clanek_go_congress/clanek.bib

   1 % Encoding: UTF-8
   2
   3 @ONLINE{GoAncientChina,
   4   author = "John Fairbairn",
   5   year = "1995",
   6   title = "Go in Ancient China",
   7   url = "http://www.pandanet.co.jp/English/essay/goancientchina.html",
   8   cited = "15.\,1.\,2013",
   9   owner = "jm"
  10 }
  11
  12 @MastersThesis{Moudrik13,
  13   author   = "Josef Moud{\v{r}\'{i}}k",
  14   title    = "Meta-learning methods for analyzing Go playing trends",
  15   school   = "Charles University, Faculty of Mathematics and Physics",
  16   address  = "Prague, Czech Republic",
  17   year     = "2013",
  18 }
  19
  20 @ONLINE{GoAncientChina,
  21   author = "John Fairbairn",
  22   year = "1995",
  23   title = "Go in Ancient China",
  24   url = "http://www.pandanet.co.jp/English/essay/goancientchina.html",
  25   cited = "15.\,1.\,2013",
  26   owner = "jm"
  27 }
  28
  29 @ONLINE{ wiki:Go,
  30    author = "Wikipedia",
  31    title = "Go (game) --- Wikipedia{,} The Free Encyclopedia",
  32    year = "2013",
  33    url = "http://en.wikipedia.org/w/index.php?title=Go_(game)\&oldid=532253814",
  34    cited = "15.\,1.\,2013"
  35 }
  36
  37 @ONLINE{ wiki:go_handi,
  38    author = "Wikipedia",
  39    title = "Go handicaps --- Wikipedia{,} The Free Encyclopedia",
  40    year = "2012",
  41    url = "http://en.wikipedia.org/w/index.php?title=Go_handicaps&oldid=505279363",
  42    cited = "16.\,1.\,2013"
  43 }
  44
  45 @ONLINE{ wiki:go_rank,
  46    author = "Wikipedia",
  47    title = "Go ranks and ratings --- Wikipedia{,} The Free Encyclopedia",
  48    year = "2012",
  49    url = "http://en.wikipedia.org/w/index.php?title=Go_ranks_and_ratings&oldid=522963011",
  50    cited = "18.\,1.\,2013"
  51 }
  52
  53 @ARTICLE{ieee:mcts_overview,
  54 author={Browne, C.B. and Powley, E. and Whitehouse, D. and Lucas, S.M. and Cowling, P.I. and Rohlfshagen, P. and Tavener, S. and Perez, D. and Samothrakis, S. and Colton, S.},
  55 journal={Computational Intelligence and AI in Games, IEEE Transactions on},
  56 title={A Survey of Monte Carlo Tree Search Methods},
  57 year={2012},
  58 month={march },
  59 volume={4},
  60 number={1},
  61 pages={1 -43},
  62 keywords={Artificial intelligence;Computers;Decision theory;Game theory;Games;Markov processes;Monte Carlo methods;Monte Carlo methods;game theory;tree searching;MCTS research;Monte carlo tree search methods;computer Go;key game;nongame domains;random sampling generality;Artificial intelligence (AI);Monte Carlo tree search (MCTS);bandit-based methods;computer Go;game search;upper confidence bounds (UCB);upper confidence bounds for trees (UCT);},
  63 doi={10.1109/TCIAIG.2012.2186810},
  64 ISSN={1943-068X},
  65    url = "http://www.doc.ic.ac.uk/~sgc/papers/browne_ieee12.pdf",
  66
  67 }
  68
  69 @ONLINE{ wiki:computer_go,
  70    author = "Wikipedia",
  71    title = "Computer Go --- Wikipedia{,} The Free Encyclopedia",
  72    year = "2013",
  73    url = "http://en.wikipedia.org/w/index.php?title=Computer_Go&oldid=530803356",
  74    cited = "17.\,1.\,2013"
  75 }
  76
  77
  78 @ONLINE{ senseis:which_pro,
  79    author = "{Sensei's Library}",
  80    title = "Which Pro Do You Most Play Like",
  81    url = "http://senseis.xmp.net/?WhichProDoYouMostPlayLike",
  82    year = "2013",
  83    cited = "8.\,4.\,2013"
