❢ ❛❧❣♦r✐t❤♠s ◮ ❆♥❛❧②s✐s ♦❢ ❛❧❣♦r✐t❤♠s ◮ ❊①tr❡♠❛❧ ❝❛s❡s ✭✇♦rst✲❝❛s❡✱ ❜❡st✲❝❛s❡✮ ◮ ❖♥ t❤❡ ❛✈❡r❛❣❡ ✭♠♦r❡ r❡♣r❡s❡♥t❛t✐✈❡ ❢r♦♠ t❤❡ ✏❣❡♥❡r✐❝ ❝❛s❡✑❄✮ ◮ ■♥ ❞✐str✐❜✉t✐♦♥ ✭■♥♣✉ts ❞✐str✐❜✉t✐♦♥❄✮

  4. ❍♦✇❄ ❆ ❧♦t ♦❢ t♦♦❧s ❛♥❞ t❡❝❤♥✐q✉❡s ✭❝♦♠❜✐♥❛t♦r✐❝s✱ ♣r♦❜❛❜✐❧✐t✐❡s✮ ❬❝❢✳ ❉✳ ❑♥✉t❤✱ P❤✳ ❋❧❛❥♦❧❡t❪ ❆♥❛❧②t✐❝ ❝♦♠❜✐♥❛t♦r✐❝s ✭❋❧❛❥♦❧❡t✲❙❡❞❣❡✇✐❝❦✮ ❋r❡❡❧② ❞♦✇♥❧♦❛❞❛❜❧❡✦ ✭❝❢✳ ❙❡❞❣❡✇✐❝❦✬s t❛❧❦✮ Introduction ❙t✉❞② t❤❡ ♣❡r❢♦r♠❛♥❝❡ ♦❢ ❛❧❣♦r✐t❤♠s ◮ ❆♥❛❧②s✐s ♦❢ ❛❧❣♦r✐t❤♠s ◮ ❊①tr❡♠❛❧ ❝❛s❡s ✭✇♦rst✲❝❛s❡✱ ❜❡st✲❝❛s❡✮ ◮ ❖♥ t❤❡ ❛✈❡r❛❣❡ ✭♠♦r❡ r❡♣r❡s❡♥t❛t✐✈❡ ❢r♦♠ t❤❡ ✏❣❡♥❡r✐❝ ❝❛s❡✑❄✮ ◮ ■♥ ❞✐str✐❜✉t✐♦♥ ✭■♥♣✉ts ❞✐str✐❜✉t✐♦♥❄✮ ◮ ❲❤②❄ ◮ ❱❛❧✐❞❛t❡ ❛♥ ❛❧❣♦r✐t❤♠ ✭s❝❛❧✐♥❣✮✱ ❡st✐♠❛t❡ r✉♥♥✐♥❣ t✐♠❡ ◮ ❉❡s✐❣♥✐♥❣ ❛♥❞ ✉♥❞❡rst❛♥❞✐♥❣ ❛❧❣♦r✐t❤♠s ◮ ❖♣t✐♠✐③❛t✐♦♥ ◮ ❉❡✈❡❧♦♣ t♦♦❧s ❛♥❞ t❡❝❤♥✐q✉❡s

  5. Introduction ❙t✉❞② t❤❡ ♣❡r❢♦r♠❛♥❝❡ ♦❢ ❛❧❣♦r✐t❤♠s ◮ ❆♥❛❧②s✐s ♦❢ ❛❧❣♦r✐t❤♠s ◮ ❊①tr❡♠❛❧ ❝❛s❡s ✭✇♦rst✲❝❛s❡✱ ❜❡st✲❝❛s❡✮ ◮ ❖♥ t❤❡ ❛✈❡r❛❣❡ ✭♠♦r❡ r❡♣r❡s❡♥t❛t✐✈❡ ❢r♦♠ t❤❡ ✏❣❡♥❡r✐❝ ❝❛s❡✑❄✮ ◮ ■♥ ❞✐str✐❜✉t✐♦♥ ✭■♥♣✉ts ❞✐str✐❜✉t✐♦♥❄✮ ◮ ❲❤②❄ ◮ ❱❛❧✐❞❛t❡ ❛♥ ❛❧❣♦r✐t❤♠ ✭s❝❛❧✐♥❣✮✱ ❡st✐♠❛t❡ r✉♥♥✐♥❣ t✐♠❡ ◮ ❉❡s✐❣♥✐♥❣ ❛♥❞ ✉♥❞❡rst❛♥❞✐♥❣ ❛❧❣♦r✐t❤♠s ◮ ❖♣t✐♠✐③❛t✐♦♥ ◮ ❉❡✈❡❧♦♣ t♦♦❧s ❛♥❞ t❡❝❤♥✐q✉❡s ◮ ❍♦✇❄ ◮ ❆ ❧♦t ♦❢ t♦♦❧s ❛♥❞ t❡❝❤♥✐q✉❡s ✭❝♦♠❜✐♥❛t♦r✐❝s✱ ♣r♦❜❛❜✐❧✐t✐❡s✮ ❬❝❢✳ ❉✳ ❑♥✉t❤✱ P❤✳ ❋❧❛❥♦❧❡t❪ ◮ ❆♥❛❧②t✐❝ ❝♦♠❜✐♥❛t♦r✐❝s ✭❋❧❛❥♦❧❡t✲❙❡❞❣❡✇✐❝❦✮ ❋r❡❡❧② ❞♦✇♥❧♦❛❞❛❜❧❡✦ ✭❝❢✳ ❙❡❞❣❡✇✐❝❦✬s t❛❧❦✮

