18.04.2013
•
Views
file:///E|/WEBSITE/BIBLIO/TESTDATA/PEOPLE_N Cavicchioli, Alberto Cazzaniga, Franco Cerruti, Umberto Chareyron, Jacques Chiarenza, Filippo Chiarolla, Maria Chicco, Maurizio Cirina, Marco Coen, Salvatore Colaneri, Patrizio Collino, Alberto Conforti, Domenico Conte, Giuseppe Contessa, Maria Conti, Roberto Contro, Filippo Corsi Tani, Gabriella Coti Zelati, Vittorio Cotta-Ramusino, Paolo F Crosta, Giovanni F D'Alessandro, Paolo D'Ambra, Pasqua D'Alessandro, Paolo D'Ambra, Pasqua D'Amore, Luisa D'Aprile, Margherita D'Aquino, Paola D'Auria, Catello Dagnino, Catterina Damiani, Ernesto de Bartolomeis, Paolo De Leone, Renato De Luca, Aldo de Lucia, Paolo De Mari, Filippo De Pascale, Espedito De Sena, Silvestro F de-Michele, Leonede DeAngelis, Pasquale L Del Fra, Alberto Dell'Antonio, Gianfausto Detofoli, Rino Di Maio, Giuseppe Di Martino, Lino Di Pillo, Gianni Di Serafino, Daniela Dominici, Paolo Lanza de Cristoforis, M Van Der Mee, Cornelis V Ebagezio, Valter Elia, Michele Emmanuele, Giovanni Emmer, Michele Evangelista, Elio Del Fra, Alberto Facchinei, Francisco Facchini, Alberto Faina, Giorgio Falcone, Maurizio Famularo, Domenico file:///E|/WEBSITE/BIBLIO/TESTDATA/PEOPLE_N (22 of 64) [19/1/2003 1:40:36]
file:///E|/WEBSITE/BIBLIO/TESTDATA/PEOPLE_N Fania, Maria L Farranti, Matteo Fasano, Antonio Ferragina, Paolo Ferrari, Carlo Ferrari, Luca Ferri, Massimo Ferro, Ruggero Figa-Talamanca, Alessandro Figari, Rodolfo Filippone, Salvatore Filipponi, Piero Floreanini, Roberto Fontana, Marco Forni, Giovanni Francaviglia, Mauro Franchi, Bruno Frittelli, Marco Frosali, Giovanni Frosini, Patrizio Moseneder-Frajria, Pierluigi Paveri-Fontana, Stefano L Gaivoronski, Alexei A Galbiati, Margherita Gargano, Luisa Garrisi, Daniele Gastaldi, Tommaso Gatteschi, Luigi Gaudioso, Manlio Gaviano, Marco Gentile, Antonio Gentili, Graziano Geronazzo, Lucio Ghinelli-Smit, Dina Giambruno, Antonino Giaquinta, Mariano Gimigliano, Alessandro Giorgi, Giorgio Girone, Giovanni Giuli, Eraldo Giunta, Giulio Glielmo, Luigi Van Geemen, Bert Iannelli, Mimmo Invernizzi, Sergio Iozzi, Fabrizio Kisel, Ema De Leone, Renato Laccetti, Giuliano Laeng, Enrico Lammens, Johan M Landucci, Mario Lanteri, Antonio Lanza de Cristoforis, M Laurence, Peter M Lauria, Francesco E Leoni, Giovanni Licalzi, Marco De Mari, Filippo Di Maio, Giuseppe Di Martino, Lino file:///E|/WEBSITE/BIBLIO/TESTDATA/PEOPLE_N (23 of 64) [19/1/2003 1:40:37]
-
Page 1 and 2:
The Algorithm Design Manual Next: P
-
Page 3 and 4:
Preface Next: Acknowledgments Up: T
-
Page 5 and 6:
Preface one stressing design over a
-
Page 7 and 8:
Acknowledgments Mon Jun 2 23:33:50
-
Page 9 and 10:
Contents Next: Techniques Up: The A
-
Page 11 and 12:
Contents ■ All-Pairs Shortest Pat
-
Page 13 and 14:
Contents ■ Graph Problems: Polyno
-
Page 15 and 16:
Contents ● About this document ..
-
Page 17 and 18:
The Algorithm Design Manual The Alg
-
Page 19 and 20:
Lecture Notes -- Analysis of Algori
-
Page 21 and 22:
Lecture Notes -- Analysis of Algori
-
Page 23 and 24:
The Stony Brook Algorithm Repositor
-
Page 25 and 26:
Techniques Next: Introduction to Al
-
Page 27 and 28:
Techniques Algorithms Mon Jun 2 23:
-
Page 29 and 30:
Introduction to Algorithms ● Reas
-
Page 31 and 32:
Data Structures and Sorting divide-
-
Page 33 and 34:
Breaking Problems Down ● Dynamic
-
Page 35 and 36:
Graph Algorithms The take-home less
-
Page 37 and 38:
Combinatorial Search and Heuristic
-
Page 39 and 40:
Intractable Problems and Approximat
-
Page 41 and 42:
How to Design Algorithms Next: Reso
-
Page 43 and 44:
How to Design Algorithms with a cou
-
Page 45 and 46:
How to Design Algorithms Next: Reso
-
Page 47 and 48:
A Catalog of Algorithmic Problems N
-
Page 49 and 50:
A Catalog of Algorithmic Problems
-
Page 51 and 52:
Algorithmic Resources Next: Softwar
-
Page 53 and 54:
References L. Adleman. Algorithmic
-
Page 55 and 56:
References AS89 Ata83 Ata84 problem
-
Page 57 and 58:
References BJL 91 A. Blum, T. Jiang
-
Page 59 and 60:
References BS81 BS86 BS93 BS96 BS97
-
Page 61 and 62:
References J. M. Chambers. Partial
-
Page 63 and 64:
References CT80 CT92 1971. G. Carpa
-
Page 65 and 66:
References K. Daniels and V. Milenk
-
Page 67 and 68:
References (FOCS), pages 60-69, 199
-
Page 69 and 70:
References FM71 M. Fischer and A. M
-
Page 71 and 72:
References History of Computing, 7:
-
Page 73 and 74:
References N. Gibbs, W. Poole, and
-
Page 75 and 76:
References Hof82 Hof89 Hol75 C. M.
