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17th PKDD / 24th ECML 2013: Prague, Czech Republic
- Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part III. Lecture Notes in Computer Science 8190, Springer 2013, ISBN 978-3-642-40993-6
Ensembles
- Baidya Nath Saha, Gautam Kunapuli, Nilanjan Ray, Joseph A. Maldjian, Sriraam Natarajan:
AR-Boost: Reducing Overfitting by a Robust Data-Driven Regularization Strategy. 1-16 - Indraneel Mukherjee, Kevin Robert Canini, Rafael M. Frongillo, Yoram Singer:
Parallel Boosting with Momentum. 17-32 - Houman Abbasian, Chris Drummond, Nathalie Japkowicz, Stan Matwin:
Inner Ensembles: Using Ensemble Methods Inside the Learning Algorithm. 33-48
Statistical Learning
- Xiong Li, Bin Wang, Yuncai Liu, Tai Sing Lee:
Learning Discriminative Sufficient Statistics Score Space for Classification. 49-64 - Constantinos Panagiotakopoulos, Petroula Tsampouka:
The Stochastic Gradient Descent for the Primal L1-SVM Optimization Revisited. 65-80 - Yatao Bian, Xiong Li, Mingqi Cao, Yuncai Liu:
Bundle CDN: A Highly Parallelized Approach for Large-Scale ℓ1-Regularized Logistic Regression. 81-95 - Kostiantyn Antoniuk, Vojtech Franc, Václav Hlavác:
MORD: Multi-class Classifier for Ordinal Regression. 96-111 - Manfred Jaeger:
Identifiability of Model Properties in Over-Parameterized Model Classes. 112-127
Semi-supervised Learning
- Bhavana Bharat Dalvi, William W. Cohen, Jamie Callan:
Exploratory Learning. 128-143 - P. K. Srijith, Shirish K. Shevade, S. Sundararajan:
Semi-supervised Gaussian Process Ordinal Regression. 144-159 - Celso André R. de Sousa, Solange O. Rezende, Gustavo E. A. P. A. Batista:
Influence of Graph Construction on Semi-supervised Learning. 160-175 - Kai-Wei Chang, S. Sundararajan, S. Sathiya Keerthi:
Tractable Semi-supervised Learning of Complex Structured Prediction Models. 176-191 - Behnam Babagholami-Mohamadabadi, Ali Zarghami, Mohammadreza Zolfaghari, Mahdieh Soleymani Baghshah:
PSSDL: Probabilistic Semi-supervised Dictionary Learning. 192-207
Unsupervised Learning
- Wenchao Yu, Guangxiang Zeng, Ping Luo, Fuzhen Zhuang, Qing He, Zhongzhi Shi:
Embedding with Autoencoder Regularization. 208-223 - Yinjie Huang, Cong Li, Michael Georgiopoulos, Georgios C. Anagnostopoulos:
Reduced-Rank Local Distance Metric Learning. 224-239 - Shu Kong, Donghui Wang:
Learning Exemplar-Represented Manifolds in Latent Space for Classification. 240-255 - Max Vladymyrov, Miguel Á. Carreira-Perpiñán:
Locally Linear Landmarks for Large-Scale Manifold Learning. 256-271
Subgroup Discovery, Outlier Detection and Anomaly Detection
- Matthijs van Leeuwen, Antti Ukkonen:
Discovering Skylines of Subgroup Sets. 272-287 - Florian Lemmerich, Martin Becker, Frank Puppe:
Difference-Based Estimates for Generalization-Aware Subgroup Discovery. 288-303 - Xuan-Hong Dang, Barbora Micenková, Ira Assent, Raymond T. Ng:
Local Outlier Detection with Interpretation. 304-320 - Marco Stolpe, Kanishka Bhaduri, Kamalika Das, Katharina Morik:
Anomaly Detection in Vertically Partitioned Data by Distributed Core Vector Machines. 321-336 - Didi Surian, Sanjay Chawla:
Mining Outlier Participants: Insights Using Directional Distributions in Latent Models. 337-352
Privacy and Security
- Giorgos Poulis, Grigorios Loukides, Aris Gkoulalas-Divanis, Spiros Skiadopoulos:
Anonymizing Data with Relational and Transaction Attributes. 353-369 - Michael Kamp, Christine Kopp, Michael Mock, Mario Boley, Michael May:
Privacy-Preserving Mobility Monitoring Using Sketches of Stationary Sensor Readings. 370-386 - Battista Biggio, Igino Corona, Davide Maiorca, Blaine Nelson, Nedim Srndic, Pavel Laskov, Giorgio Giacinto, Fabio Roli:
Evasion Attacks against Machine Learning at Test Time. 387-402
Data Mining and Constraint Solving
- Saïd Jabbour, Lakhdar Sais, Yakoub Salhi:
The Top-k Frequent Closed Itemset Mining Using Top-k SAT Problem. 403-418 - Thi-Bich-Hanh Dao, Khanh-Chuong Duong, Christel Vrain:
A Declarative Framework for Constrained Clustering. 419-434 - Marco Collautti, Yuri Malitsky, Deepak Mehta, Barry O'Sullivan:
SNNAP: Solver-Based Nearest Neighbor for Algorithm Portfolios. 435-450
Evaluation
- Kendrick Boyd, Kevin H. Eng, C. David Page Jr.:
Area under the Precision-Recall Curve: Point Estimates and Confidence Intervals. 451-466
Applications
- Xiaomin Xu, Yiqi Lu, Sheng Huang, Yanghua Xiao, Wei Wang:
Incremental Sensor Placement Optimization on Water Network. 467-482 - Xian Wu, Ziming Feng, Wei Fan, Jing Gao, Yong Yu:
Detecting Marionette Microblog Users for Improved Information Credibility. 483-498 - Gideon Dror, Yoelle Maarek, Idan Szpektor:
Will My Question Be Answered? Predicting "Question Answerability" in Community Question-Answering Sites. 499-514 - Tong Wang, Cynthia Rudin, Daniel Wagner, Rich Sevieri:
Learning to Detect Patterns of Crime. 515-530 - Fábio Pinto, Carlos Soares:
Space Allocation in the Retail Industry: A Decision Support System Integrating Evolutionary Algorithms and Regression Models. 531-546
Medical Applications
- Jeremy C. Weiss, David Page:
Forest-Based Point Process for Event Prediction from Electronic Health Records. 547-562 - Yin Song, Jian Zhang, Longbing Cao, Morgan Sangeux:
On Discovering the Correlated Relationship between Static and Dynamic Data in Clinical Gait Analysis. 563-578 - Ping Zhang, Pankaj Agarwal, Zoran Obradovic:
Computational Drug Repositioning by Ranking and Integrating Multiple Data Sources. 579-594 - Houssam Nassif, Finn Kuusisto, Elizabeth S. Burnside, David Page, Jude W. Shavlik, Vítor Santos Costa:
Score As You Lift (SAYL): A Statistical Relational Learning Approach to Uplift Modeling. 595-611
Nectar Track
- Tijl De Bie, Eirini Spyropoulou:
A Theoretical Framework for Exploratory Data Mining: Recent Insights and Challenges Ahead. 612-616 - Maximilian Nickel, Volker Tresp:
Tensor Factorization for Multi-relational Learning. 617-621 - Myra Spiliopoulou, Eirini Ntoutsi, Yannis Theodoridis, René Schult:
MONIC and Followups on Modeling and Monitoring Cluster Transitions. 622-626 - Jan Peters, Jens Kober, Katharina Mülling, Oliver Krömer, Gerhard Neumann:
Towards Robot Skill Learning: From Simple Skills to Table Tennis. 627-631 - Irina Rish:
Functional MRI Analysis with Sparse Models. 632-636
Demo Track
- Nenad Tomasev, Dunja Mladenic:
Image Hub Explorer: Evaluating Representations and Metrics for Content-Based Image Retrieval and Object Recognition. 637-640 - Fabrice Lauri, Nicolas Gaud, Stéphane Galland, Vincent Hilaire:
Ipseity - A Laboratory for Synthesizing and Validating Artificial Cognitive Systems in Multi-agent Systems. 641-644 - Jan N. van Rijn, Bernd Bischl, Luís Torgo, Bo Gao, Venkatesh Umaashankar, Simon Fischer, Patrick Winter, Bernd Wiswedel, Michael R. Berthold, Joaquin Vanschoren:
OpenML: A Collaborative Science Platform. 645-649 - Borut Sluban, Nada Lavrac:
ViperCharts: Visual Performance Evaluation Platform. 650-653 - Milan Dojchinovski, Tomás Kliegr:
Entityclassifier.eu: Real-Time Classification of Entities in Text with Wikipedia. 654-658 - Nikos Pelekis, Christos Ntrigkogias, Panagiotis Tampakis, Stylianos Sideridis, Yannis Theodoridis:
Hermoupolis: A Trajectory Generator for Simulating Generalized Mobility Patterns. 659-662 - Michele Berlingerio, Francesco Calabrese, Giusy Di Lorenzo, Rahul Nair, Fabio Pinelli, Marco Luca Sbodio:
AllAboard: A System for Exploring Urban Mobility and Optimizing Public Transport Using Cellphone Data. 663-666 - Daniil Mirylenka, Andrea Passerini:
ScienScan - An Efficient Visualization and Browsing Tool for Academic Search. 667-671 - Daniel Paurat, Thomas Gärtner:
InVis: A Tool for Interactive Visual Data Analysis. 672-676 - Ioana Hulpus, Conor Hayes, Marcel Karnstedt, Derek Greene, Marek Jozwowicz:
Kanopy: Analysing the Semantic Network around Document Topics. 677-680 - Antoine Adam, Hendrik Blockeel, Sander Govers, Abram Aertsen:
SCCQL : A Constraint-Based Clustering System. 681-684 - Kendrick Boyd, Kevin H. Eng, C. David Page Jr.:
Erratum: Area under the Precision-Recall Curve: Point Estimates and Confidence Intervals.
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