clanek_go_congress/clanek.bib

   1 % Encoding: UTF-8
   2
   3 @TECHREPORT{style_quest,
   4   author = "{M}oud{\v{r}\'{i}}k, {J}osef and {B}audi{\v{s}}, {P}etr",
   5   title = "Style Consensus: Style of Professional Players, Judged by Strong Players",
   6   year = "2013",
   7   month = "May",
   8 }
   9
  10 @MastersThesis{Moudrik13,
  11   author   = "Josef Moud{\v{r}\'{i}}k",
  12   title    = "Meta-learning methods for analyzing Go playing trends",
  13   school   = "Charles University, Faculty of Mathematics and Physics",
  14   address  = "Prague, Czech Republic",
  15   note     = "Currently in preparation.",
  16   year     = "2013",
  17 }
  18 @ONLINE{GoAncientChina,
  19   author = "John Fairbairn",
  20   year = "1995",
  21   title = "Go in Ancient China",
  22   url = "http://www.pandanet.co.jp/English/essay/goancientchina.html",
  23   cited = "15.\,1.\,2013",
  24   owner = "jm"
  25 }
  26
  27 @ONLINE{ wiki:Go,
  28    author = "Wikipedia",
  29    title = "Go (game) --- Wikipedia{,} The Free Encyclopedia",
  30    year = "2013",
  31    url = "http://en.wikipedia.org/w/index.php?title=Go_(game)\&oldid=532253814",
  32    cited = "15.\,1.\,2013"
  33 }
  34
  35 @ONLINE{ wiki:go_handi,
  36    author = "Wikipedia",
  37    title = "Go handicaps --- Wikipedia{,} The Free Encyclopedia",
  38    year = "2012",
  39    url = "http://en.wikipedia.org/w/index.php?title=Go_handicaps&oldid=505279363",
  40    cited = "16.\,1.\,2013"
  41 }
  42
  43 @ONLINE{ wiki:go_rank,
  44    author = "Wikipedia",
  45    title = "Go ranks and ratings --- Wikipedia{,} The Free Encyclopedia",
  46    year = "2012",
  47    url = "http://en.wikipedia.org/w/index.php?title=Go_ranks_and_ratings&oldid=522963011",
  48    cited = "18.\,1.\,2013"
  49 }
  50
  51 @ARTICLE{ieee:mcts_overview,
  52 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.},
  53 journal={Computational Intelligence and AI in Games, IEEE Transactions on},
  54 title={A Survey of Monte Carlo Tree Search Methods},
  55 year={2012},
  56 month={march },
  57 volume={4},
  58 number={1},
  59 pages={1 -43},
  60 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);},
  61 doi={10.1109/TCIAIG.2012.2186810},
  62 ISSN={1943-068X},
  63    url = "http://www.doc.ic.ac.uk/~sgc/papers/browne_ieee12.pdf",
  64
  65 }
  66
  67 @ONLINE{ wiki:computer_go,
  68    author = "Wikipedia",
  69    title = "Computer Go --- Wikipedia{,} The Free Encyclopedia",
  70    year = "2013",
  71    url = "http://en.wikipedia.org/w/index.php?title=Computer_Go&oldid=530803356",
  72    cited = "17.\,1.\,2013"
  73 }
  74
  75
  76 @ONLINE{ senseis:which_pro,
  77    author = "{Sensei's Library}",
  78    title = "Which Pro Do You Most Play Like",
  79    url = "http://senseis.xmp.net/?WhichProDoYouMostPlayLike",
  80    year = "2013",
  81    cited = "8.\,4.\,2013"
  82 }
  83
  84 @ONLINE{ senseis:33,
  85    author = "{Sensei's Library}",
  86    title = "4-4 point low approach one-space low pincer",
  87    url = "http://senseis.xmp.net/?44PointLowApproachOneSpaceLowPincer",
  88    year = "2013",
  89    cited = "29.\,3.\,2013"
  90 }
  91
  92 @ONLINE{ senseis:empty_triangle,
  93    author = "{Sensei's Library}",