-
Page 77 and 78:
References IK75 Ita78 O. Ibarra and
-
Page 79 and 80:
References Kir83 D. Kirkpatrick. Ef
-
Page 81 and 82:
References object in 2-dimensional
-
Page 83 and 84:
References LT79 LT80 8:99-118, 1995
-
Page 85 and 86:
References Mil97 V. Milenkovic. Dou
-
Page 87 and 88:
References Theoretical Computer Sci
-
Page 89 and 90:
References Pav82 T. Pavlidis. Algor
-
Page 91 and 92:
References Rei72 Rei91 Rei94 E. Rei
-
Page 93 and 94:
References Prentice Hall, Englewood
-
Page 95 and 96:
References SR95 SS71 SS90 SSS74 ST8
-
Page 97 and 98:
References Tin90 Mikkel Thorup. On
-
Page 99 and 100:
References Wel84 T. Welch. A techni
-
Page 101 and 102:
References Algorithms Mon Jun 2 23:
-
Page 103 and 104:
Correctness and Efficiency Next: Co
-
Page 105 and 106:
Correctness NearestNeighborTSP(P) P
-
Page 107 and 108:
Correctness Figure: A bad example f
-
Page 109 and 110:
Efficiency Next: Expressing Algorit
-
Page 111 and 112:
Keeping Score Next: The RAM Model o
-
Page 113 and 114:
The RAM Model of Computation substa
-
Page 115 and 116:
Best, Worst, and Average-Case Compl
-
Page 117 and 118:
The Big Oh Notation Figure: Illustr
-
Page 119 and 120:
Logarithms Next: Modeling the Probl
-
Page 121 and 122:
Logarithms justified in ignoring th
-
Page 123 and 124:
Modeling the Problem Figure: Modeli
-
Page 125 and 126:
About the War Stories Next: War Sto
-
Page 127 and 128:
War Story: Psychic Modeling Next: E
-
Page 129 and 130:
War Story: Psychic Modeling have pu
-
Page 131 and 132:
War Story: Psychic Modeling Next: E
-
Page 133 and 134:
Exercises (b) If I prove that an al
-
Page 135 and 136:
Fundamental Data Types Next: Contai
-
Page 137 and 138:
Containers Next: Dictionaries Up: F
-
Page 139 and 140:
Dictionaries Next: Binary Search Tr
-
Page 141 and 142:
Binary Search Trees BinaryTreeQuery
-
Page 143 and 144:
Priority Queues Next: Specialized D
-
Page 145 and 146:
Specialized Data Structures Next: S
-
Page 147 and 148:
Sorting Next: Applications of Sorti
-
Page 149 and 150:
Applications of Sorting Figure: Con
-
Page 151 and 152:
Data Structures Next: Incremental I
-
Page 153 and 154:
Incremental Insertion Next: Divide
-
Page 155 and 156:
Randomization Next: Bucketing Techn
-
Page 157 and 158:
Randomization Next: Bucketing Techn
-
Page 159 and 160:
Bucketing Techniques Algorithms Mon
-
Page 161 and 162:
War Story: Stripping Triangulations
-
Page 163 and 164:
War Story: Stripping Triangulations
-
Page 165 and 166:
War Story: Mystery of the Pyramids
-
Page 167 and 168:
War Story: Mystery of the Pyramids
-
Page 169 and 170:
War Story: String 'em Up We were co
-
Page 171 and 172:
War Story: String 'em Up Figure: Su
-
Page 173 and 174:
Exercises Next: Implementation Chal
-
Page 175 and 176:
Exercises used to select the pivot.
-
Page 177 and 178:
Dynamic Programming Next: Fibonacci
-
Page 179 and 180:
Fibonacci numbers Next: The Partiti
-
Page 181 and 182:
Fibonacci numbers Next: The Partiti
-
Page 183 and 184:
The Partition Problem . What is the
-
Page 185 and 186:
The Partition Problem Figure: Dynam
-
Page 187 and 188:
Approximate String Matching Next: L
-
Page 189 and 190:
Approximate String Matching The val
-
Page 191 and 192:
Longest Increasing Sequence Will th
-
Page 193 and 194:
Minimum Weight Triangulation Next:
-
Page 195 and 196:
Limitations of Dynamic Programming
-
Page 197 and 198:
War Story: Evolution of the Lobster
-
Page 199 and 200:
War Story: Evolution of the Lobster
-
Page 201 and 202:
War Story: What's Past is Prolog Ne
-
Page 203 and 204:
War Story: What's Past is Prolog th
-
Page 205 and 206:
War Story: Text Compression for Bar
-
Page 207 and 208:
War Story: Text Compression for Bar
-
Page 209 and 210:
Divide and Conquer Next: Fast Expon
-
Page 211 and 212:
Fast Exponentiation Next: Binary Se
-
Page 213 and 214:
Binary Search Next: Square and Othe
-
Page 215 and 216:
Exercises Next: Implementation Chal
-
Page 217 and 218:
Exercises whose denominations are ,
-
Page 219 and 220:
The Friendship Graph Next: Data Str
-
Page 221 and 222:
The Friendship Graph friendship gra
-
Page 223 and 224:
Data Structures for Graphs linked t
-
Page 225 and 226:
War Story: Getting the Graph ``Well
-
Page 227 and 228:
Traversing a Graph Next: Breadth-Fi
-
Page 229 and 230:
Breadth-First Search Next: Depth-Fi
-
Page 231 and 232:
Depth-First Search Next: Applicatio
-
Page 233 and 234:
Depth-First Search Next: Applicatio
-
Page 235 and 236:
Connected Components Next: Tree and
-
Page 237 and 238:
Two-Coloring Graphs Next: Topologic
-
Page 239 and 240:
Topological Sorting Next: Articulat
-
Page 241 and 242:
Modeling Graph Problems Next: Minim
-
Page 243 and 244:
Modeling Graph Problems good line s
-
Page 245 and 246:
Minimum Spanning Trees ● Prim's A
-
Page 247 and 248:
Prim's Algorithm inserted edge (x,y
-
Page 249 and 250:
Kruskal's Algorithm a tree of weigh
-
Page 251 and 252:
Dijkstra's Algorithm Next: All-Pair
-
Page 253 and 254:
All-Pairs Shortest Path Next: War S
-
Page 255 and 256:
War Story: Nothing but Nets Next: W
-
Page 257 and 258:
War Story: Nothing but Nets ``You a
-
Page 259 and 260:
War Story: Dialing for Documents Ne
-
Page 261 and 262:
War Story: Dialing for Documents If
-
Page 263 and 264:
War Story: Dialing for Documents CO
-
Page 265 and 266:
Exercises Next: Implementation Chal
-
Page 267 and 268:
Exercises Prove the statement or gi
-
Page 269 and 270:
Backtracking report it. kth element
-
Page 271 and 272:
Constructing All Subsets Next: Cons
-
Page 273 and 274:
Constructing All Paths in a Graph N
-
Page 275 and 276:
Search Pruning Next: Bandwidth Mini
-
Page 277 and 278:
Bandwidth Minimization immediately
-
Page 279 and 280:
War Story: Covering Chessboards Nex
-
Page 281 and 282:
War Story: Covering Chessboards att
-
Page 283 and 284:
Heuristic Methods Mon Jun 2 23:33:5
-
Page 285 and 286:
Simulated Annealing Return S then u
-
Page 287 and 288:
Traveling Salesman Problem Next: Ma
-
Page 289 and 290:
Independent Set Next: Circuit Board
-