  84 }
  85
  86 @ONLINE{ senseis:33,
  87    author = "{Sensei's Library}",
  88    title = "4-4 point low approach one-space low pincer",
  89    url = "http://senseis.xmp.net/?44PointLowApproachOneSpaceLowPincer",
  90    year = "2013",
  91    cited = "29.\,3.\,2013"
  92 }
  93
  94 @ONLINE{ senseis:empty_triangle,
  95    author = "{Sensei's Library}",
  96    title = "The empty triangle is bad",
  97    url = "http://senseis.xmp.net/?TheEmptyTriangleIsBad",
  98    year = "2013",
  99    cited = "18.\,3.\,2013"
 100 }
 101
 102 @ONLINE{ senseis:styles,
 103    author = "{Sensei's Library}",
 104    title = "Professional Players' Go Styles",
 105    url = "http://senseis.xmp.net/?ProfessionalPlayersGoStyles",
 106    year = "2013",
 107    cited = "12.\,3.\,2013"
 108 }
 109 @ONLINE{ senseis:rank_cmp,
 110    author = "{Sensei's Library}",
 111    title = "Rank - worldwide comparison",
 112    url = "http://senseis.xmp.net/?RankWorldwideComparison",
 113    year = "2013",
 114    cited = "16.\,1.\,2013"
 115 }
 116 @ONLINE{ senseis:proverbs,
 117    author = "{Sensei's Library}",
 118    title = "Go Proverbs",
 119    url = "http://senseis.xmp.net/?GoProverbs",
 120    year = "2013",
 121    cited = "18.\,2.\,2013"
 122 }
 123
 124 @ONLINE{ senseis:tutorial,
 125    author = "{Sensei's Library}",
 126    title = "Rules of Go - introductory",
 127    url = "http://senseis.xmp.net/?BasicRulesOfGo",
 128    year = "2013",
 129    cited = "15.\,1.\,2013"
 130 }
 131 @ONLINE{ senseis:scoring,
 132    author = "{Sensei's Library}",
 133    title = "Scoring",
 134    url = "http://senseis.xmp.net/?Scoring",
 135    year = "2013",
 136    cited = "16.\,1.\,2013"
 137 }
 138 @ONLINE{ senseis:seki,
 139    author = "{Sensei's Library}",
 140    title = "Seki",
 141    url = "http://senseis.xmp.net/?Seki",
 142    year = "2013",
 143    cited = "16.\,1.\,2013"
 144 }
 145 @ONLINE{ senseis:dan,
 146    author = "{Sensei's Library}",
 147    title = "Dan",
 148    url = "http://senseis.xmp.net/?Dan",
 149    year = "2013",
 150    cited = "8.\,2.\,2013"
 151 }
 152 @ONLINE{ senseis:rules,
 153    author = "{Sensei's Library}",
 154    title = "Rules of Go",
 155    url = "http://senseis.xmp.net/?RulesOfGo",
 156    year = "2013",
 157    cited = "16.\,1.\,2013"
 158 }
 159 @ONLINE{ senseis,
 160    author = "{Sensei's Library}",
 161    title = "Sensei's Library",
 162    year = "2013",
 163    url = "http://senseis.xmp.net/",
 164    cited = "15.\,1.\,2013"
 165 }
 166
 167 @ONLINE{ computer_go,
 168    author = "Nick Wedd",
 169    title = "Computer Go Info --- Human-Computer Go Challenges",
 170    year = "2013",
 171    url = "http://www.computer-go.info/h-c/index.html",
 172    cited = "8.\,2.\,2013"
 173 }
 174
 175 @ONLINE{ est_go,
 176    author = "{Go Census}",
 177    title = "",
 178    year = "2002",
 179    url = "http://web.archive.org/web/20021217041220/http://www.fin.ne.jp/~igo/census.htm",
 180    cited = "10.\,2.\,2013"
 181 }
 182
 183 @conference{ van_ees,
 184    author = "Theo van Ees",
 185    title = "The Slow Way West",
 186    booktitle = "Third International Conference on Baduk",
 187    address = "Myong-Ji University, Yongin City, Korea",
 188    month = "October",
 189    year = "2005",