  94    title = "The empty triangle is bad",
  95    url = "http://senseis.xmp.net/?TheEmptyTriangleIsBad",
  96    year = "2013",
  97    cited = "18.\,3.\,2013"
  98 }
  99
 100 @ONLINE{ senseis:styles,
 101    author = "{Sensei's Library}",
 102    title = "Professional Players' Go Styles",
 103    url = "http://senseis.xmp.net/?ProfessionalPlayersGoStyles",
 104    year = "2013",
 105    cited = "12.\,3.\,2013"
 106 }
 107 @ONLINE{ senseis:rank_cmp,
 108    author = "{Sensei's Library}",
 109    title = "Rank - worldwide comparison",
 110    url = "http://senseis.xmp.net/?RankWorldwideComparison",
 111    year = "2013",
 112    cited = "16.\,1.\,2013"
 113 }
 114 @ONLINE{ senseis:proverbs,
 115    author = "{Sensei's Library}",
 116    title = "Go Proverbs",
 117    url = "http://senseis.xmp.net/?GoProverbs",
 118    year = "2013",
 119    cited = "18.\,2.\,2013"
 120 }
 121
 122 @ONLINE{ senseis:tutorial,
 123    author = "{Sensei's Library}",
 124    title = "Rules of Go - introductory",
 125    url = "http://senseis.xmp.net/?BasicRulesOfGo",
 126    year = "2013",
 127    cited = "15.\,1.\,2013"
 128 }
 129 @ONLINE{ senseis:scoring,
 130    author = "{Sensei's Library}",
 131    title = "Scoring",
 132    url = "http://senseis.xmp.net/?Scoring",
 133    year = "2013",
 134    cited = "16.\,1.\,2013"
 135 }
 136 @ONLINE{ senseis:seki,
 137    author = "{Sensei's Library}",
 138    title = "Seki",
 139    url = "http://senseis.xmp.net/?Seki",
 140    year = "2013",
 141    cited = "16.\,1.\,2013"
 142 }
 143 @ONLINE{ senseis:dan,
 144    author = "{Sensei's Library}",
 145    title = "Dan",
 146    url = "http://senseis.xmp.net/?Dan",
 147    year = "2013",
 148    cited = "8.\,2.\,2013"
 149 }
 150 @ONLINE{ senseis:rules,
 151    author = "{Sensei's Library}",
 152    title = "Rules of Go",
 153    url = "http://senseis.xmp.net/?RulesOfGo",
 154    year = "2013",
 155    cited = "16.\,1.\,2013"
 156 }
 157 @ONLINE{ senseis,
 158    author = "{Sensei's Library}",
 159    title = "Sensei's Library",
 160    year = "2013",
 161    url = "http://senseis.xmp.net/",
 162    cited = "15.\,1.\,2013"
 163 }
 164
 165 @ONLINE{ computer_go,
 166    author = "Nick Wedd",
 167    title = "Computer Go Info --- Human-Computer Go Challenges",
 168    year = "2013",
 169    url = "http://www.computer-go.info/h-c/index.html",
 170    cited = "8.\,2.\,2013"
 171 }
 172
 173 @ONLINE{ est_go,
 174    author = "{Go Census}",
 175    title = "",
 176    year = "2002",
 177    url = "http://web.archive.org/web/20021217041220/http://www.fin.ne.jp/~igo/census.htm",
 178    cited = "10.\,2.\,2013"
 179 }
 180
 181 @conference{ van_ees,
 182    author = "Theo van Ees",
 183    title = "The Slow Way West",
 184    booktitle = "Third International Conference on Baduk",
 185    address = "Myong-Ji University, Yongin City, Korea",
 186    month = "October",
 187    year = "2005",
 188    note = "Available as a part of the {GoGoD} {E}ncyclopaedia and {D}atabase, {H}istory",
 189    url = "http://www.gogod.co.uk/",
 190    cited = "8.\,2.\,2013"
 191 }
 192
 193 @article{vapnik95,
 194   author    = "Corinna Cortes and
 195                Vladimir Vapnik",
 196   title     = "Support-Vector Networks",