Page 291 and 292:
Neural Networks Next: Genetic Algor
-
Page 293 and 294:
Genetic Algorithms Next: War Story:
-
Page 295 and 296:
War Story: Annealing Arrays Next: P
-
Page 297 and 298:
War Story: Annealing Arrays optimal
-
Page 299 and 300:
Parallel Algorithms Next: War Story
-
Page 301 and 302:
War Story: Going Nowhere Fast Next:
-
Page 303 and 304:
Exercises Next: Implementation Chal
-
Page 305 and 306:
Problems and Reductions Next: Simpl
-
Page 307 and 308:
Simple Reductions Next: Hamiltonian
-
Page 309 and 310:
Hamiltonian Cycles Next: Independen
-
Page 311 and 312:
Independent Set and Vertex Cover pr
-
Page 313 and 314:
Clique and Independent Set These la
-
Page 315 and 316:
Satisfiability Mon Jun 2 23:33:50 E
-
Page 317 and 318:
The Theory of NP-Completeness Next:
-
Page 319 and 320:
3-Satisfiability where for , , , an
-
Page 321 and 322:
Integer Programming Next: Vertex Co
-
Page 323 and 324:
Integer Programming possible IP ins
-
Page 325 and 326:
Vertex Cover reduction for the 3-SA
-
Page 327 and 328:
Other NP-Complete Problems hard. Th
-
Page 329 and 330:
The Art of Proving Hardness easiest
-
Page 331 and 332:
War Story: Hard Against the Clock N
-
Page 333 and 334:
War Story: Hard Against the Clock I
-
Page 335 and 336:
Approximation Algorithms Next: Appr
-
Page 337 and 338:
Approximating Vertex Cover Next: Th
-
Page 339 and 340:
The Euclidean Traveling Salesman Ne
-
Page 341 and 342:
The Euclidean Traveling Salesman Ne
-
Page 343 and 344:
Exercises 1. Prove that the low deg
-
Page 345 and 346:
Data Structures Next: Dictionaries
-
Page 347 and 348:
Dictionaries Next: Priority Queues
-
Page 349 and 350:
Dictionaries use a function that ma
-
Page 351 and 352:
Dictionaries Implementation-oriente
-
Page 353 and 354:
Priority Queues ● Besides access
-
Page 355 and 356:
Priority Queues Fibonacci heaps [FT
-
Page 357 and 358:
Suffix Trees and Arrays Figure: A t
-
Page 359 and 360:
Suffix Trees and Arrays [GBY91]. Se
-
Page 361 and 362:
Graph Data Structures algorithms).
-
Page 363 and 364:
Graph Data Structures including the
-
Page 365 and 366:
Set Data Structures Next: Kd-Trees
-
Page 367 and 368:
Set Data Structures parent pointers
-
Page 369 and 370:
Kd-Trees Next: Numerical Problems U
-
Page 371 and 372:
Kd-Trees about p. Say we are lookin
-
Page 373 and 374:
Numerical Problems Next: Solving Li
-
Page 375 and 376:
Numerical Problems Mon Jun 2 23:33:
-
Page 377 and 378:
Solving Linear Equations algorithm
-
Page 379 and 380:
Solving Linear Equations Matrix inv
-
Page 381 and 382:
Bandwidth Reduction images near eac
-
Page 383 and 384:
Matrix Multiplication Next: Determi
-
Page 385 and 386:
Matrix Multiplication The linear al
-
Page 387 and 388:
Determinants and Permanents Next: C
-
Page 389 and 390:
Determinants and Permanents exposit
-
Page 391 and 392:
Constrained and Unconstrained Optim
-
Page 393 and 394:
Constrained and Unconstrained Optim
-
Page 395 and 396:
Linear Programming variable assignm
-
Page 397 and 398:
Linear Programming The book [MW93]
-
Page 399 and 400:
Random Number Generation Next: Fact
-
Page 401 and 402:
Random Number Generation is largely
-
Page 403 and 404:
Random Number Generation Related Pr
-
Page 405 and 406:
Factoring and Primality Testing The
-
Page 407 and 408:
Factoring and Primality Testing Alg
-
Page 409 and 410:
Arbitrary-Precision Arithmetic If y
-
Page 411 and 412:
Arbitrary-Precision Arithmetic PARI
-
Page 413 and 414:
Knapsack Problem Next: Discrete Fou
-
Page 415 and 416:
Knapsack Problem is a subset of S'
-
Page 417 and 418:
Discrete Fourier Transform Next: Co
-
Page 419 and 420:
Discrete Fourier Transform an algor
-
Page 421 and 422:
Combinatorial Problems Next: Sortin
-
Page 423 and 424:
Sorting Next: Searching Up: Combina
-
Page 425 and 426:
Sorting The simplest approach to ex
-
Page 427 and 428:
Sorting operations, implying an sor
-
Page 429 and 430:
Searching large performance improve
-
Page 431 and 432:
Searching Notes: Mehlhorn and Tsaka
-
Page 433 and 434:
Median and Selection followed by fi
-
Page 435 and 436:
Generating Permutations Next: Gener
-
Page 437 and 438:
Generating Permutations The rank/un
-
Page 439 and 440:
Generating Permutations generating
-
Page 441 and 442:
Generating Subsets look right when
-
Page 443 and 444:
Generating Subsets above for detail
-
Page 445 and 446:
Generating Partitions Although the
-
Page 447 and 448:
Generating Partitions Two related c
-
Page 449 and 450:
Generating Graphs generate: ● Do
-
Page 451 and 452:
Generating Graphs Combinatorica [Sk
-
Page 453 and 454:
Calendrical Calculations Next: Job
-
Page 455 and 456:
Calendrical Calculations Gregorian,
-
Page 457 and 458:
Job Scheduling ● To assign a set
-
Page 459 and 460:
Job Scheduling shop scheduling incl
-
Page 461 and 462:
Satisfiability logic, and automatic
-
Page 463 and 464:
Satisfiability Next: Graph Problems
-
Page 465 and 466:
Graph Problems: Polynomial-Time rec
-
Page 467 and 468:
Connected Components Testing the co
-
Page 469 and 470:
Connected Components discussing gra
-
Page 471 and 472:
Topological Sorting contradiction t
-
Page 473 and 474:
Minimum Spanning Tree Next: Shortes
-
Page 475 and 476:
Minimum Spanning Tree help you sort
-
Page 477 and 478:
Shortest Path Next: Transitive Clos
-
Page 479 and 480:
Shortest Path easier to program tha
-
Page 481 and 482:
Shortest Path Related Problems: Net
-
Page 483 and 484:
Transitive Closure and Reduction
-
Page 485 and 486:
Transitive Closure and Reduction Al
-
Page 487 and 488:
Matching augmenting paths and stopp
-
Page 489 and 490:
Matching Combinatorica [Ski90] prov
-
Page 491 and 492:
Eulerian Cycle / Chinese Postman ar
-
Page 493 and 494:
Eulerian Cycle / Chinese Postman Ne
-
Page 495 and 496:
Edge and Vertex Connectivity Severa
-
Page 497 and 498:
Edge and Vertex Connectivity Next:
-
Page 499 and 500:
Network Flow programming model for
-
Page 501 and 502:
Network Flow Combinatorica [Ski90]
-
Page 503 and 504:
Drawing Graphs Nicely vertices are
-
Page 505 and 506:
Drawing Graphs Nicely labs.com/orgs
-
Page 507 and 508:
Drawing Trees such as the map of th
-
Page 509 and 510:
Planarity Detection and Embedding N
-
Page 511 and 512:
Planarity Detection and Embedding p
-
Page 513 and 514:
Graph Problems: Hard Problems ● C
-
Page 515 and 516:
Clique approximate even to within a
-
Page 517 and 518:
Independent Set Next: Vertex Cover
-
Page 519 and 520:
Independent Set Related Problems: C
-
Page 521 and 522:
Vertex Cover Vertex cover and indep
-
Page 523 and 524:
Traveling Salesman Problem Next: Ha
-
Page 525 and 526:
Traveling Salesman Problem practice
-
Page 527 and 528:
Traveling Salesman Problem Size is
-
Page 529 and 530:
Hamiltonian Cycle Eulerian cycle, p
-
Page 531 and 532:
Graph Partition Next: Vertex Colori
-
Page 533 and 534:
Graph Partition annealing, is almos
-
Page 535 and 536:
Vertex Coloring Several special cas
-
Page 537 and 538:
Vertex Coloring Notes: An excellent
-
Page 539 and 540:
Edge Coloring The minimum number of
-
Page 541 and 542:
Graph Isomorphism Next: Steiner Tre
-
Page 543 and 544:
Graph Isomorphism vertices into equ
-
Page 545 and 546:
Steiner Tree Next: Feedback Edge/Ve
-
Page 547 and 548:
Steiner Tree The worst case for a m
-
Page 549 and 550:
Feedback Edge/Vertex Set Next: Comp
-
Page 551 and 552:
Feedback Edge/Vertex Set An interes
-
Page 553 and 554:
Computational Geometry complete bib
-
Page 555 and 556:
Robust Geometric Primitives Next: C
-
Page 557 and 558:
Robust Geometric Primitives ● Are
-
Page 559 and 560:
Robust Geometric Primitives Related
-
Page 561 and 562:
Convex Hull ● How many dimensions
-
Page 563 and 564:
Convex Hull http://www.cs.att.com/n
-
Page 565 and 566:
Triangulation Next: Voronoi Diagram
-
Page 567 and 568:
Triangulation GEOMPACK is a suite o
-
Page 569 and 570:
Voronoi Diagrams Next: Nearest Neig
-
Page 571 and 572:
Voronoi Diagrams McDonald's, the ti
-
Page 573 and 574:
Nearest Neighbor Search Next: Range
-
Page 575 and 576:
Nearest Neighbor Search Implementat
-
Page 577 and 578:
Range Search Next: Point Location U
-
Page 579 and 580:
Range Search subdivisions in C++. I
-
Page 581 and 582:
Point Location the n edges for inte
-
Page 583 and 584:
Point Location More recently, there
-
Page 585 and 586:
Intersection Detection ● Do you w
-
Page 587 and 588:
Intersection Detection Implementati
-
Page 589 and 590:
Bin Packing Next: Medial-Axis Trans
-
Page 591 and 592:
Bin Packing approach for general sh
-
Page 593 and 594:
Medial-Axis Transformation Next: Po
-
Page 595 and 596:
Medial-Axis Transformation Implemen
-
Page 597 and 598:
Polygon Partitioning number of piec
-
Page 599 and 600:
Simplifying Polygons Next: Shape Si
-
Page 601 and 602:
Simplifying Polygons vertices and o
-
Page 603 and 604:
Shape Similarity Next: Motion Plann
-
Page 605 and 606:
Shape Similarity or how close it is
-
Page 607 and 608:
Motion Planning There is a wide ran
-
Page 609 and 610:
Motion Planning often arise in the
-
Page 611 and 612:
Maintaining Line Arrangements Think
-
Page 613 and 614:
Maintaining Line Arrangements Next:
-
Page 615 and 616:
Minkowski Sum where x+y is the vect
-
Page 617 and 618:
Set and String Problems Next: Set C
-
Page 619 and 620:
Set Cover Next: Set Packing Up: Set
-
Page 621 and 622:
Set Cover Figure: Hitting set is du
-
Page 623 and 624:
Set Packing Next: String Matching U
-
Page 625 and 626:
Set Packing Notes: An excellent exp
-
Page 627 and 628:
String Matching shouldn't try. Furt
-
Page 629 and 630:
String Matching and texts, I recomm
-
Page 631 and 632:
Approximate String Matching This sa
-
Page 633 and 634:
Approximate String Matching http://
-
Page 635 and 636:
Text Compression Next: Cryptography
-
Page 637 and 638:
Text Compression code string. ASCII
-
Page 639 and 640:
Cryptography Next: Finite State Mac
-
Page 641 and 642:
Cryptography ● How can I validate
-
Page 643 and 644:
Cryptography MD5 [Riv92] is the sec
-
Page 645 and 646:
Finite State Machine Minimization F
-
Page 647 and 648:
Finite State Machine Minimization S
-
Page 649 and 650:
Longest Common Substring than edit
-
Page 651 and 652:
Longest Common Substring include [A
-
Page 653 and 654:
Shortest Common Superstring Finding
-
Page 655 and 656:
Software systems Next: LEDA Up: Alg
-
Page 657 and 658:
LEDA Next: Netlib Up: Software syst
-
Page 659 and 660:
Netlib Algorithms Mon Jun 2 23:33:5
-
Page 661 and 662:
The Stanford GraphBase Next: Combin
-
Page 663 and 664:
Algorithm Animations with XTango Ne
-
Page 665 and 666:
Programs from Books Next: Discrete
-
Page 667 and 668:
Handbook of Data Structures and Alg
-
Page 669 and 670:
Algorithms from P to NP Next: Compu
-
Page 671 and 672:
Algorithms in C++ Next: Data Source
-
Page 673 and 674:
Textbooks Next: On-Line Resources U
-
Page 675 and 676:
On-Line Resources Next: Literature
-
Page 677 and 678:
People Next: Software Up: On-Line R
-
Page 679 and 680:
Professional Consulting Services Ne
-
Page 681 and 682:
Index A Up: Index - All Index: A ab
-
Page 683 and 684:
Index A artists steal ASA ASCII asp
-
Page 685 and 686:
Index B binary representation - sub
-
Page 687 and 688:
Index C Up: Index - All Index: C C+
-
Page 689 and 690:
Index C clustering , , co-NP coding
-
Page 691 and 692:
Index C consulting services , conta
-
Page 693 and 694:
Index D Up: Index - All Index: D DA
-
Page 695 and 696:
Index D Dictionaries dictionaries -
-
Page 697 and 698:
Index D dynamic programming - appli
-
Page 699 and 700:
Index E empirical results - heurist
-
Page 701 and 702:
Index F Up: Index - All Index: F fa
-
Page 703 and 704:
Index F frequency domain friend-or-
-
Page 705 and 706:
Index G geometric shortest path , g
-
Page 707 and 708:
Index H Up: Index - All Index: H ha
-
Page 709 and 710:
Index H Algorithms Tue Jun 3 11:59:
-
Page 711 and 712:
Index I independent set - alternate
-
Page 713 and 714:
Index J Up: Index - All Index: J ji
-
Page 715 and 716:
Index K Algorithms Tue Jun 3 11:59:
-
Page 717 and 718:
Index L linear congruential generat
-