 190    note = "Available as a part of the {GoGoD} {E}ncyclopaedia and {D}atabase, {H}istory",
 191    url = "http://www.gogod.co.uk/",
 192    cited = "8.\,2.\,2013"
 193 }
 194
 195 @article{vapnik95,
 196   author    = "Corinna Cortes and
 197                Vladimir Vapnik",
 198   title     = "Support-Vector Networks",
 199   journal   = "Machine Learning",
 200   volume    = "20",
 201   number    = "3",
 202   year      = "1995",
 203   pages     = "273-297",
 204   doi       = "10.1007/BF00994018",
 205 }
 206
 207
 208 @article{breiman96,
 209 year={1996},
 210 issn={0885-6125},
 211 journal={Machine Learning},
 212 volume={24},
 213 issue={1},
 214 doi={10.1007/BF00117832},
 215 title={Stacked regressions},
 216 url={http://dx.doi.org/10.1007/BF00117832},
 217 publisher={Kluwer Academic Publishers},
 218 keywords={Stacking; Non-negativity; Trees; Subset regression; Combinations},
 219 author={Breiman, Leo},
 220 pages={49-64},
 221 language={English}
 222 }
 223
 224 @ARTICLE{wolpert92,
 225     author = {David H. Wolpert},
 226     title = {Stacked Generalization},
 227     journal = {Neural Networks},
 228     year = {1992},
 229     volume = {5},
 230     pages = {241--259},
 231     url = "http://www.machine-learning.martinsewell.com/ensembles/stacking/Wolpert1992.pdf"
 232 }
 233
 234 @inproceedings{boosting,
 235 year={1995},
 236 isbn={978-3-540-59119-1},
 237 booktitle={Computational Learning Theory},
 238 volume={904},
 239 series={Lecture Notes in Computer Science},
 240 doi={10.1007/3-540-59119-2_166},
 241 title={A desicion-theoretic generalization of on-line learning and an application to boosting},
 242 url={http://dx.doi.org/10.1007/3-540-59119-2_166},
 243 publisher={Springer Berlin Heidelberg},
 244 author={Freund, Yoav and Schapire, RobertE.},
 245 pages={23-37}
 246 }
 247
 248
 249 @article{whitley94,
 250   title={A genetic algorithm tutorial},
 251   author={Whitley, D.},
 252   journal={Statistics and computing},
 253   volume={4},
 254   number={2},
 255   pages={65--85},
 256   year={1994},
 257   publisher={Springer}
 258 }
 259
 260 @book{ breiman84,
 261     author = "Breiman, Leo and Friedman, J. H. and Olshen R. A. and Stone, C. J.",
 262     year = "1984",
 263     title= "Classification and regression trees",
 264     address = "Monterey, CA",
 265     publisher = "Wadsworth \& Brooks/Cole Advanced Books \& Software",
 266     isbn = "978-0-412-04841-8"
 267 }
 268
 269 @article{breimanbag96,
 270  author = {Breiman, Leo},
 271  title = {Bagging predictors},
 272  journal = {Mach. Learn.},
 273  issue_date = {Aug. 1996},
 274  volume = {24},
 275  number = {2},
 276  month = aug,
 277  year = {1996},
 278  issn = {0885-6125},
 279  pages = {123--140},
 280  numpages = {18},
 281  url = {http://dx.doi.org/10.1023/A:1018054314350},
 282  doi = {10.1023/A:1018054314350},
 283  acmid = {231989},
 284  publisher = {Kluwer Academic Publishers},
 285  address = {Hingham, MA, USA},
 286  keywords = {aggregation, averaging, bootstrap, combining},
 287 }
 288
 289 @article{breiman01,
 290  author = "Breiman, Leo",
 291  title = "Random Forests",
 292  journal = "Machine Learning",
 293  issue_date = "October 1 2001",
 294  volume = "45",
 295  number = "1",
 296  month = oct,
 297  year = "2001",
 298  issn = "0885-6125",
 299  pages = "5--32",
 300  numpages = "28",