 197   journal   = "Machine Learning",
 198   volume    = "20",
 199   number    = "3",
 200   year      = "1995",
 201   pages     = "273-297",
 202   doi       = "10.1007/BF00994018",
 203 }
 204
 205
 206 @article{breiman96,
 207 year={1996},
 208 issn={0885-6125},
 209 journal={Machine Learning},
 210 volume={24},
 211 issue={1},
 212 doi={10.1007/BF00117832},
 213 title={Stacked regressions},
 214 url={http://dx.doi.org/10.1007/BF00117832},
 215 publisher={Kluwer Academic Publishers},
 216 keywords={Stacking; Non-negativity; Trees; Subset regression; Combinations},
 217 author={Breiman, Leo},
 218 pages={49-64},
 219 language={English}
 220 }
 221
 222 @ARTICLE{wolpert92,
 223     author = {David H. Wolpert},
 224     title = {Stacked Generalization},
 225     journal = {Neural Networks},
 226     year = {1992},
 227     volume = {5},
 228     pages = {241--259},
 229     url = "http://www.machine-learning.martinsewell.com/ensembles/stacking/Wolpert1992.pdf"
 230 }
 231
 232 @inproceedings{boosting,
 233 year={1995},
 234 isbn={978-3-540-59119-1},
 235 booktitle={Computational Learning Theory},
 236 volume={904},
 237 series={Lecture Notes in Computer Science},
 238 doi={10.1007/3-540-59119-2_166},
 239 title={A desicion-theoretic generalization of on-line learning and an application to boosting},
 240 url={http://dx.doi.org/10.1007/3-540-59119-2_166},
 241 publisher={Springer Berlin Heidelberg},
 242 author={Freund, Yoav and Schapire, RobertE.},
 243 pages={23-37}
 244 }
 245
 246
 247 @article{whitley94,
 248   title={A genetic algorithm tutorial},
 249   author={Whitley, D.},
 250   journal={Statistics and computing},
 251   volume={4},
 252   number={2},
 253   pages={65--85},
 254   year={1994},
 255   publisher={Springer}
 256 }
 257
 258 @book{ breiman84,
 259     author = "Breiman, Leo and Friedman, J. H. and Olshen R. A. and Stone, C. J.",
 260     year = "1984",
 261     title= "Classification and regression trees",
 262     address = "Monterey, CA",
 263     publisher = "Wadsworth \& Brooks/Cole Advanced Books \& Software",
 264     isbn = "978-0-412-04841-8"
 265 }
 266
 267 @article{breimanbag96,
 268  author = {Breiman, Leo},
 269  title = {Bagging predictors},
 270  journal = {Mach. Learn.},
 271  issue_date = {Aug. 1996},
 272  volume = {24},
 273  number = {2},
 274  month = aug,
 275  year = {1996},
 276  issn = {0885-6125},
 277  pages = {123--140},
 278  numpages = {18},
 279  url = {http://dx.doi.org/10.1023/A:1018054314350},
 280  doi = {10.1023/A:1018054314350},
 281  acmid = {231989},
 282  publisher = {Kluwer Academic Publishers},
 283  address = {Hingham, MA, USA},
 284  keywords = {aggregation, averaging, bootstrap, combining},
 285 }
 286
 287 @article{breiman01,
 288  author = "Breiman, Leo",
 289  title = "Random Forests",
 290  journal = "Machine Learning",
 291  issue_date = "October 1 2001",
 292  volume = "45",
 293  number = "1",
 294  month = oct,
 295  year = "2001",
 296  issn = "0885-6125",
 297  pages = "5--32",
 298  numpages = "28",
 299  doi = "10.1023/A:1010933404324",
 300  acmid = "570182",
 301  publisher = "Kluwer Academic Publishers",
 302  address = "Hingham, MA, USA",
 303  keywords = "classification, ensemble, regression",