Page 719 and 720:
Index M Up: Index - All Index: M ma
-
Page 721 and 722:
Index M mindset minima minimax sear
-
Page 723 and 724:
Index N Up: Index - All Index: N na
-
Page 725 and 726:
Index N numerical analysis numerica
-
Page 727 and 728:
Index O overlap graph overpasses -
-
Page 729 and 730:
Index P , , , , , , , , , , passwor
-
Page 731 and 732:
Index P polygons polygon triangulat
-
Page 733 and 734:
Index Q Up: Index - All Index: Q Qh
-
Page 735 and 736:
Index R ranking combinatorial objec
-
Page 737 and 738:
Index S Up: Index - All Index: S s-
-
Page 739 and 740:
Index S Shape Similarity shape simp
-
Page 741 and 742:
Index S solar year Solving Linear E
-
Page 743 and 744:
Index S straight-line graph drawing
-
Page 745 and 746:
Index T Up: Index - All Index: T ta
-
Page 747 and 748:
Index T trees - matching trees - pa
-
Page 749 and 750:
Index V Up: Index - All Index: V va
-
Page 751 and 752:
Index W Up: Index - All Index: W wa
-
Page 753 and 754:
Index Y Up: Index - All Index: Y Yo
-
Page 755 and 756:
Index (complete) Up: Index - All In
-
Page 757 and 758:
Index (complete) arm, robot around
-
Page 759 and 760:
Index (complete) binary search tree
-
Page 761 and 762:
Index (complete) center vertex, , C
-
Page 763 and 764:
Index (complete) compaction compari
-
Page 765 and 766:
Index (complete) counting paths, co
-
Page 767 and 768:
Index (complete) deletion from bina
-
Page 769 and 770:
Index (complete) dominance ordering
-
Page 771 and 772:
Index (complete) English to French
-
Page 773 and 774:
Index (complete) file directory tre
-
Page 775 and 776:
Index (complete) geom.bib, geometri
-
Page 777 and 778:
Index (complete) Hamiltonian Cycle
-
Page 779 and 780:
Index (complete) implementation cha
-
Page 781 and 782:
Index (complete) job-shop schedulin
-
Page 783 and 784:
Index (complete) linear programming
-
Page 785 and 786:
Index (complete) , , , , , , , math
-
Page 787 and 788:
Index (complete) modular arithmetic
-
Page 789 and 790:
Index (complete) normal distributio
-
Page 791 and 792:
Index (complete) parallel algorithm
-
Page 793 and 794:
Index (complete) planar subdivision
-
Page 795 and 796:
Index (complete) proof of correctne
-
Page 797 and 798:
Index (complete) regular expression
-
Page 799 and 800:
Index (complete) self-organizing tr
-
Page 801 and 802:
Index (complete) sine functions sin
-
Page 803 and 804:
Index (complete) spring embedding h
-
Page 805 and 806:
Index (complete) Symbol Technologie
-
Page 807 and 808:
Index (complete) trial division Tri
-
Page 809 and 810:
Index (complete) VLSI circuit layou
-
Page 811 and 812:
1.4.4 Shortest Path 1.4.4 Shortest
-
Page 813 and 814:
1.2.5 Constrained and Unconstrained
-
Page 815 and 816:
1.6.4 Voronoi Diagrams 1.6.4 Vorono
-
Page 817 and 818:
1.4.7 Eulerian Cycle / Chinese Post
-
Page 819 and 820:
Online Bibliographies Online Biblio
-
Page 821 and 822:
About the Book -- The Algorithm Des
-
Page 823 and 824:
Copyright and Disclaimers Copyright
-
Page 825 and 826:
CD-ROM Installation Installation an
-
Page 827 and 828:
CD-ROM Installation install a sound
-
Page 829 and 830:
Thanks! Frank Ruscica file:///E|/WE
-
Page 831 and 832:
Thanks! Zhong Li Thanks also to Fil
-
Page 833 and 834:
CD-ROM Installation To use the CD-R
-
Page 835 and 836:
Binary Search in Action Binary Sear
-
Page 837 and 838:
Binary Search in Action file:///E|/
-
Page 839 and 840:
Binary Search in Action file:///E|/
-
Page 841 and 842:
Postscript version of the lecture n
-
Page 843 and 844:
Lecture 1 - analyzing algorithms Ne
-
Page 845 and 846:
Lecture 1 - analyzing algorithms Yo
-
Page 847 and 848:
Lecture 1 - analyzing algorithms Th
-
Page 849 and 850:
Lecture 1 - analyzing algorithms Th
-
Page 851 and 852:
Lecture 1 - analyzing algorithms is
-
Page 853 and 854:
Lecture 2 - asymptotic notation How
-
Page 855 and 856:
Lecture 2 - asymptotic notation Not
-
Page 857 and 858:
Lecture 2 - asymptotic notation alg
-
Page 859 and 860:
Lecture 2 - asymptotic notation Sup
-
Page 861 and 862:
Lecture 2 - asymptotic notation Nex
-
Page 863 and 864:
Lecture 3 - recurrence relations Is
-
Page 865 and 866:
Lecture 3 - recurrence relations
-
Page 867 and 868:
Lecture 3 - recurrence relations Li
-
Page 869 and 870:
Lecture 3 - recurrence relations Su
-
Page 871 and 872:
Lecture 3 - recurrence relations A
-
Page 873 and 874:
Lecture 4 - heapsort Note iteration
-
Page 875 and 876:
Lecture 4 - heapsort The convex hul
-
Page 877 and 878:
Lecture 4 - heapsort 1. All leaves
-
Page 879 and 880:
Lecture 4 - heapsort left = 2i righ
-
Page 881 and 882:
Lecture 4 - heapsort Since this sum
-
Page 883 and 884:
Lecture 4 - heapsort Selection sort
-
Page 885 and 886:
Lecture 4 - heapsort Greedy Algorit
-
Page 887 and 888:
Lecture 5 - quicksort Partitioning
-
Page 889 and 890:
Lecture 5 - quicksort Listen To Par
-
Page 891 and 892:
Lecture 5 - quicksort Listen To Par
-
Page 893 and 894:
Lecture 5 - quicksort The worst cas
-
Page 895 and 896:
Lecture 5 - quicksort Mon Jun 2 09:
-
Page 897 and 898:
Lecture 6 - linear sorting Since 2i
-
Page 899 and 900:
Lecture 6 - linear sorting With uni
-
Page 901 and 902:
Lecture 6 - linear sorting Listen T
-
Page 903 and 904:
Lecture 7 - elementary data structu
-
Page 905 and 906:
Lecture 7 - elementary data structu
-
Page 907 and 908:
Lecture 7 - elementary data structu
-
Page 909 and 910:
Lecture 7 - elementary data structu
-
Page 911 and 912:
Lecture 7 - elementary data structu
-
Page 913 and 914:
Lecture 7 - elementary data structu
-
Page 915 and 916:
Lecture 7 - elementary data structu
-
Page 917 and 918:
Lecture 8 - binary trees - Joyce Ki
-
Page 919 and 920:
Lecture 8 - binary trees TREE-MINIM
-
Page 921 and 922:
Lecture 8 - binary trees Inorder-Tr
-
Page 923 and 924:
Lecture 8 - binary trees Listen To
-
Page 925 and 926:
Lecture 8 - binary trees insert(b)
-
Page 927 and 928:
Lecture 8 - binary trees Not (1) -
-
Page 929 and 930:
Lecture 9 - catch up Next: Lecture
-
Page 931 and 932:
Lecture 10 - tree restructuring 1.