 301  doi = "10.1023/A:1010933404324",
 302  acmid = "570182",
 303  publisher = "Kluwer Academic Publishers",
 304  address = "Hingham, MA, USA",
 305  keywords = "classification, ensemble, regression",
 306 }
 307
 308 @article{smola04,
 309  author = "Smola, Alex J. and Sch{\"{o}}lkopf, Bernhard",
 310  title = "A tutorial on support vector regression",
 311  journal = "Statistics and Computing",
 312  issue_date = "August 2004",
 313  volume = "14",
 314  number = "3",
 315  month = "aug",
 316  year = "2004",
 317  issn = "0960-3174",
 318  pages = "199--222",
 319  numpages = "24",
 320  url = "http://www.cmlab.csie.ntu.edu.tw/~cyy/learning/papers/SVR_Tutorial.pdf",
 321  doi = "10.1023/B:STCO.0000035301.49549.88",
 322  acmid = "1011939",
 323  publisher = "Kluwer Academic Publishers",
 324  address = "Hingham, MA, USA",
 325  keywords = "machine learning, regression estimation, support vector machines"
 326 }
 327
 328 @ONLINE{GoGoD,
 329   author = "Hall, T. Mark and Fairbairn, John",
 330   year = "winter 2011",
 331   title = "{G}ames of {G}o on {D}isk --- {GoGoD} {E}ncyclopaedia and {D}atabase",
 332   url = "http://www.gogod.co.uk/",
 333   owner = "jm"
 334 }
 335
 336 @ONLINE{GoGoD:styles,
 337   author = "Fairbairn, John",
 338   year = "winter 2011",
 339   title = "{G}ames of {G}o on {D}isk --- {GoGoD} {E}ncyclopaedia and {D}atabase, {G}o players' styles",
 340   url = "http://www.gogod.co.uk/",
 341   owner = "jm"
 342 }
 343
 344 @ONLINE{GoGoD:dosaku,
 345   author = "Hall, T. Mark and Fairbairn, John",
 346   year = "winter 2011",
 347   title = "{G}ames of {G}o on {D}isk --- {GoGoD} {E}ncyclopaedia and {D}atabase, {A}rticles on {F}amous {P}layers -- Honinbo Dosaku",
 348   url = "http://www.gogod.co.uk/",
 349   owner = "jm"
 350 }
 351
 352 @INPROCEEDINGS{pls,
 353     author = "Roman Rosipal and Nicole Krämer",
 354     title = "Overview and recent advances in partial least squares",
 355     booktitle = "in ‘Subspace, Latent Structure and Feature Selection Techniques’, Lecture Notes in Computer Science",
 356     url = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.85.7735",
 357     cited = "2013\.02\.07",
 358     year = "2006",
 359     pages = "34--51",
 360     publisher = "Springer",
 361     owner = "jm"
 362 }
 363
 364 @book{haykin_nn,
 365     abstract = "Provides a comprehensive foundation of neural networks, recognizing the
 366 multidisciplinary nature of the subject, supported with examples, computer-
 367 oriented experiments, end of chapter problems, and a bibliography. {DLC}: Neural
 368 networks (Computer science).",
 369     author = "Haykin, Simon",
 370     day = "16",
 371     edition = "2",
 372     howpublished = "Hardcover",
 373     isbn = "0132733501",
 374     month = "jul",
 375     address="",
 376     publisher = "Prentice Hall",
 377     title = "Neural Networks: A Comprehensive Foundation (2nd Edition)",
 378     url = "http://www.worldcat.org/isbn/0132733501",
 379     year = "1998",
 380     owner = "jm"
 381
 382 }
 383
 384 @ONLINE{GnuGo,
 385   author = "Daniel Bump and Gunnar Farneback and Arend Bayer and others",
 386   year = "2009",
 387   title = "{GNU} {G}o",
 388   url = "http://www.gnu.org/software/gnugo/",
 389   owner = "jm",
 390   timestamp = "2012.03.27"
 391 }
 392
 393 @ONLINE{Pachi,