 304 }
 305
 306 @article{smola04,
 307  author = "Smola, Alex J. and Sch{\"{o}}lkopf, Bernhard",
 308  title = "A tutorial on support vector regression",
 309  journal = "Statistics and Computing",
 310  issue_date = "August 2004",
 311  volume = "14",
 312  number = "3",
 313  month = "aug",
 314  year = "2004",
 315  issn = "0960-3174",
 316  pages = "199--222",
 317  numpages = "24",
 318  url = "http://www.cmlab.csie.ntu.edu.tw/~cyy/learning/papers/SVR_Tutorial.pdf",
 319  doi = "10.1023/B:STCO.0000035301.49549.88",
 320  acmid = "1011939",
 321  publisher = "Kluwer Academic Publishers",
 322  address = "Hingham, MA, USA",
 323  keywords = "machine learning, regression estimation, support vector machines"
 324 }
 325
 326 @ONLINE{GoGoD,
 327   author = "Hall, T. Mark and Fairbairn, John",
 328   year = "winter 2011",
 329   title = "{G}ames of {G}o on {D}isk --- {GoGoD} {E}ncyclopaedia and {D}atabase",
 330   url = "http://www.gogod.co.uk/",
 331   owner = "jm"
 332 }
 333
 334 @ONLINE{GoGoD:styles,
 335   author = "Fairbairn, John",
 336   year = "winter 2011",
 337   title = "{G}ames of {G}o on {D}isk --- {GoGoD} {E}ncyclopaedia and {D}atabase, {G}o players' styles",
 338   url = "http://www.gogod.co.uk/",
 339   owner = "jm"
 340 }
 341
 342 @ONLINE{GoGoD:dosaku,
 343   author = "Hall, T. Mark and Fairbairn, John",
 344   year = "winter 2011",
 345   title = "{G}ames of {G}o on {D}isk --- {GoGoD} {E}ncyclopaedia and {D}atabase, {A}rticles on {F}amous {P}layers -- Honinbo Dosaku",
 346   url = "http://www.gogod.co.uk/",
 347   owner = "jm"
 348 }
 349
 350 @INPROCEEDINGS{pls,
 351     author = "Roman Rosipal and Nicole Krämer",
 352     title = "Overview and recent advances in partial least squares",
 353     booktitle = "in ‘Subspace, Latent Structure and Feature Selection Techniques’, Lecture Notes in Computer Science",
 354     url = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.85.7735",
 355     cited = "2013\.02\.07",
 356     year = "2006",
 357     pages = "34--51",
 358     publisher = "Springer",
 359     owner = "jm"
 360 }
 361
 362 @book{haykin_nn,
 363     abstract = "Provides a comprehensive foundation of neural networks, recognizing the
 364 multidisciplinary nature of the subject, supported with examples, computer-
 365 oriented experiments, end of chapter problems, and a bibliography. {DLC}: Neural
 366 networks (Computer science).",
 367     author = "Haykin, Simon",
 368     day = "16",
 369     edition = "2",
 370     howpublished = "Hardcover",
 371     isbn = "0132733501",
 372     month = "jul",
 373     address="",
 374     publisher = "Prentice Hall",
 375     title = "Neural Networks: A Comprehensive Foundation (2nd Edition)",
 376     url = "http://www.worldcat.org/isbn/0132733501",
 377     year = "1998",
 378     owner = "jm"
 379
 380 }
 381
 382 @ONLINE{GnuGo,
 383   author = "Daniel Bump and Gunnar Farneback and Arend Bayer and others",
 384   year = "2009",
 385   title = "{GNU} {G}o",
 386   url = "http://www.gnu.org/software/gnugo/",
 387   owner = "jm",
 388   timestamp = "2012.03.27"
 389 }
 390
 391 @ONLINE{Pachi,
 392   author = "{B}audi{\v{s}}, {P}etr and others",
 393   year = "2012",
 394   title = "Pachi --- {S}imple {G}o/{B}aduk/{W}eiqi {B}ot",