-
Page 933 and 934:
Lecture 10 - tree restructuring Lis
-
Page 935 and 936:
Lecture 10 - tree restructuring Not
-
Page 937 and 938:
Lecture 10 - tree restructuring Cas
-
Page 939 and 940:
Lecture 11 - backtracking Next: Lec
-
Page 941 and 942:
Lecture 11 - backtracking Only 63 s
-
Page 943 and 944:
Lecture 11 - backtracking Recursion
-
Page 945 and 946:
Lecture 11 - backtracking Specifica
-
Page 947 and 948:
Lecture 12 - introduction to dynami
-
Page 949 and 950:
Lecture 12 - introduction to dynami
-
Page 951 and 952:
Lecture 12 - introduction to dynami
-
Page 953 and 954:
Lecture 12 - introduction to dynami
-
Page 955 and 956:
Lecture 12 - introduction to dynami
-
Page 957 and 958:
Lecture 13 - dynamic programming ap
-
Page 959 and 960:
Lecture 13 - dynamic programming ap
-
Page 961 and 962:
Lecture 13 - dynamic programming ap
-
Page 963 and 964:
Lecture 14 - data structures for gr
-
Page 965 and 966:
Lecture 14 - data structures for gr
-
Page 967 and 968:
Lecture 14 - data structures for gr
-
Page 969 and 970:
Lecture 14 - data structures for gr
-
Page 971 and 972:
Lecture 14 - data structures for gr
-
Page 973 and 974:
Lecture 14 - data structures for gr
-
Page 975 and 976:
Lecture 15 - DFS and BFS Next: Lect
-
Page 977 and 978:
Lecture 15 - DFS and BFS In a DFS o
-
Page 979 and 980:
Lecture 15 - DFS and BFS It could u
-
Page 981 and 982:
Lecture 15 - DFS and BFS Algorithm
-
Page 983 and 984:
Lecture 16 - applications of DFS an
-
Page 985 and 986:
Lecture 16 - applications of DFS an
-
Page 987 and 988:
Lecture 16 - applications of DFS an
-
Page 989 and 990:
Lecture 17 - minimum spanning trees
-
Page 991 and 992:
Lecture 17 - minimum spanning trees
-
Page 993 and 994:
Lecture 17 - minimum spanning trees
-
Page 995 and 996:
Lecture 17 - minimum spanning trees
-
Page 997 and 998:
Lecture 17 - minimum spanning trees
-
Page 999 and 1000:
Lecture 18 - shortest path algorthm
-
Page 1001 and 1002:
Lecture 18 - shortest path algorthm
-
Page 1003 and 1004:
Lecture 18 - shortest path algorthm
-
Page 1005 and 1006:
Lecture 18 - shortest path algorthm
-
Page 1007 and 1008:
Lecture 18 - shortest path algorthm
-
Page 1009 and 1010:
Lecture 19 - satisfiability Next: L
-
Page 1011 and 1012:
Lecture 19 - satisfiability Why? Th
-
Page 1013 and 1014:
Lecture 19 - satisfiability between
-
Page 1015 and 1016:
Lecture 19 - satisfiability Note th
-
Page 1017 and 1018:
Lecture 20 - integer programming Ex
-
Page 1019 and 1020:
Lecture 20 - integer programming Ne
-
Page 1021 and 1022:
Lecture 21 - vertex cover Proof: VC
-
Page 1023 and 1024:
Lecture 21 - vertex cover Question:
-
Page 1025 and 1026:
Lecture 21 - vertex cover seen to d
-
Page 1027 and 1028:
Lecture 22 - techniques for proving
-
Page 1029 and 1030:
Lecture 22 - techniques for proving
-
Page 1031 and 1032:
Lecture 22 - techniques for proving
-
Page 1033 and 1034:
Lecture 22 - techniques for proving
-
Page 1035 and 1036:
Lecture 23 - approximation algorith
-
Page 1037 and 1038:
Lecture 23 - approximation algorith
-
Page 1039 and 1040:
Lecture 23 - approximation algorith
-
Page 1041 and 1042:
Lecture 23 - approximation algorith
-
Page 1043 and 1044:
Lecture 23 - approximation algorith
-
Page 1045 and 1046:
About this document ... Up: No Titl
-
Page 1047 and 1048:
1.1.6 Kd-Trees ● Point Location
-
Page 1049 and 1050:
1.1.3 Suffix Trees and Arrays Send
-
Page 1051 and 1052:
1.5.1 Clique ● Vertex Cover Go to
-
Page 1053 and 1054:
1.6.2 Convex Hull Related Problems
-
Page 1055 and 1056:
Visual Links Index file:///E|/WEBSI
-
Page 1057 and 1058:
Visual Links Index file:///E|/WEBSI
-
Page 1059 and 1060:
Visual Links Index file:///E|/WEBSI
-
Page 1061 and 1062:
Visual Links Index file:///E|/WEBSI
-
Page 1063 and 1064:
Visual Links Index file:///E|/WEBSI
-
Page 1065 and 1066:
Visual Links Index file:///E|/WEBSI
-
Page 1067 and 1068:
Visual Links Index file:///E|/WEBSI
-
Page 1069 and 1070:
Visual Links Index file:///E|/WEBSI
-
Page 1071 and 1072:
Visual Links Index file:///E|/WEBSI
-
Page 1073 and 1074:
Visual Links Index file:///E|/WEBSI
-
Page 1075 and 1076:
Visual Links Index file:///E|/WEBSI
-
Page 1077 and 1078:
Visual Links Index file:///E|/WEBSI
-
Page 1079 and 1080:
Visual Links Index file:///E|/WEBSI
-
Page 1081 and 1082:
Visual Links Index file:///E|/WEBSI
-
Page 1083 and 1084:
About the Ratings About the Ratings
-
Page 1085 and 1086:
1.2 Numerical Problems 1.2 Numerica
-
Page 1087 and 1088:
1.4 Graph Problems -- polynomial-ti
-
Page 1089 and 1090:
1.6 Computational Geometry 1.6 Comp
-
Page 1091 and 1092:
C++ Language Implementations Algori
-
Page 1093 and 1094:
C Language Implementations ● POSI
-
Page 1095 and 1096:
FORTRAN Language Implementations Al
-
Page 1097 and 1098:
Lisp Language Implementations Algor
-
Page 1099 and 1100:
Algorithm Repository -- Citations C
-
Page 1101 and 1102:
Practical Algorithm Design -- User
-
Page 1103 and 1104:
LEDA - A Library of Efficient Data
-
Page 1105 and 1106:
Discrete Optimization Methods Discr
-
Page 1107 and 1108:
Netlib / TOMS -- Collected Algorith
-
Page 1109 and 1110:
Netlib / TOMS -- Collected Algorith
-
Page 1111 and 1112:
Xtango and Polka Algorithm Animatio
-
Page 1113 and 1114:
Combinatorica Combinatorica Combina
-
Page 1115 and 1116:
file:///E|/WEBSITE/IMPLEMEN/GRAPHBA
-
Page 1117 and 1118:
1.4.1 Connected Components 1.4.1 Co
-
Page 1119 and 1120:
1.5.9 Graph Isomorphism 1.5.9 Graph
-
Page 1121 and 1122:
1.2.3 Matrix Multiplication 1.2.3 M
-
Page 1123 and 1124:
1.6.14 Motion Planning 1.6.14 Motio
-
Page 1125 and 1126:
1.4.9 Network Flow 1.4.9 Network Fl
-
Page 1127 and 1128:
1.1.2 Priority Queues 1.1.2 Priorit
-
Page 1129 and 1130:
1.5.10 Steiner Tree 1.5.10 Steiner
-
Page 1131 and 1132:
1.4.5 Transitive Closure and Reduct
-
Page 1133 and 1134:
About the Book -- The Algorithm Des
-
Page 1135 and 1136:
About the Book -- The Algorithm Des
-
Page 1137 and 1138:
Genocop -- Optimization via Genetic
-
Page 1139 and 1140:
1.2.6 Linear Programming ● Knapsa
-
Page 1141 and 1142:
1.2.7 Random Number Generation ●
-
Page 1143 and 1144:
1.3.10 Satisfiability ● Constrain
-
Page 1145 and 1146:
Qhull - higher dimensional convex h
-
Page 1147 and 1148:
1.6.5 Nearest Neighbor Search 1.6.5
-
Page 1149 and 1150:
1.6.7 Point Location 1.6.7 Point Lo
-
Page 1151 and 1152:
1.6.10 Medial-Axis Transformation 1
-
Page 1153 and 1154:
1.6.3 Triangulation 1.6.3 Triangula
-
Page 1155 and 1156:
Nijenhuis and Wilf: Combinatorial A
-
Page 1157 and 1158:
1.5.5 Hamiltonian Cycle 1.5.5 Hamil
-
Page 1159 and 1160:
1.4.6 Matching 1.4.6 Matching INPUT
-
Page 1161 and 1162:
A compendium of NP optimization pro
-
Page 1163 and 1164:
1.6.9 Bin Packing 1.6.9 Bin Packing
-
Page 1165 and 1166:
1.6.12 Simplifying Polygons 1.6.12
-
Page 1167 and 1168:
1.6.13 Shape Similarity 1.6.13 Shap
-
Page 1169 and 1170:
1.6.11 Polygon Partitioning 1.6.11
-
Page 1171 and 1172:
1.4.3 Minimum Spanning Tree 1.4.3 M
-
Page 1173 and 1174:
1.6.15 Maintaining Line Arrangement
-
Page 1175 and 1176:
1.3.7 Generating Graphs 1.3.7 Gener
-
Page 1177 and 1178:
1.2.11 Discrete Fourier Transform 1
-
Page 1179 and 1180:
1.5.8 Edge Coloring 1.5.8 Edge Colo
-
Page 1181 and 1182:
1.3.3 Median and Selection 1.3.3 Me
-
Page 1183 and 1184:
1.3.1 Sorting 1.3.1 Sorting INPUT O
-
Page 1185 and 1186:
Plugins for use with the CDROM Plug
-
Page 1187 and 1188:
Implementation Challenges Next: Dat
-
Page 1189 and 1190:
Implementation Challenges Next: Gra
-
Page 1191 and 1192:
Implementation Challenges Next: Int
-
Page 1193 and 1194:
Caveats Next: Data Structures Up: A
-
Page 1195 and 1196:
1.1.1 Dictionaries ● Priority Que
-
Page 1197 and 1198:
1.1.4 Graph Data Structures ● Gra
-
Page 1199 and 1200:
1.1.5 Set Data Structures ● Gener
-
Page 1201 and 1202:
1.2.1 Solving Linear Equations ●
-
Page 1203 and 1204:
1.2.2 Bandwidth Reduction ● Topol
-
Page 1205 and 1206:
1.2.4 Determinants and Permanents
-
Page 1207 and 1208:
1.2.8 Factoring and Primality Testi
-
Page 1209 and 1210:
1.2.9 Arbitrary Precision Arithmeti
-
Page 1211 and 1212:
1.2.10 Knapsack Problem ● Linear
-
Page 1213 and 1214:
1.3.2 Searching ● Sorting Go to t
-
Page 1215 and 1216:
1.3.4 Generating Permutations ● C
-
Page 1217 and 1218:
1.3.5 Generating Subsets ● Genera
-
Page 1219 and 1220:
1.3.6 Generating Partitions ● Gen
-
Page 1221 and 1222:
1.3.8 Calendrical Calculations Go t
-
Page 1223 and 1224:
1.3.9 Job Scheduling ● Feedback E
-
Page 1225 and 1226:
1.4.2 Topological Sorting Related P
-
Page 1227 and 1228:
1.4.8 Edge and Vertex Connectivity
-
Page 1229 and 1230:
1.4.10 Drawing Graphs Nicely ● Pl
-
Page 1231 and 1232:
1.4.11 Drawing Trees ● Planarity
-
Page 1233 and 1234:
1.4.12 Planarity Detection and Embe
-
Page 1235 and 1236:
1.5.2 Independent Set ● Vertex Co
-
Page 1237 and 1238:
1.5.3 Vertex Cover ● Independent
-
Page 1239 and 1240:
1.5.4 Traveling Salesman Problem
-
Page 1241 and 1242:
1.5.6 Graph Partition ● Network F
-
Page 1243 and 1244:
1.5.7 Vertex Coloring Related Probl
-
Page 1245 and 1246:
1.5.11 Feedback Edge/Vertex Set Go
-
Page 1247 and 1248:
1.6.1 Robust Geometric Primitives G
-
Page 1249 and 1250:
1.6.6 Range Search ● Kd-Trees ●
-
Page 1251 and 1252:
1.6.8 Intersection Detection ● Ro
-
Page 1253 and 1254:
1.6.16 Minkowski Sum Go to the corr
-
Page 1255 and 1256:
1.7.1 Set Cover ● Set Packing ●
-
Page 1257 and 1258:
1.7.2 Set Packing Go to the corresp
-
Page 1259 and 1260:
1.7.3 String Matching ● Approxima
-
Page 1261 and 1262:
1.7.4 Approximate String Matching
-
Page 1263 and 1264:
1.7.5 Text Compression Go to the co
-
Page 1265 and 1266:
1.7.6 Cryptography ● Text Compres
-
Page 1267 and 1268:
1.7.7 Finite State Machine Minimiza
-
Page 1269 and 1270:
1.7.8 Longest Common Substring ●
-
Page 1271 and 1272:
1.7.9 Shortest Common Superstring G
-
Page 1273 and 1274:
Handbook of Algorithms and Data Str
-
Page 1275 and 1276:
Moret and Shapiro's Algorithms P to
-
Page 1277 and 1278:
Index B Up: Index - All Index: B ba
-
Page 1279 and 1280:
Index C Up: Index - All Index: C ch
-
Page 1281 and 1282:
Index E Up: Index - All Index: E ed
-
Page 1283 and 1284:
Index G Up: Index - All Index: G ga
-
Page 1285 and 1286:
Index I Up: Index - All Index: I in
-
Page 1287 and 1288:
Index L Up: Index - All Index: L li
-
Page 1289 and 1290:
Index N Up: Index - All Index: N ne
-
Page 1291 and 1292:
Index P Up: Index - All Index: P pa
-
Page 1293 and 1294:
Index R Up: Index - All Index: R RA
-
Page 1295 and 1296:
Index S successor supercomputer , s
-
Page 1297 and 1298:
Index U Up: Index - All Index: U un
-
Page 1299 and 1300:
Index W Up: Index - All Index: W wo
-
Page 1301 and 1302:
Index (complete) bin packing bipart
-
Page 1303 and 1304:
Index (complete) Fourier transform
-
Page 1305 and 1306:
Index (complete) parenthesization p
-
Page 1307 and 1308:
Index (complete) symmetry, exploiti
-
Page 1309 and 1310:
Ranger - Nearest Neighbor Search in
-
Page 1311 and 1312:
DIMACS Implementation Challenges Pe
-
Page 1313 and 1314:
Stony Brook Project Implementations
-
Page 1315 and 1316:
Clarkson's higher dimensional conve
-