 394   author = "{B}audi{\v{s}}, {P}etr and others",
 395   year = "2012",
 396   title = "Pachi --- {S}imple {G}o/{B}aduk/{W}eiqi {B}ot",
 397   url = "http://repo.or.cz/w/pachi.git",
 398   owner = "pasky"
 399 }
 400
 401 @ONLINE{GoR,
 402   author = "Ales Cieply and others",
 403   year = "2011",
 404   title = "{EGF} ratings system -- {S}ystem description",
 405   url = "http://www.europeangodatabase.eu/EGD/EGF_rating_system.php",
 406   owner = "pasky",
 407   timestamp = "2011.03.10"
 408 }
 409
 410 @ONLINE{ProGoR,
 411   author = "Ales Cieply and others",
 412   year = "2008",
 413   title = "{G}o {R}atings of {P}rofessional and {S}trong {A}mateur {P}layers",
 414   url = "http://www.goweb.cz/progor",
 415   owner = "pasky"
 416 }
 417
 418 @ARTICLE{CoverHart1967,
 419   author = "Thomas M. Cover and Peter E. Hart",
 420   title = "Nearest neighbor pattern classification",
 421   journal = "IEEE Transactions on Information Theory",
 422   year = "1967",
 423   volume = "13",
 424   pages = "21-27",
 425   doi="10.1109/TIT.1967.1053964",
 426   number = "1",
 427   owner = "hellboy",
 428   timestamp = "2010.03.10"
 429 }
 430
 431 @INPROCEEDINGS{PatElo,
 432   author = "{C}oulom, {R}{\'e}mi",
 433   title = "{C}omputing {E}lo {R}atings of {M}ove {P}atterns in the {G}ame of {G}o",
 434   booktitle = "{C}omputer {G}ames {W}orkshop ",
 435   year = "2007",
 436   editor = "van den {H}erik, {H}. {J}aap and {M}ark {W}inands and {J}os {U}iterwijk and {M}aarten {S}chadd",
 437   address = "{A}msterdam {P}ays-{B}as ",
 438   abstract = "{M}ove patterns are an essential method to incorporate domain knowledge
 439         into {G}o-playing programs. {T}his paper presents a new {B}ayesian
 440         technique for supervised learning of such patterns from game records,
 441         based on a generalization of {E}lo ratings. {E}ach sample move in
 442         the training data is considered as a victory of a team of pattern
 443         features. {E}lo ratings of individual pattern features are computed
 444         from these victories, and can be used in previously unseen positions
 445         to compute a probability distribution over legal moves. {I}n this
 446         approach, several pattern features may be combined, without an exponential
 447         cost in the number of features. {D}espite a very small number of
 448         training games (652), this algorithm outperforms most previous pattern-learning
 449         algorithms, both in terms of mean log-evidence (−2.69), and prediction
 450         rate (34.9%). {A} 19x19 {M}onte-{C}arlo program improved with these
 451         patterns reached the level of the strongest classical programs.",
 452   affiliation = "{SEQUEL} - {INRIA} {F}uturs - {INRIA} - {CNRS} : {UMR}8022 - {CNRS}
 453         : {UMR}8146 - {U}niversit{\'e} des {S}ciences et {T}echnologies de
 454         {L}ille - {L}ille {I} - {U}niversit{\'e} {C}harles de {G}aulle -
 455         {L}ille {III} - {E}cole {C}entrale de {L}ille ",
 456   audience = "non sp{\'e}cifi{\'e}e ",
 457   url = "http://hal.inria.fr/inria-00149859/en/"
 458 }
 459
 460 @BOOK{Bayes,
 461   title = "Pattern classification and scene analysis",
 462   publisher = "A Wiley-Interscience Publication, New York: Wiley",
 463   year = "1973",
 464   author = "{Duda}, R.~O. and {Hart}, P.~E."
