Jornada GIC random forests 2012-01-27

objetivo

El objetivo de la jornada es hacer un repaso al estado del arte sobre random forests (y sistemas de clasificación basados en ensambles?). El metodo de trabajo consiste en la presentación por parte de todos los presentes de resumenes de articulos recientes

orden de las presentaciones

• Josu Maiora: tutorial de Criminisi, clasificiacion y regresion slides
• Alexandre Savio: breiman slides_sinrefs
• Iñigo Barandiaran: prehistoria ?? [

distribución de articulos a presentar

• Ana I. Gonzalez
  • experimental comparison on ensembles of trees [1] review
  • rotation forest empirical [2] review

• Josu Maiora
  • tutorial de Criminisi, clasificiacion y regresion [3] slides
  • multilabel y heterogeneos [4] slides

• Borja Ayerdi
  • random feature weights [5]
  • statistical pruning [6] diap

• Iñigo Barandiaran
  • tutorial de Criminisi, density, manyfold, semisupervised [7]
  • prehistoria ?? [8]

• Borja Fernandez-Gauna
  • learning areas of expertise [9] presentation
  • building by reward-punishment [10] presentation

• Jose Manuel Lopez-Guede
  • data mining [11] presentation
  • pruning con reinforcement learning [12] presentation

• Israel Rebollo
  • fuzzy random forests [13] review

• Darya Chyzhyk
  • incremental ensembles [14] |---Slides
  • subspace projections [15] |---Slides, [16] |---Slides

• Elsa Fernandez
  • seleccion de variables usando RF [17] Slides
  • diversidad [18] Slides, [19]

• Maite Termenon
  • varianza residual [20] Slides
  • streaming random forests [21] Slides
  • theoretical study [22] Slides

• Ramón Moreno
  • overfitting cautious [23] Slides
  • aplicaciones [24] Slides

• Miguel A. Veganzones
  • gene functional inference [25] intro slides
  • rotation forests [26] intro slides

• Ion Marques
  • ensembles from fuzzy clustering [27] presentation
  • action detection [28] presentation

• Eider Sanchez
  • dynamic ensemble [29] presentacion dynamic
  • aplicaciones generales [30] presentacion aplicaciones

• Alexandre Savio:
  • Ting Agregacion de subespacios de features [31] -- > no llega late slides
  • comparison [32] slides slides_sinrefs
  • breiman [33] slides slides_sinrefs

referencias

• Groupware general [34]

• Breiman, el padre de la criatura, bagging [35], random forests [36]. Groupware [37]

• tutorial de Criminisi [38], slides [39], pagina personal [40]

• Kuncheva [41], [42], [43], [44], [45], [46], [47], [48], [49]

aplicaciones [50]

• analisis de accidentes [51]
• ingenieria mecanica [52]
• ingenieria financiera [53], [54], [55], [56], [57], [58], [59], [60], [61], [62]

• modelos de lenguage [63], [64], [65],

• biologicas, medicas y ecologicas [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], genomics [77], [78], [79], [80], breast cancer [81], [82], [83], cardiac arrythmia [84], [85], [86], [87], soil texture [88], [89], apendicitis [90], pulmones [91], cancer [92], glaucoma [93], [94], colon cells [95], higado [96], piel [97], de todo ?? [98], celulas [99], ultrasonidos [100], mental fatigue [101], cornea [102]

• quimica [103], [104], [105], [106], [107], [108], [109], [110], [111], [112], [113], [114], [115]

• data mining [116],

• neurociencias [117], [118], [119], fMRI [120], [121], [122], [123], [124], [125], [126], brain extraction [127]

• imagen de reconocimiento remoto, remote sensing, [128], [129], [130], [131], [132], land slides [133], [134], [135], [136], [137], hypespectral data [138], [139], SAR [140]

• pattern recognition [141], [142], biometric data [143], hadwritng [144], signature [145], objetos y acciones [146], [147], [148], visual concept [149], face and action [150]

• intrusion detection [151]