  6. ❜❛s❡❞ ✉♣♦♥ ❝♦♠♣❛r✐s♦♥s ✭❛♥❞ s✇❛♣s✮ ❜❡t✇❡❡♥ ❦❡②s✳ ❚❤❡ ✉♥✐t❛r② ❝♦st ✐s t❤❡ ❦❡② ❝♦♠♣❛r✐s♦♥✳ ❚❤❡ ❜❡❤❛✈✐♦✉r ♦♥❧② ❞❡♣❡♥❞s ♦♥ t❤❡ r❡❧❛t✐✈❡ ♦r❞❡r ❜❡t✇❡❡♥ ❦❡②s✳ ❲❡ ❝❛♥ r❡str✐❝t t♦ ✶ ♥ ✳ ❚❤❡ s❡t ♦❢ ✐♥♣✉ts ✐s t❤❡♥ ♥ ✭♣❡r♠✉t❛t✐♦♥s✮ ✇✐t❤ t❤❡ ✉♥✐❢♦r♠ ❞✐str✐❜✉t✐♦♥✳ ■♥ t❤✐s ❝♦♥t❡①t✱ ♠♦st t❤✐♥❣s ❛r❡ ✇❡❧❧ ✉♥❞❡rst♦♦❞ ✭❜❡st✱ ✇♦rst✱ ❛✈❡r❛❣❡ ❝❛s❡s✮✳ ❆❧❣♦r✐t❤♠s ❑ ♥ ◗✉✐❝❦❙♦rt ✷ ♥ ❧♦❣ ♥ ♥ ✷ ■♥s❙♦rt ✹ ♥ ✷ ❇✉❜❙♦rt ✷ ◗✉✐❝❦▼✐♥ ✷ ♥ ❙❡❧▼✐♥ ♥ ❑ ♥ ♠❡❛♥ ♥✉♠❜❡r ♦❢ ❦❡② ❝♦♠♣❛r✐s♦♥s Classic framework for sorting and searching algorithms ◮ ❚❤❡ ♠❛✐♥ s♦rt✐♥❣ ❛♥❞ s❡❛r❝❤✐♥❣ ❛❧❣♦r✐t❤♠s✱ ❡✳❣✳✱ ◗✉✐❝❦❙♦rt✱ ❇❙❚✲❙❡❛r❝❤✱ ■♥s❡rt✐♦♥❙♦rt✱✳✳✳ ❝♦♥s✐❞❡r ♥ ✭❞✐st✐♥❝t✮ ❦❡②s ❯ ✶ , ❯ ✷ , . . . , ❯ ♥ ❢r♦♠ t❤❡ s❛♠❡ ♦r❞❡r❡❞ s❡t Ω ✳

