GfKl 2008 - Legos

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Session Mixture Analysis III: Model Fitting, Estimation and Applications 16:50- 17:15 17:15- 17:40 17:40- 18:05 18:05- 18:30 18:30- 18:55 Greselin, Francesca; Ingrassia, Salvatore Neykov, Neyko; Filzmoser, Peter; Neytchev, Plamen Garel, Bernard; Boucharel, Julien; Dewitte, Boris; du Penhoat, Yves (Chair: McLachlan) Room 3 A note on constrained EM algorithms for mixtures of elliptical distributions Robust fitting of mixtures: The approach based on the Trimmed Likelihood Estimator Non-Gaussian nature of ENSO signals and climate shifts: implications for regional studies off the western coast of South America Schlattmann, Peter Comparison of four estimators of the heterogeneity variance for meta-analysis Schiffner, Julia; Weihs, Claus Session Pattern Recognition and Machine Learning III 16:50- 17:15 17:15- 17:40 17:40- 18:05 18:05- 18:30 Localized Classification Using Mixture Models 53 103 48 131 130 (Chair: Hüllermeier) Room 405/6 Wehrens, Ron Supervised Self-Organising Maps and More 160 Worm, Katja; Meffert, Image Based Mail Piece 166 Beate Identification using Unsupervised Learning Barbosa, Rui Pedro; Belo, Orlando Autonomous Forex Trading Agents 9 Chiou, Hua-Kai; Huang, Applying Rough Set Theory to 27 Yong-Ting; Liu, Gia- Constructing Knowledge Base for Shie Critical Military Commodity Management Session Invited Session: PLS Path Modeling 16:50- 17:15 17:15- 17:40 17:40- 18:05 (Chair: Esposito Vinzi) Room 2 Ringle, Christian FIMIX-PLS Segmentation of Data for Path Models with Multiple Endogenous LVs Trinchera, L.; Esposito Vinzi, Vincenzo A Comprehensive Partial Least Squares Approach to Component- Based Structural Equation Modeling Henseler, Jörg Nonlinear Effects in PLS Path Models: A Comparison of Available Approaches − xvi − 120 151 63
18:05- 18:30 Betzin, Jörg Categorical Data in PLS Path modeling Session Microarray Data Analysis 16:50- 17:15 17:15- 17:40 17:40- 18:05 18:05- 18:30 Boulesteix, Anne- Laure; Slawski, Martin Slawski, Martin; Boulesteix, Anne- Laure; Daumer, Martin Scharl, Theresa; Leisch, Friedrich Martin-Magniette, Marie-Laure; Mary- Huard, Tristan; Bérard, Caroline; Robin, Stéphane Session Investments and Capital Markets 16:50- 17:15 17:15- 17:40 17:40- 18:05 18:05- 18:30 Locarek-Junge, Hermann; Mihm, Max 14 (Chair: Benner) Room 6 On optimistic bias in reporting microarray-based classification accuracy 20 'CMA' - Steps in developing a comprehensive R-toolbox for classification with microarray data and other high-dimensional problems 136 Quality-Based Clustering of Functional Data: Applications to Time Course Microarray Data 127 ChIPmix : Mixture model of regressions for ChIP-chip experiment analysis 92 (Chair: Ultsch) Room 4 Fundamental Indexation - testing the concept in the German stock market 86 Ultsch, Alfred Is log ratio a good value for measuring return in stock investments? Klein, Christian; Kundisch, Dennis Bessler, Wolfgang; Holler, Julian Index-Based Investment Vehicles - A Comparative Study for the German DAX Hedge Funds in a Bayesian Asset Allocation Framework: Incorporating Information on market states and manager's ability 19:00 Reception (Building “M1”) − xvii − 154 77 13
Page 1 and 2: GfKl 2008 German Classification Soc
Page 3 and 4: Contents Welcome, v Sponsors, vi Sc
Page 5 and 6: Welcome On behalf of the Helmut-Sch
Page 7 and 8: Scientific Program Committee H.-H.