Page 1317 and 1318:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1319 and 1320:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1321 and 1322:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1323 and 1324:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1325 and 1326:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1327 and 1328:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1329 and 1330:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1331 and 1332:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1333 and 1334:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1335 and 1336:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1337 and 1338:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1339 and 1340:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1341 and 1342:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1343 and 1344:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1345 and 1346:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1347 and 1348:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1349 and 1350:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1351 and 1352:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1353 and 1354:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1355 and 1356:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1357 and 1358:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1359 and 1360:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1361 and 1362:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1363 and 1364:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1365 and 1366:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1367 and 1368:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1369 and 1370:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1371 and 1372:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1373 and 1374:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1375 and 1376:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1377 and 1378:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1379 and 1380:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1381 and 1382:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1383 and 1384:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1385 and 1386:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1387 and 1388:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1389 and 1390:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1391 and 1392:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1393 and 1394:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1395 and 1396:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1397 and 1398:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1399 and 1400:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1401 and 1402:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1403:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1407 and 1408:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1409 and 1410:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1411 and 1412:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1413 and 1414:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1415 and 1416:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1417 and 1418:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1419 and 1420:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1421 and 1422:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1423 and 1424:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1425 and 1426:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1427 and 1428:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1429 and 1430:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1431 and 1432:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1433 and 1434:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1435 and 1436:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1437 and 1438:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1439 and 1440:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1441 and 1442:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1443 and 1444:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1445 and 1446:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
-
Page 1447 and 1448:
SimPack/Sim++ Simulation Toolkit Si
-
Page 1449 and 1450:
Fire-Engine and Spare-Parts String
-
Page 1451 and 1452:
Geolab -- Computational Geometry Sy
-
Page 1453 and 1454:
Calendrical Calculations Calendrica
-
Page 1455 and 1456:
David Eppstein's Knuth-Morris-Pratt
-
Page 1457 and 1458:
Mike Trick's Graph Coloring Resourc
-
Page 1459 and 1460:
Frank Ruskey's Combinatorial Genera
-
Page 1461 and 1462:
Arrange - maintainance of arrangeme
-
Page 1463 and 1464:
LP_SOLVE: Linear Programming Code L
-
Page 1465 and 1466:
PARI - Package for Number Theory Se
-
Page 1467 and 1468:
TSP solvers TSP solvers tsp-solve i
-
Page 1469 and 1470:
PHYLIP -- inferring phylogenic tree
-
Page 1471 and 1472:
Skeletonization Software (2-D) Skel
-
Page 1473 and 1474:
agrep - Approximate General Regular
-
Page 1475 and 1476:
CAP -- Contig Assembly Program CAP
-
Page 1477 and 1478:
NAUTY -- Graph Isomorphism NAUTY --
-
Page 1479 and 1480:
BIPM -- Bipartite Matching Codes BI
-
Page 1481 and 1482:
LAPACK and LINPACK -- Linear Algebr
-
Page 1483 and 1484:
User Comments User Comments Archive
-
Page 1485 and 1486:
The Algorithm Design Manual Most pr
-
Page 1487 and 1488:
The Algorithm Design Manual 5.6 War
Change language