  7. ❚❤❡ ❜❡❤❛✈✐♦✉r ♦♥❧② ❞❡♣❡♥❞s ♦♥ t❤❡ r❡❧❛t✐✈❡ ♦r❞❡r ❜❡t✇❡❡♥ ❦❡②s✳ ❲❡ ❝❛♥ r❡str✐❝t t♦ ✶ ♥ ✳ ❚❤❡ s❡t ♦❢ ✐♥♣✉ts ✐s t❤❡♥ ♥ ✭♣❡r♠✉t❛t✐♦♥s✮ ✇✐t❤ t❤❡ ✉♥✐❢♦r♠ ❞✐str✐❜✉t✐♦♥✳ ■♥ t❤✐s ❝♦♥t❡①t✱ ♠♦st t❤✐♥❣s ❛r❡ ✇❡❧❧ ✉♥❞❡rst♦♦❞ ✭❜❡st✱ ✇♦rst✱ ❛✈❡r❛❣❡ ❝❛s❡s✮✳ ❆❧❣♦r✐t❤♠s ❑ ♥ ◗✉✐❝❦❙♦rt ✷ ♥ ❧♦❣ ♥ ♥ ✷ ■♥s❙♦rt ✹ ♥ ✷ ❇✉❜❙♦rt ✷ ◗✉✐❝❦▼✐♥ ✷ ♥ ❙❡❧▼✐♥ ♥ ❑ ♥ ♠❡❛♥ ♥✉♠❜❡r ♦❢ ❦❡② ❝♦♠♣❛r✐s♦♥s Classic framework for sorting and searching algorithms ◮ ❚❤❡ ♠❛✐♥ s♦rt✐♥❣ ❛♥❞ s❡❛r❝❤✐♥❣ ❛❧❣♦r✐t❤♠s✱ ❡✳❣✳✱ ◗✉✐❝❦❙♦rt✱ ❇❙❚✲❙❡❛r❝❤✱ ■♥s❡rt✐♦♥❙♦rt✱✳✳✳ ❝♦♥s✐❞❡r ♥ ✭❞✐st✐♥❝t✮ ❦❡②s ❯ ✶ , ❯ ✷ , . . . , ❯ ♥ ❢r♦♠ t❤❡ s❛♠❡ ♦r❞❡r❡❞ s❡t Ω ✳ ◮ ❜❛s❡❞ ✉♣♦♥ ❝♦♠♣❛r✐s♦♥s ✭❛♥❞ s✇❛♣s✮ ❜❡t✇❡❡♥ ❦❡②s✳ ❚❤❡ ✉♥✐t❛r② ❝♦st ✐s t❤❡ ❦❡② ❝♦♠♣❛r✐s♦♥✳

Recommend

From Worst-Case to Realistic-Case Analysis for Large Scale Machine Learning Algorithms

From Worst-Case to Realistic-Case Analysis for Large Scale Machine Learning Algorithms

From Worst-Case to Realistic-Case Analysis for Large Scale Machine Learning Algorithms Maria-Florina Balcan, PI Avrim Blum, Co-PI Tom M Mitchell, Co-PI Students Travis Dick Nika Haghtalab Hongyang Zhang Motivation Machine learning

443 views • 22 slides
Analysis of Scaling Algorithms for Matrix & Operator Scaling Contents Scaling Algorithms

Analysis of Scaling Algorithms for Matrix & Operator Scaling Contents Scaling Algorithms

Rafael Oliveira University of Toronto Analysis of Scaling Algorithms for Matrix & Operator Scaling Contents Scaling Algorithms Three Step Analysis Generalization One More Application of Scaling Non-Negative Matrices &

604 views • 15 slides
Dynamical analysis of euclidean algorithms Introduction Dynamical analysis of euclidean

Dynamical analysis of euclidean algorithms Introduction Dynamical analysis of euclidean

Dynamical analysis of euclidean algorithms Beno t Daireaux Dynamical analysis of euclidean algorithms Introduction Dynamical analysis of euclidean algorithms Beno t Daireaux Application to accelerated GREYC, Universit e

978 views • 76 slides
You Only Live Multiple Times Black box re-use of Crash-Stop Algorithms In Realistic Crash-Recovery

You Only Live Multiple Times Black box re-use of Crash-Stop Algorithms In Realistic Crash-Recovery

You Only Live Multiple Times Black box re-use of Crash-Stop Algorithms In Realistic Crash-Recovery Settings DAVID KOZHAYA 1 , OGNJEN MARIC 2 , AND YVONNE-ANNE PIGNOLET 1 1 ABB CORPORATE RESEARCH SWITZERLAND , 2 DIGITAL ASSET SWITZERLAND A

555 views • 19 slides
Methods for Modeling Realistic Methods for Modeling Realistic Playing in Plucked-String

Methods for Modeling Realistic Methods for Modeling Realistic Playing in Plucked-String

DAFX00, Verona, Italy, December 2000 HELSINKI UNIVERSITY OF TECHNOLOGY Methods for Modeling Realistic Methods for Modeling Realistic Playing in Plucked-String Synthesis: Playing in Plucked-String Synthesis: Analysis, Control and Synthesis

468 views • 20 slides
PAFFI: Performance Analysis Framework for Fog Infrastructures in realistic scenarios Claudia

PAFFI: Performance Analysis Framework for Fog Infrastructures in realistic scenarios Claudia