 465 }
 466
 467 @BOOK{Elo,
 468   title = "The rating of chessplayers, past and present",
 469   publisher = "Arco, New York",
 470   year = "1978",
 471   author = "Arpad E. Elo",
 472   isbn = "0668047216",
 473   owner = "pasky"
 474 }
 475
 476 @ONLINE{GTP,
 477   author = "{Gunnar Farneb\"ack}",
 478   year = "2001",
 479   title = "GTP --- {G}o {T}ext {P}rotocol (version 1)",
 480   url = "http://www.lysator.liu.se/~gunnar/gtp/",
 481   owner = "pasky"
 482 }
 483
 484 @ONLINE{Kombilo,
 485   author = "Ulrich G{\"o}rtz",
 486   year = "2012",
 487   title = "Kombilo --- a {G}o database program (version 0.7)",
 488   url = "http://www.u-go.net/kombilo/",
 489   owner = "pasky"
 490 }
 491
 492 @ONLINE{GTL,
 493   author = "Jean-loup Gailly and Bill Hosken and others",
 494   year = "2011",
 495   title = "{T}he {G}o {T}eaching {L}adder",
 496   url = "http://gtl.xmp.net/",
 497   owner = "pasky"
 498 }
 499
 500 @INPROCEEDINGS{GellySilver2008,
 501   author = "Gelly, Sylvain and Silver, David",
 502   title = "Achieving master level play in 9x9 computer go",
 503   booktitle = "AAAI'08: Proceedings of the 23rd national conference on Artificial intelligence",
 504   year = "2008",
 505   pages = "1537--1540",
 506   publisher = "AAAI Press",
 507   abstract = "The UCT algorithm uses Monte-Carlo simulation to estimate the value
 508         of states in a search tree from the current state. However, the first
 509         time a state is encountered, UCT has no knowledge, and is unable
 510         to generalise from previous experience. We describe two extensions
 511         that address these weaknesses. Our first algorithm, heuristic UCT,
 512         incorporates prior knowledge in the form of a value function. The
 513         value function can be learned offline, using a linear combination
 514         of a million binary features, with weights trained by temporal-difference
 515         learning. Our second algorithm, UCT-RAVE, forms a rapid online generalisation
 516         based on the value of moves. We applied our algorithms to the domain
 517         of 9 × 9 Computer Go, using the program MoGo. Using both heuristic
 518         UCT and RAVE, MoGo became the first program to achieve human master
 519         level in competitive play.",
 520   isbn = "978-1-57735-368-3",
 521   location = "Chicago, Illinois"
 522 }
 523
 524 @INPROCEEDINGS{CompAwar,
 525   author = "Ghoneim, A.S. and Essam, D.L. and Abbass, H.A.",
 526   title = "Competency awareness in strategic decision making",
 527   booktitle = "Cognitive Methods in Situation Awareness and Decision Support (CogSIMA),
 528         2011 IEEE First International Multi-Disciplinary Conference on",
 529   year = "2011",
 530   pages = "106 -109",
 531   month = "feb.",
 532   doi = "10.1109/COGSIMA.2011.5753426",
 533   keywords = "competency awareness;data mining;human-played GO games;mental picture;player
 534         skill;psychological tests;real-time monitoring;reasoning;skill-assessment
 535         tests;strategic decision making;time-series analysis;cognition;computer
 536         games;data mining;decision making;psychology;time series;",
 537   owner = "jm",
 538   timestamp = "2012.03.27"
 539 }
 540
 541 @ONLINE{GoDiscThread,
 542   author = "GoDiscussions",
 543   title = "{P}ro {S}tyles (discussion thread)",
 544   url = "http://www.godiscussions.com/forum/showthread.php?t=10980",
 545   owner = "pasky"
 546 }
 547
 548 @ONLINE{MoyoGo,
 549   author = "Frank de Groot",
 550   year = "2005",
 551   title = "{M}oyo {G}o {S}tudio",
 552   url = "http://www.moyogo.com/",
 553   owner = "pasky"
 554 }
 555
 556
 557 @BOOK{Haykin1994,
 558   title = "Neural Networks: A Comprehensive Foundation",
 559   publisher = "Macmillan",
 560   year = "1994",
 561   author = "Haykin, S.",
 562   address = "New York",
 563   citeulike-article-id = "2429223",