Page 9 and 10: Thursday, July 17, 15:55-16:35: Sab
Page 11 and 12: Detailed Schedule 13:30- 17:30 Tues
Page 13 and 14: 12:10- 12:35 12:35- 13:00 Mylonas,
Page 15: Session Invited Session: VOC (Chair
Page 19 and 20: Session Statistical Musicology I (C
Page 21 and 22: 12:10- 12:35 13:00- 14:00 van de Ve
Page 23 and 24: 17:30- 17:55 Nalbantov, Georgi Ilko
Page 25 and 26: Session Exploratory Data Analysis I
Page 27 and 28: Session Spatial Planning II (Chair:
Page 29 and 30: Bravo, Cristian; Maldonado, Practic
Page 31 and 32: Herrmann, Lutz; Ultsch, Alfred Stre
Page 33 and 34: Capital of Japan Oosthuizen, Surett
Page 35 and 36: Strobl, Carolin; Leisch, Friedrich
Page 37 and 38: Author Index Abu Assab, Samah 1 Ada
Page 39 and 40: Lamont, Morne 87 Lang, Elmar 126 La
Page 41 and 42: Designing Products Using Quality Fu
Page 43 and 44: WaldIS - a web based reference syst
Page 45 and 46: Segmentation of Neural Tissue Bjoer
Page 47 and 48: Evaluation Criteria for the Constru
Page 49 and 50: Autonomous Forex Trading Agents Rui
Page 51 and 52: Estimating the number of buildings
Page 53 and 54: Hedge Funds in a Bayesian Asset All
Page 55 and 56: Choosing the number of clusters in
Page 57 and 58: The K -INDSCAL Model for Heterogene
Page 59 and 60: HIDDEN MARKOV MODEL BASED CLASSIFIC
Page 61 and 62: Practical experiences from Credit S
Page 63 and 64: Motif-based Classification of Time
Page 65 and 66: A novel approach to construct discr
Page 67 and 68:
Applying Rough Set Theory to Constr
Page 69 and 70:
Extending Multivariate Planing Mari
Page 71 and 72:
Augmenting Model-Based Clustering w
Page 73 and 74:
Mixture Hidden Markov Models in Fin
Page 75 and 76:
Multimodal Performance Analysis of
Page 77 and 78:
Regression-autoregression based clu
Page 79 and 80:
Regression and Classification using
Page 81 and 82:
Validity of images from binary codi
Page 83 and 84:
An Improved Criterion for Clusterin
Page 85 and 86:
Multi-Dimensional Scaling applied t
Page 87 and 88:
Scalable and Incrementally Updated
Page 89 and 90:
Likelihood ratio test for general m
Page 91 and 92:
The Potential of Social Intelligenc
Page 93 and 94:
A note on constrained EM algorithms
Page 95 and 96:
Usage of Artificial Neural Networks
Page 97 and 98:
Classification with Regularized Ker
Page 99 and 100:
Auswertung hochaufgelöster Streuli
Page 101 and 102:
Die präzise und effizienzte Erkenn
Page 103 and 104:
Nonlinear Effects in PLS Path Model
Page 105 and 106:
Strengths and Weaknesses of Ant Col
Page 107 and 108:
On the prognostic value of gene exp
Page 109 and 110:
Rule-Based Learning of Reliable Cla
Page 111 and 112:
Using Cluster Networks to Represent
Page 113 and 114:
Dimensionality Reduction of Similar
Page 115 and 116:
Benchmarking Bicluster Algorithms S
Page 117 and 118:
Indexnachbildende Wertpapiere - Ein
Page 119 and 120:
Exploiting synergetic and redundant
Page 121 and 122:
Multivariate comparative analysis o
Page 123 and 124:
An application of copula functions
Page 125 and 126:
Bayesian Methods for Graph Clusteri
Page 127 and 128:
Identifying Atypical Cases in Kerne
Page 129 and 130:
Applying Statistical Models and Par
Page 131 and 132:
Exploring the Interaction Structure
Page 133 and 134:
Clustering of High-Dimensional Data
Page 135 and 136:
Optimization Methods with Evolution
Page 137 and 138:
Deviant box and dual clusters for t
Page 139 and 140:
Predictive classification trees Ulr
Page 141 and 142:
Support Vector Machines in the Dual
Page 143 and 144:
Robust fitting of mixtures: The app
Page 145 and 146:
Multi-Class Extension of Verifiable
Page 147 and 148:
Variable Selection for kernel class
Page 149 and 150:
Clustering and Dimensionality Reduc
Page 151 and 152:
Begriffsanalytischer Ansatz zur qua
Page 153 and 154:
Testing distribution in errors in v
Page 155 and 156:
Bagging with different split criter
Page 157 and 158:
Dynamic disturbances in BTA deephol
Page 159 and 160:
Automatic Dictionary Expansion Usin
Page 161 and 162:
Extreme unconditional dependence vs
Page 163 and 164:
Cluster ensemble based on co-occurr
Page 165 and 166:
��
Page 167 and 168:
Quality-Based Clustering of Functio
Page 169 and 170:
Localized Logistic Regression for D
Page 171 and 172:
Comparison of four estimators of th
Page 173 and 174:
Age Distributions for costs in drug
Page 175 and 176:
Time Related Features for Alarm Cla
Page 177 and 178:
Generating Collective Intelligence
Page 179 and 180:
Trust as a Key Determinant of Loyal
Page 181 and 182:
Clustering Association Rules with F
Page 183 and 184:
A New, Conditional Variable Importa
Page 185 and 186:
Optimal VDSL Expansion taking into
Page 187 and 188:
Mining ideas from textual informati
Page 189 and 190:
Multilevel Simultaneous Component A
Page 191 and 192:
A Comprehensive Partial Least Squar
Page 193 and 194:
Comparison of Algorithms to find di
Page 195 and 196:
Mosaic Plots and Knowledge Structur
Page 197 and 198:
Selection of items for tests and qu
Page 199 and 200:
Clustering Consumers with Respect t
Page 201 and 202:
Multi-Item Versus Single-Item Measu
Page 203 and 204:
Clustering with Repulsive Prototype
Page 205 and 206:
Analysis of massive emigration from
Page 207 and 208:
Factor Analysis of Incomplete Disju
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