PAFFI: Performance Analysis Framework for Fog Infrastructures in realistic scenarios Claudia Canali, Riccardo Lancellotti Department of Engineering Enzo Ferrari University of Modena and Reggio Emilia ICCCS - Oct. 10-12, 2019, Rome 1 Fog

335 views • 16 slides
ANALYSIS of EUCLIDEAN ALGORITHMS An Arithmetical Instance of Dynamical Analysis Dynamical

ANALYSIS of EUCLIDEAN ALGORITHMS An Arithmetical Instance of Dynamical Analysis Dynamical

ANALYSIS of EUCLIDEAN ALGORITHMS An Arithmetical Instance of Dynamical Analysis Dynamical Analysis := Analysis of Algorithms + Dynamical Systems Brigitte Vall ee (CNRS and Universit e de Caen, France) Results obtained with : Ali Akhavi ,

1.73k views • 125 slides
ANALYSIS of EUCLIDEAN ALGORITHMS An Arithmetical Instance of Dynamical Analysis Dynamical

ANALYSIS of EUCLIDEAN ALGORITHMS An Arithmetical Instance of Dynamical Analysis Dynamical

ANALYSIS of EUCLIDEAN ALGORITHMS An Arithmetical Instance of Dynamical Analysis Dynamical Analysis := Analysis of Algorithms + Dynamical Systems Brigitte Vall ee (CNRS and Universit e de Caen, France) Results obtained with : Ali Akhavi ,

893 views • 55 slides
ECE 2574: Data Structures and Algorithms - Analysis of Algorithms C. L. Wyatt Today we will look

ECE 2574: Data Structures and Algorithms - Analysis of Algorithms C. L. Wyatt Today we will look

ECE 2574: Data Structures and Algorithms - Analysis of Algorithms C. L. Wyatt Today we will look at how we analyze (compare and contrast) different algorithms and how that analysis can guide our choice of algorithm in a particular case.

227 views • 18 slides
Realistic Evaluation of Deep Semi-Supervised Learning Algorithms Avital Oliver* Augustus Odena*

Realistic Evaluation of Deep Semi-Supervised Learning Algorithms Avital Oliver* Augustus Odena*

Realistic Evaluation of Deep Semi-Supervised Learning Algorithms Avital Oliver* Augustus Odena* Colin Raffel* Ekin Dogus Cubuk Ian Goodfellow vs. Error rates for our reimplementation of different semi-supervised learning methods. Reported

212 views • 17 slides
Mathematical Analysis of Genetic Algorithms Genetic Algorithms are not appropriate for

Mathematical Analysis of Genetic Algorithms Genetic Algorithms are not appropriate for

Mathematical Analysis of Genetic Algorithms Genetic Algorithms are not appropriate for certain problems where finding the exact global optimum is required. Genetic Algorithms are non-deterministic. However, there are theories about

271 views • 5 slides
The impact of Analysis of Algorithms on Bioinformatics Gaston H. Gonnet Informatik, ETH, Zurich

The impact of Analysis of Algorithms on Bioinformatics Gaston H. Gonnet Informatik, ETH, Zurich

The impact of Analysis of Algorithms on Bioinformatics Gaston H. Gonnet Informatik, ETH, Zurich Analysis of Algorithms, Maresias, April 16, 2008 Abstract In principle, Analysis of Algorithms and Bioinformatics share few tools and methods.

1.02k views • 43 slides
Mind The Portability A Warriors Guide through Realistic Profiled Side-channel Analysis Shivam

Mind The Portability A Warriors Guide through Realistic Profiled Side-channel Analysis Shivam

Mind The Portability A Warriors Guide through Realistic Profiled Side-channel Analysis Shivam Bhasin 1 , Dirmanto Jap 1 , Anupam Chattopadhyay 1 , Stjepan Picek 2 , Annelie Heuser 3 , and Ritu Ranjan Shrivastwa 4 1 NTU, Singapore 2 TU Delft,

335 views • 22 slides
Analysis of Algorithms Amr Magdy Analyzing Algorithms Algorithm Correctness 1. Termination a.

Analysis of Algorithms Amr Magdy Analyzing Algorithms Algorithm Correctness 1. Termination a.