 564   keywords = "neural\_nets",
 565   owner = "hellboy",
 566   posted-at = "2008-02-26 12:33:02",
 567   priority = "2",
 568   timestamp = "2010.06.13"
 569 }
 570
 571 @ONLINE{SGF,
 572   author = "Arno Hollosi",
 573   year = "2006",
 574   title = "{SGF} {F}ile {F}ormat",
 575   url = "http://www.red-bean.com/sgf/",
 576   owner = "pasky"
 577 }
 578
 579 @MISC{SociomapsPersonal,
 580   author = "{{H}\"{o}schl, {C}yril}",
 581   howpublished = "personal communication",
 582   year = "2010"
 583 }
 584
 585 @BOOK{Sociomaps,
 586   title = "Visualization of Sociomaps",
 587   publisher = "Bachelor Thesis, MFF UK",
 588   year = "2006",
 589   author = "{{H}\"{o}schl, {C}yril}",
 590   location = "Praha"
 591 }
 592
 593 @BOOK{Jolliffe1986,
 594   title = "Principal Component Analysis",
 595   publisher = "Springer",
 596   address ="New York",
 597   year = "1986",
 598   author = "I.T. Jolliffe",
 599   owner = "hellboy"
 600 }
 601 @ONLINE{style:baduk,
 602   author = "Alexander Dinerchtein",
 603   year = "2012",
 604   title = "What is your playing style?",
 605   url = "http://style.baduk.com",
 606   owner = "jm",
 607   cited = "8.\,4.\,2013"
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 627     booktitle = {},
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 629     pages = {1137--1143},
 630     publisher = {Morgan Kaufmann}
 631 }
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 635   author = "William Shubert",
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 638   owner = "jm"
 639 }
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 646   owner = "jm"
 647 }
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 654   owner = "pasky"
 655 }
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 659   year = "2011",
 660   title = "{AI::NaiveBayes1} {CPAN} {M}odule",
 661   url = "http://search.cpan.org/~vlado/AI-NaiveBayes1-2.006/NaiveBayes1.pm",
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 695 }
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 699   title     = "On Move Pattern Trends in a Large Go Games Corpus",
 700   journal   = "Arxiv, CoRR",
 701   month = "October",
 702   year      = "2012",
 703   url        = "http://arxiv.org/abs/1209.5251",
 704   bibsource = "DBLP, http://dblp.uni-trier.de"
 705 }
 706 volume    = "abs/1209.5251",
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 726     Uroš Petrovič and Ivan Bratko and Gad Shaulsky and Blaž Zupan},
 727   title = {Microarray data mining with visual programming},
 728   journal = {Bioinformatics},
 729   volume = {21},
 730   issue = {3},
 731   month = feb,
 732   year = {2005},
 733   issn = {1367-4803},
 734   pages = {396--398},
 735   numpages = {3},
 736   url = {http://bioinformatics.oxfordjournals.org/content/21/3/396.full.pdf},
 737   publisher = {Oxford University Press},
 738   address = {Oxford, UK},
 739 }
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 741 @TECHREPORT{Nissen2003,
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 766   url = "http://www.python.org/dev/peps/pep-0356/",
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 768   timestamp = "2009.04.29"
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 774   title = "{S}ociomapping {S}uite",
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 776   owner = "pasky"
 777 }
 778
 779 @ONLINE{TPA,
 780   author = "{QED GROUP}",
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 782   title = "{T}eam {P}rofile {A}nalyzer",
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 784   owner = "pasky"
 785 }
 786
 787 @INPROCEEDINGS{Riedmiller1993,
 788   author = "Martin Riedmiller and Heinrich Braun",
 789   title = "{A Direct Adaptive Method for Faster Backpropagation Learning: The
 790         RPROP Algorithm}",
 791   booktitle = "IEEE International Conference on Neural Networks",
 792   year = "1993",
 793   pages = "586--591",