 395   url = "http://repo.or.cz/w/pachi.git",
 396   owner = "pasky"
 397 }
 398
 399 @ONLINE{GoR,
 400   author = "Ales Cieply and others",
 401   year = "2011",
 402   title = "{EGF} ratings system -- {S}ystem description",
 403   url = "http://www.europeangodatabase.eu/EGD/EGF_rating_system.php",
 404   owner = "pasky",
 405   timestamp = "2011.03.10"
 406 }
 407
 408 @ONLINE{ProGoR,
 409   author = "Ales Cieply and others",
 410   year = "2008",
 411   title = "{G}o {R}atings of {P}rofessional and {S}trong {A}mateur {P}layers",
 412   url = "http://www.goweb.cz/progor",
 413   owner = "pasky"
 414 }
 415
 416 @ARTICLE{CoverHart1967,
 417   author = "Thomas M. Cover and Peter E. Hart",
 418   title = "Nearest neighbor pattern classification",
 419   journal = "IEEE Transactions on Information Theory",
 420   year = "1967",
 421   volume = "13",
 422   pages = "21-27",
 423   doi="10.1109/TIT.1967.1053964",
 424   number = "1",
 425   owner = "hellboy",
 426   timestamp = "2010.03.10"
 427 }
 428
 429 @INPROCEEDINGS{PatElo,
 430   author = "{C}oulom, {R}{\'e}mi",
 431   title = "{C}omputing {E}lo {R}atings of {M}ove {P}atterns in the {G}ame of {G}o",
 432   booktitle = "{C}omputer {G}ames {W}orkshop ",
 433   year = "2007",
 434   editor = "van den {H}erik, {H}. {J}aap and {M}ark {W}inands and {J}os {U}iterwijk and {M}aarten {S}chadd",
 435   address = "{A}msterdam {P}ays-{B}as ",
 436   abstract = "{M}ove patterns are an essential method to incorporate domain knowledge
 437         into {G}o-playing programs. {T}his paper presents a new {B}ayesian
 438         technique for supervised learning of such patterns from game records,
 439         based on a generalization of {E}lo ratings. {E}ach sample move in
 440         the training data is considered as a victory of a team of pattern
 441         features. {E}lo ratings of individual pattern features are computed
 442         from these victories, and can be used in previously unseen positions
 443         to compute a probability distribution over legal moves. {I}n this
 444         approach, several pattern features may be combined, without an exponential
 445         cost in the number of features. {D}espite a very small number of
 446         training games (652), this algorithm outperforms most previous pattern-learning
 447         algorithms, both in terms of mean log-evidence (−2.69), and prediction
 448         rate (34.9%). {A} 19x19 {M}onte-{C}arlo program improved with these
 449         patterns reached the level of the strongest classical programs.",
 450   affiliation = "{SEQUEL} - {INRIA} {F}uturs - {INRIA} - {CNRS} : {UMR}8022 - {CNRS}
 451         : {UMR}8146 - {U}niversit{\'e} des {S}ciences et {T}echnologies de
 452         {L}ille - {L}ille {I} - {U}niversit{\'e} {C}harles de {G}aulle -
 453         {L}ille {III} - {E}cole {C}entrale de {L}ille ",
 454   audience = "non sp{\'e}cifi{\'e}e ",
 455   url = "http://hal.inria.fr/inria-00149859/en/"
 456 }
 457
 458 @BOOK{Bayes,
 459   title = "Pattern classification and scene analysis",
 460   publisher = "A Wiley-Interscience Publication, New York: Wiley",
 461   year = "1973",
 462   author = "{Duda}, R.~O. and {Hart}, P.~E."
