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Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part II 2013 ed. [Minkštas viršelis]

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  • Formatas: Paperback / softback, 693 pages, aukštis x plotis: 235x155 mm, weight: 1116 g, 160 Illustrations, black and white; XLIV, 693 p. 160 illus., 1 Paperback / softback
  • Serija: Lecture Notes in Artificial Intelligence 8189
  • Išleidimo metai: 12-Sep-2013
  • Leidėjas: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3642409903
  • ISBN-13: 9783642409905
  • Formatas: Paperback / softback, 693 pages, aukštis x plotis: 235x155 mm, weight: 1116 g, 160 Illustrations, black and white; XLIV, 693 p. 160 illus., 1 Paperback / softback
  • Serija: Lecture Notes in Artificial Intelligence 8189
  • Išleidimo metai: 12-Sep-2013
  • Leidėjas: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3642409903
  • ISBN-13: 9783642409905
This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013, held in Prague, Czech Republic, in September 2013. The 111 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 447 submissions. The papers are organized in topical sections on reinforcement learning; Markov decision processes; active learning and optimization; learning from sequences; time series and spatio-temporal data; data streams; graphs and networks; social network analysis; natural language processing and information extraction; ranking and recommender systems; matrix and tensor analysis; structured output prediction, multi-label and multi-task learning; transfer learning; bayesian learning; graphical models; nearest-neighbor methods; ensembles; statistical learning; semi-supervised learning; unsupervised learning; subgroup discovery, outlier detection and anomaly detection; privacy and security; evaluation; applications; and medical applications.
Social Network Analysis
Incremental Local Evolutionary Outlier Detection for Dynamic Social Networks
1(15)
Tengfei Ji
Dongqing Yang
Jun Gao
How Long Will She Call Me? Distribution, Social Theory and Duration Prediction
16(16)
Yuxiao Dong
Jie Tang
Tiancheng Lou
Bin Wu
Nitesh V. Chawla
Discovering Nested Communities
32(16)
Nikolaj Tatti
Aristides Gionis
CSI: Community-Level Social Influence Analysis
48(16)
Yasir Mehmood
Nicola Barbieri
Francesco Bonchi
Antti Ukkonen
Natural Language Processing and Information Extraction
Supervised Learning of Syntactic Contexts for Uncovering Definitions and Extracting Hypernym Relations in Text Databases
64(16)
Guido Boella
Luigi Di Caro
Error Prediction with Partial Feedback
80(15)
William Darling
Cedric Archambeau
Shachar Mirkin
Guillaume Bouchard
Boot-Strapping Language Identifiers for Short Colloquial Postings
95(17)
Moises Goldszmidt
Marc Najork
Stelios Paparizos
Ranking and Recommender Systems
A Pairwise Label Ranking Method with Imprecise Scores and Partial Predictions
112(16)
Sebastien Destercke
Learning Socially Optimal Information Systems from Egoistic Users
128(17)
Karthik Raman
Thorsten Joachims
Socially Enabled Preference Learning from Implicit Feedback Data
145(16)
Julien Delporte
Alexandros Karatzoglou
Tomasz Matuszczyk
Stephane Canu
Cross-Domain Recommendation via Cluster-Level Latent Factor Model
161(16)
Sheng Gao
Hao Luo
Da Chen
Shantao Li
Patrick Gallinari
Jun Guo
Minimal Shrinkage for Noisy Data Recovery Using Schatten-p Norm Objective
177(17)
Deguang Kong
Miao Zhang
Chris Ding
Matrix and Tensor Analysis
Noisy Matrix Completion Using Alternating Minimization
194(16)
Suriya Gunasekar
Ayan Acharya
Neeraj Gaur
Joydeep Ghosh
A Nearly Unbiased Matrix Completion Approach
210(16)
Dehua Liu
Tengfei Zhou
Hui Qian
Congfu Xu
Zhihua Zhang
A Counterexample for the Validity of Using Nuclear Norm as a Convex Surrogate of Rank
