'First search' presentation slideshows

Reading and Review Chapter 12: Indexing and Hashing

Reading and Review Chapter 12: Indexing and Hashing. 12.1 Basic Concepts 12.2 Ordered Indices 12.3 B+-tree Index Files lots of stuff 12.4 B-tree Index Files 12.5 Static Hashing lots of stuff 12.6 Dynamic Hashing (Extendable Hashing) lots of stuff

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Classical Problem Solving

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Problem Solving

1.79k views • 85 slides

Robots: An Introduction

Robots: An Introduction. A robot can be defined as a computer controlled machine with some degrees of freedom that is, the ability to move about in its environment A robot typically has sensors to sense its environment, particularly to make sure it does not hit any obstacles in its way

1.2k views • 58 slides

Adversarial Search and Game Playing

Adversarial Search and Game Playing CS 271: Fall 2007 Instructor: Padhraic Smyth CSPs: phase transitions in problem space Hogg and Williams, AI Journal, 1994 Average time constraints/variables Graph coloring by human subjects From Kearns, Suri, Montfort, Science, 2006

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Intro

Intro. Name: Chun ping Wang Why? No idea Current status: Senior. What is computer science?. 1.Finding ways to solve answer. 2. Software designing. 3. Finding relation between software and hardware. 4. Finding relation between software and hardware. .

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Metric based KNN indexing

Metric based KNN indexing. Lecturer : Prof Ooi Beng Chin Presenters : Frankie Chan HT00-3550Y Tan Zhenqiang HT01-6163J. Outline. Introduction Examples SR-Tree MVP-Tree Future works Conclusion References. Introduction.

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Minimax Trees: Utility Evaluation, Tree Evaluation, Pruning

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The Evolution of a Sparse Partial Pivoting Algorithm

The Evolution of a Sparse Partial Pivoting Algorithm. John R. Gilbert with: Tim Davis, Jim Demmel, Stan Eisenstat, Laura Grigori, Stefan Larimore, Sherry Li, Joseph Liu, Esmond Ng, Tim Peierls, Barry Peyton, . . . Outline. Introduction: A modular approach to left-looking LU

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CSCE 3110 Data Structures & Algorithm Analysis

CSCE 3110 Data Structures & Algorithm Analysis. Rada Mihalcea http://www.cs.unt.edu/~rada/CSCE3110 Graphs (I) Reading: Chap.9, Weiss. What is a Graph?. A graph G = ( V ,E) is composed of: V : set of vertices E : set of edges connecting the vertices in V

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Notes 6: Two-Player Games and Search

Notes 6: Two-Player Games and Search ICS 171 Winter 2001 Outline Computer programs which play 2-player games game-playing as search with the complication of an opponent General principles of game-playing and search evaluation functions, minimax principle

878 views • 31 slides

A new linear algorithm for checking a graph for 3-edge-connectivity

A new linear algorithm for checking a graph for 3-edge-connectivity. Feng Sun. Advisor: Dr. Robert W. Robinson Committee: Dr. E. Rodney Canfield Dr. Eileen T. Kraemer. 2003.2. Outline. Overview Concepts and definitions Analysis of separation pairs

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Visualization of Biological Information with Circular Drawings

Visualization of Biological Information with Circular Drawings. Outline. Preliminaries Gene clustering Graph extraction from biological data Graph visualization Circular Drawings Conclusions and Discussion. Preliminaries. Graph G(V,E) : set of vertices V,

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Detecting and Correcting Malicious Data in VANETs

Detecting and Correcting Malicious Data in VANETs. Philippe Golle, Dan Greene, Jessica Staddon Palo Alto Research Center . Presented by: Jacob Lynch. Table of Contents. Introduction Related Work Classification of Attacks Distinguishability Model Example Conclusion. Introduction.

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Converting formulas into a normal form

Converting formulas into a normal form. Consider the following FOL formula stating that a brick is an object which is on another object which is not a pyramid, and there is nothing that a brick is on, and at the same time that object is on the brick, and there is nothing that is not

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A PARALLEL BISECTION ALGORITHM (WITHOUT COMMUNICATION)

A PARALLEL BISECTION ALGORITHM (WITHOUT COMMUNICATION). Rui Ralha DMAT, CMAT Univ. do Minho Portugal r_ralha@math.uminho.pt. Acknowledgements. CMAT FCT POCTI (European Union contribution) Prof. B. Parlett. Outline. Counting eigenvalues of symmetric tridiagonals

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Sparse Matrix Methods

Sparse Matrix Methods. Day 1: Overview Matlab and examples Data structures Ax=b Sparse matrices and graphs Fill-reducing matrix permutations Matching and block triangular form Day 2: Direct methods Day 3: Iterative methods. D. (Demo in Matlab). Matlab sprand spy sparse, full

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Depth-First Search

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Search applied to a problem against an adversary some actions are not under the control of the problem-solver there is a

Game playing. Search applied to a problem against an adversary some actions are not under the control of the problem-solver there is an opponent (hostile agent) Since it is a search problem, we must specify states & operations/actions

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LTL Model Checking

LTL Model Checking. 15-820A Flavio Lerda. LTL Model Checking. LTL Subset of CTL* of the form: A f where f is a path formula LTL model checking Model checking of a property expressed as an LTL formula: Given a model M and an initial state s 0 : M,s 0 ? A f. LTL Formulas.

386 views • 10 slides