 463 }
 464
 465 @BOOK{Elo,
 466   title = "The rating of chessplayers, past and present",
 467   publisher = "Arco, New York",
 468   year = "1978",
 469   author = "Arpad E. Elo",
 470   isbn = "0668047216",
 471   owner = "pasky"
 472 }
 473
 474 @ONLINE{GTP,
 475   author = "{Gunnar Farneb\"ack}",
 476   year = "2001",
 477   title = "GTP --- {G}o {T}ext {P}rotocol (version 1)",
 478   url = "http://www.lysator.liu.se/~gunnar/gtp/",
 479   owner = "pasky"
 480 }
 481
 482 @ONLINE{Kombilo,
 483   author = "Ulrich G{\"o}rtz",
 484   year = "2012",
 485   title = "Kombilo --- a {G}o database program (version 0.7)",
 486   url = "http://www.u-go.net/kombilo/",
 487   owner = "pasky"
 488 }
 489
 490 @ONLINE{GTL,
 491   author = "Jean-loup Gailly and Bill Hosken and others",
 492   year = "2011",
 493   title = "{T}he {G}o {T}eaching {L}adder",
 494   url = "http://gtl.xmp.net/",
 495   owner = "pasky"
 496 }
 497
 498 @INPROCEEDINGS{GellySilver2008,
 499   author = "Gelly, Sylvain and Silver, David",
 500   title = "Achieving master level play in 9x9 computer go",
 501   booktitle = "AAAI'08: Proceedings of the 23rd national conference on Artificial intelligence",
 502   year = "2008",
 503   pages = "1537--1540",
 504   publisher = "AAAI Press",
 505   abstract = "The UCT algorithm uses Monte-Carlo simulation to estimate the value
 506         of states in a search tree from the current state. However, the first
 507         time a state is encountered, UCT has no knowledge, and is unable
 508         to generalise from previous experience. We describe two extensions
 509         that address these weaknesses. Our first algorithm, heuristic UCT,
 510         incorporates prior knowledge in the form of a value function. The
 511         value function can be learned offline, using a linear combination
 512         of a million binary features, with weights trained by temporal-difference
 513         learning. Our second algorithm, UCT-RAVE, forms a rapid online generalisation
 514         based on the value of moves. We applied our algorithms to the domain
 515         of 9 × 9 Computer Go, using the program MoGo. Using both heuristic
 516         UCT and RAVE, MoGo became the first program to achieve human master
 517         level in competitive play.",
 518   isbn = "978-1-57735-368-3",
 519   location = "Chicago, Illinois"
 520 }
 521
 522 @INPROCEEDINGS{CompAwar,
 523   author = "Ghoneim, A.S. and Essam, D.L. and Abbass, H.A.",
 524   title = "Competency awareness in strategic decision making",
 525   booktitle = "Cognitive Methods in Situation Awareness and Decision Support (CogSIMA),
 526         2011 IEEE First International Multi-Disciplinary Conference on",
 527   year = "2011",
 528   pages = "106 -109",
 529   month = "feb.",
 530   doi = "10.1109/COGSIMA.2011.5753426",
 531   keywords = "competency awareness;data mining;human-played GO games;mental picture;player
 532         skill;psychological tests;real-time monitoring;reasoning;skill-assessment
 533         tests;strategic decision making;time-series analysis;cognition;computer
 534         games;data mining;decision making;psychology;time series;",
 535   owner = "jm",
 536   timestamp = "2012.03.27"
 537 }
 538
 539 @ONLINE{GoDiscThread,
 540   author = "GoDiscussions",
 541   title = "{P}ro {S}tyles (discussion thread)",
 542   url = "http://www.godiscussions.com/forum/showthread.php?t=10980",
 543   owner = "pasky"
 544 }
 545
 546 @ONLINE{MoyoGo,
 547   author = "Frank de Groot",
 548   year = "2005",
 549   title = "{M}oyo {G}o {S}tudio",
 550   url = "http://www.moyogo.com/",
 551   owner = "pasky"
 552 }
 553
 554
 555 @BOOK{Haykin1994,
 556   title = "Neural Networks: A Comprehensive Foundation",
 557   publisher = "Macmillan",
 558   year = "1994",
 559   author = "Haykin, S.",
 560   address = "New York",
 561   citeulike-article-id = "2429223",
 562   keywords = "neural\_nets",
 563   owner = "hellboy",
 564   posted-at = "2008-02-26 12:33:02",
 565   priority = "2",
 566   timestamp = "2010.06.13"
 567 }
 568
 569 @ONLINE{SGF,