 794   owner = "hellboy",
 795   timestamp = "2010.03.07"
 796 }
 797
 798 @article{freeviz,
 799 title = "FreeViz --- An intelligent multivariate visualization approach to explorative analysis of biomedical data",
 800 journal = "Journal of Biomedical Informatics",
 801 volume = "40",
 802 number = "6",
 803 pages = "661 - 671",
 804 year = "2007",
 805 note = "Intelligent Data Analysis in Biomedicine",
 806 issn = "1532-0464",
 807 doi = "10.1016/j.jbi.2007.03.010",
 808 url = "http://www.sciencedirect.com/science/article/pii/S1532046407000275",
 809 author = "Janez Dem{\v{s}}ar and Gregor Leban and Bla{\v{z}} Zupan"
 810 }
 811
 812
 813 @ARTICLE{Pearson,
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 815   title = "{Thirteen ways to look at the correlation coefficient}",
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 818   volume = "42",
 819   pages = "59--66",
 820   number = "1",
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 822   owner = "pasky"
 823 }
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 828   title = "Rank --- worldwide comparison",
 829   url = "http://senseis.xmp.net/?RankWorldwideComparison",
 830   owner = "pasky"
 831 }
 832
 833 @INPROCEEDINGS{SpatPat,
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 835   title = "Bayesian pattern ranking for move prediction in the game of Go",
 836   booktitle = "ICML '06: Proceedings of the 23rd international conference on Machine
 837         learning",
 838   year = "2006",
 839   pages = "873--880",
 840   address = "New York, NY, USA",
 841   publisher = "ACM",
 842   doi = "http://doi.acm.org/10.1145/1143844.1143954",
 843   isbn = "1-59593-383-2",
 844   location = "Pittsburgh, Pennsylvania"
 845 }
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 849   title = "Using Visualisation of Group Structure and Dynamics in Team Development",
 850   booktitle = "50th Conference of the International Military Training Association",
 851   year = "2008",
 852   location = "Amsterdam"
 853 }
 854
 855 @ARTICLE{MDP,
 856   author = "Zito Tiziano and Wilbert Niko and Wiskott Laurenz and Berkes Pietro",
 857   title = "Modular toolkit for {D}ata {P}rocessing ({MDP}): a {P}ython data processing framework",
 858   journal = "Frontiers in Neuroinformatics",
 859   year = "2008",
 860   volume = "2",
 861   abstract = "Modular toolkit for Data Processing (MDP) is a data processing framework
 862         written in Python. From the user&#39;s perspective, MDP is a collection
 863         of supervised and unsupervised learning algorithms and other data
 864         processing units that can be combined into data processing sequences
 865         and more complex feed-forward network architectures. Computations
 866         are performed efficiently in terms of speed and memory requirements.
 867         From the scientific developer&#39;s perspective, MDP is a modular
 868         framework, which can easily be expanded. The implementation of new
 869         algorithms is easy and intuitive. The new implemented units are then
 870         automatically integrated with the rest of the library. MDP has been
 871         written in the context of theoretical research in neuroscience, but
 872         it has been designed to be helpful in any context where trainable
 873         data processing algorithms are used. Its simplicity on the user&#39;s
 874         side, the variety of readily available algorithms, and the reusability
 875         of the implemented units make it also a useful educational tool.",
 876   doi = "10.3389/neuro.11/008.2008",
 877   issn = "ISSN 1662-5196",
 878   owner = "hellboy",
 879   timestamp = "2010.03.05"
 880 }
 881
 882 @comment{jabref-meta: selector_publisher:}
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 888 @comment{jabref-meta: selector_keywords:}
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