CS141: Intermediate Data Structures and Algorithms Analysis of Algorithms Amr Magdy Analyzing Algorithms Algorithm Correctness 1. Termination a. Produces the correct output for all possible input. b. Algorithm Performance 2. Either

1.02k views • 64 slides
outline development of cryptographic algorithms for a real life application introduction

outline development of cryptographic algorithms for a real life application introduction

Design and Analysis of Cryptographic Algorithms for Mobile Communication Systems Henri Gilbert Orange Labs {firstname.lastname@orange-ftgroup.com} research & development outline development of cryptographic algorithms for a real life

486 views • 12 slides
INFORMATION THEORY: SOURCES, DIRICHLET SERIES, REALISTIC ANALYSIS OF DATA STRUCTURES Mathieu Roux

INFORMATION THEORY: SOURCES, DIRICHLET SERIES, REALISTIC ANALYSIS OF DATA STRUCTURES Mathieu Roux

INFORMATION THEORY: SOURCES, DIRICHLET SERIES, REALISTIC ANALYSIS OF DATA STRUCTURES Mathieu Roux and Brigitte Vall ee GREYC Laboratory (CNRS and University of Caen, France) Talk also based on joint works with Viviane Baladi , Eda Cesaratto ,

1.22k views • 96 slides
Program Analysis 1 Summary Summary analysis of algorithms asymptotic analysis

Program Analysis 1 Summary Summary analysis of algorithms asymptotic analysis

csci 210: Data Structures Program Analysis 1 Summary Summary analysis of algorithms asymptotic analysis big-O big-Omega big-theta asymptotic notation commonly used functions discrete math

500 views • 33 slides
MA/CSSE 473 Day 02 Algorithms Intro Some Numeric Algorithms and their Analysis Student

MA/CSSE 473 Day 02 Algorithms Intro Some Numeric Algorithms and their Analysis Student

MA/CSSE 473 Day 02 Algorithms Intro Some Numeric Algorithms and their Analysis Student questions on Syllabus? Course procedures, policies, or resources? Course materials? Homework assignments? Anything else? A

179 views • 17 slides
Analysis of Algorithms What to analyze [Lewis/Denenberg 2.1, Goodrich/Tamassia 3.5]

Analysis of Algorithms What to analyze [Lewis/Denenberg 2.1, Goodrich/Tamassia 3.5]

TDDB56 DALGOPT-D Lecture 2: Analysis of algorithms. Page 1 C. Kessler, IDA, Link opings Universitet, 2001. Analysis of Algorithms What to analyze [Lewis/Denenberg 2.1, Goodrich/Tamassia 3.5] correctness termination efficiency

728 views • 31 slides
TALx86: A Realistic Typed Assembly Language TALx86: A Realistic Typed Assembly Language Dan

TALx86: A Realistic Typed Assembly Language TALx86: A Realistic Typed Assembly Language Dan

TALx86: A Realistic Typed Assembly Language TALx86: A Realistic Typed Assembly Language Dan Grossman, Fred Smith Cornell University Joint work with: Greg Morrisett, Karl Crary (CMU), Neal Glew, Richard Samuels, Dave Walker, Stephanie Weirich,

447 views • 20 slides
Empirical Analysis of SLS Algorithms adapted and extended from slides for SLS:FA, Chapter 4

Empirical Analysis of SLS Algorithms adapted and extended from slides for SLS:FA, Chapter 4

HEURISTIC OPTIMIZATION Empirical Analysis of SLS Algorithms adapted and extended from slides for SLS:FA, Chapter 4 Analysis of SLS algorithms I How long does it take to find a feasible solution? I How good are the solutions generated by the

860 views • 54 slides
Empirical Analysis of SLS Algorithms adapted and extended from slides for SLS:FA, Chapter 4

Empirical Analysis of SLS Algorithms adapted and extended from slides for SLS:FA, Chapter 4

HEURISTIC OPTIMIZATION Empirical Analysis of SLS Algorithms adapted and extended from slides for SLS:FA, Chapter 4 Analysis of SLS algorithms I How long does it take to find a feasible solution? I How good are the solutions generated by the

535 views • 19 slides
8. Average-Case Analysis of Algorithms + Randomized Algorithms 1 outline and goals 1)

8. Average-Case Analysis of Algorithms + Randomized Algorithms 1 outline and goals 1)

CSE 421, Spring 2017, W.L.Ruzzo 8. Average-Case Analysis of Algorithms + Randomized Algorithms 1 outline and goals 1) Probability tools you've seen allow formal definition of "average case" running time of algorithms 2) Coupled

943 views • 19 slides
GLOBAL ILLUMINATION ALGORITHMS Graphics & Visualization: Principles & Algorithms

GLOBAL ILLUMINATION ALGORITHMS Graphics & Visualization: Principles & Algorithms

Graphics & Visualization Chapter 16 GLOBAL ILLUMINATION ALGORITHMS Graphics & Visualization: Principles & Algorithms Chapter 16 Introduction Global Illumination Algorithms: Deal with the realistic computation of light

1.23k views • 99 slides

More recommend