 570   author = "Arno Hollosi",
 571   year = "2006",
 572   title = "{SGF} {F}ile {F}ormat",
 573   url = "http://www.red-bean.com/sgf/",
 574   owner = "pasky"
 575 }
 576
 577 @MISC{SociomapsPersonal,
 578   author = "{{H}\"{o}schl, {C}yril}",
 579   howpublished = "personal communication",
 580   year = "2010"
 581 }
 582
 583 @BOOK{Sociomaps,
 584   title = "Visualization of Sociomaps",
 585   publisher = "Bachelor Thesis, MFF UK",
 586   year = "2006",
 587   author = "{{H}\"{o}schl, {C}yril}",
 588   location = "Praha"
 589 }
 590
 591 @BOOK{Jolliffe1986,
 592   title = "Principal Component Analysis",
 593   publisher = "Springer",
 594   address ="New York",
 595   year = "1986",
 596   author = "I.T. Jolliffe",
 597   owner = "hellboy"
 598 }
 599 @ONLINE{style:baduk,
 600   author = "Alexander Dinerchtein",
 601   year = "2012",
 602   title = "What is your playing style?",
 603   url = "http://style.baduk.com",
 604   owner = "jm",
 605   cited = "8.\,4.\,2013"
 606 }
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 623     author = {Ron Kohavi},
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 625     booktitle = {},
 626     year = {1995},
 627     pages = {1137--1143},
 628     publisher = {Morgan Kaufmann}
 629 }
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 635   url = "http://www.gokgs.com/",
 636   owner = "jm"
 637 }
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 644   owner = "jm"
 645 }
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 652   owner = "pasky"
 653 }
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 655 @ONLINE{NaiveBayes1,
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 657   year = "2011",
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 659   url = "http://search.cpan.org/~vlado/AI-NaiveBayes1-2.006/NaiveBayes1.pm",
 660   owner = "pasky"
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 693 }
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 697   title     = "On Move Pattern Trends in a Large Go Games Corpus",
 698   journal   = "Arxiv, CoRR",
 699   month = "October",
 700   year      = "2012",
 701   url        = "http://arxiv.org/abs/1209.5251",
 702   bibsource = "DBLP, http://dblp.uni-trier.de"
 703 }
 704 volume    = "abs/1209.5251",
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 724     Uroš Petrovič and Ivan Bratko and Gad Shaulsky and Blaž Zupan},
 725   title = {Microarray data mining with visual programming},
 726   journal = {Bioinformatics},
 727   volume = {21},
 728   issue = {3},
 729   month = feb,
 730   year = {2005},
 731   issn = {1367-4803},
 732   pages = {396--398},
 733   numpages = {3},
 734   url = {http://bioinformatics.oxfordjournals.org/content/21/3/396.full.pdf},
 735   publisher = {Oxford University Press},
 736   address = {Oxford, UK},
 737 }
 738
 739 @TECHREPORT{Nissen2003,
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 743   year = "2003",
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 745   owner = "hellboy",
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 747 }
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 757 }
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 763   title = "{P}ython 2.5",
 764   url = "http://www.python.org/dev/peps/pep-0356/",
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 766   timestamp = "2009.04.29"
 767 }
 768
 769 @ONLINE{SociomapSite,
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 772   title = "{S}ociomapping {S}uite",
 773   url = "http://www.sociomap.com/",
 774   owner = "pasky"
 775 }
 776
 777 @ONLINE{TPA,
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 780   title = "{T}eam {P}rofile {A}nalyzer",
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 782   owner = "pasky"
 783 }
 784
 785 @INPROCEEDINGS{Riedmiller1993,
 786   author = "Martin Riedmiller and Heinrich Braun",
 787   title = "{A Direct Adaptive Method for Faster Backpropagation Learning: The
 788         RPROP Algorithm}",
 789   booktitle = "IEEE International Conference on Neural Networks",
 790   year = "1993",
 791   pages = "586--591",
 792   owner = "hellboy",
 793   timestamp = "2010.03.07"
 794 }
 795
 796 @article{freeviz,
 797 title = "FreeViz --- An intelligent multivariate visualization approach to explorative analysis of biomedical data",
 798 journal = "Journal of Biomedical Informatics",
 799 volume = "40",
 800 number = "6",
 801 pages = "661 - 671",
 802 year = "2007",
 803 note = "Intelligent Data Analysis in Biomedicine",
 804 issn = "1532-0464",
 805 doi = "10.1016/j.jbi.2007.03.010",
 806 url = "http://www.sciencedirect.com/science/article/pii/S1532046407000275",
 807 author = "Janez Dem{\v{s}}ar and Gregor Leban and Bla{\v{z}} Zupan"
 808 }
 809
 810
 811 @ARTICLE{Pearson,
 812   author = "J. L. Rodgers and W. A. Nicewander",
 813   title = "{Thirteen ways to look at the correlation coefficient}",
 814   journal = "The American Statistician",
 815   year = "1988",
 816   volume = "42",
 817   pages = "59--66",
 818   number = "1",
 819   month = "Feb",
 820   owner = "pasky"
 821 }
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 826   title = "Rank --- worldwide comparison",
 827   url = "http://senseis.xmp.net/?RankWorldwideComparison",
 828   owner = "pasky"
 829 }
 830
 831 @INPROCEEDINGS{SpatPat,
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 833   title = "Bayesian pattern ranking for move prediction in the game of Go",
 834   booktitle = "ICML '06: Proceedings of the 23rd international conference on Machine
 835         learning",
 836   year = "2006",
 837   pages = "873--880",
 838   address = "New York, NY, USA",
 839   publisher = "ACM",
 840   doi = "http://doi.acm.org/10.1145/1143844.1143954",
 841   isbn = "1-59593-383-2",
 842   location = "Pittsburgh, Pennsylvania"
 843 }
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 845 @INPROCEEDINGS{TeamProf,
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 847   title = "Using Visualisation of Group Structure and Dynamics in Team Development",
 848   booktitle = "50th Conference of the International Military Training Association",
 849   year = "2008",
 850   location = "Amsterdam"
 851 }
 852
 853 @ARTICLE{MDP,
 854   author = "Zito Tiziano and Wilbert Niko and Wiskott Laurenz and Berkes Pietro",
 855   title = "Modular toolkit for {D}ata {P}rocessing ({MDP}): a {P}ython data processing framework",
 856   journal = "Frontiers in Neuroinformatics",
 857   year = "2008",
 858   volume = "2",
 859   abstract = "Modular toolkit for Data Processing (MDP) is a data processing framework
 860         written in Python. From the user&#39;s perspective, MDP is a collection
 861         of supervised and unsupervised learning algorithms and other data
 862         processing units that can be combined into data processing sequences
 863         and more complex feed-forward network architectures. Computations
 864         are performed efficiently in terms of speed and memory requirements.
 865         From the scientific developer&#39;s perspective, MDP is a modular
 866         framework, which can easily be expanded. The implementation of new
 867         algorithms is easy and intuitive. The new implemented units are then
 868         automatically integrated with the rest of the library. MDP has been
 869         written in the context of theoretical research in neuroscience, but
 870         it has been designed to be helpful in any context where trainable
 871         data processing algorithms are used. Its simplicity on the user&#39;s
 872         side, the variety of readily available algorithms, and the reusability
 873         of the implemented units make it also a useful educational tool.",
 874   doi = "10.3389/neuro.11/008.2008",
 875   issn = "ISSN 1662-5196",
 876   owner = "hellboy",
 877   timestamp = "2010.03.05"
 878 }
 879
 880 @comment{jabref-meta: selector_publisher:}
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 882 @comment{jabref-meta: selector_author:}
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 886 @comment{jabref-meta: selector_keywords:}
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