226(16)
Hongyang Zhang
Zhouchen Lin
Chao Zhang
Efficient Rank-one Residue Approximation Method for Graph Regularized Non-negative Matrix Factorization
242(14)
Qing Liao
Qian Zhang
Maximum Entropy Models for Iteratively Identifying Subjectively Interesting Structure in Real-Valued Data
256(16)
Kleanthis-Nikolaos Kontonasios
Jilles Vreeken
Tijl De Bie
An Analysis of Tensor Models for Learning on Structured Data
272(16)
Maximilian Nickel
Volker Tresp
Learning Modewise Independent Components from Tensor Data Using Multilinear Mixing Model
288(16)
Haiping Lu
Structured Output Prediction, Multi-label and Multi-task Learning
Taxonomic Prediction with Tree-Structured Covariances
304(16)
Matthew B. Blaschko
Wojciech Zaremba
Arthur Gretton
Position Preserving Multi-Output Prediction
320(16)
Zubin Abraham
Pang-Ning Tan
Perdinan
Julie Winkler
Shiyuan Zhong
Malgorzata Liszewska
Structured Output Learning with Candidate Labels for Local Parts
336(17)
Chengtao Li
Jianwen Zhang
Zheng Chen
Shared Structure Learning for Multiple Tasks with Multiple Views
353(16)
Xin Jin
Fuzhen Zhuang
Shuhui Wang
Qing He
Zhongzhi Shi
Using Both Latent and Supervised Shared Topics for Multitask Learning
369(16)
Ayan Acharya
Aditya Rawal
Raymond J. Mooney
Eduardo R. Hruschka
Probabilistic Clustering for Hierarchical Multi-Label Classification of Protein Functions
385(16)
Rodrigo C. Barros
Ricardo Cerri
Alex A. Freitas
Andre C.P.L.F. de Carvalho
Multi-core Structural SVM Training
401(16)
Kai-Wei Chang
Vivek Srikumar
Dan Roth
Multi-label Classification with Output Kernels
417(16)
Yuhong Guo
Dale Schuurmans
Transfer Learning
Boosting for Unsupervised Domain Adaptation
433(16)
Amaury Habrard
Jean-Philippe Peyrache
Marc Sebban
Automatically Mapped Transfer between Reinforcement Learning Tasks via Three-Way Restricted Boltzmann Machines
449(16)
Haitham Bou Ammar
Decebal Constantin Mocanu
Matthew E. Taylor
Kurt Driessens
Karl Tuyls
Gerhard Weiss
Bayesian Learning
A Layered Dirichlet Process for Hierarchical Segmentation of Sequential Grouped Data
465(18)
Adway Mitra
Ranganath B.N.
Indrajit Bhattacharya
A Bayesian Classifier for Learning from Tensorial Data
483(16)
Wei Liu
Jeffrey Chan
James Bailey
Christopher Leckie
Fang Chen
Kotagiri Ramamohanarao
Prediction with Model-Based Neutrality
499(16)
Kazuto Fukuchi
Jun Sakuma
Toshihiro Kamishima
Decision-Theoretic Sparsification for Gaussian Process Preference Learning
515(16)
M. Ehsan Abbasnejad
Edwin V. Bonilla
Scott Sanner
Variational Hidden Conditional Random Fields with Coupled Dirichlet Process Mixtures
531(17)
Konstantinos Bousmalis
Stefanos Zafeiriou
Louis--Philippe Morency
Maja Pontic
Zoubin Ghahramani
Sparsity in Bayesian Blind Source Separation and Deconvolution
548(16)
Vaclav Smidl
Ondrej Tichy
Nested Hierarchical Dirichlet Process for Nonparametric Entity-Topic Analysis
564(16)
Priyanka Agrawal
Lavanya Sita Tekumalla
Indrajit Bhattacharya
Graphical Models
Knowledge Intensive Learning: Combining Qualitative Constraints with Causal Independence for Parameter Learning in Probabilistic Models
580(16)
Shuo Yang
Sriraam Natarajan
Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation
596(16)
Song Liu
John A. Quinn
Michael U. Gutmann
Masashi Sugiyama
Greedy Part-Wise Learning of Sum-Product Networks
612(16)
Robert Peharz
Bernhard C. Geiger
Franz Pernkopf
From Topic Models to Semi-supervised Learning: Biasing Mixed-Membership Models to Exploit Topic-Indicative Features in Entity Clustering
628(15)
Ramnath Balasubramanyan
Bhavana Dalvi
William W. Cohen
Nearest-Neighbor Methods
Hub Co-occurrence Modeling for Robust High-Dimensional kNN Classification
643(17)
Nenad Tomasev
Dunja Mladenic
Fast kNN Graph Construction with Locality Sensitive Hashing
660(15)
Yan-Ming Zhang
Kaizhu Huang
Guanggang Geng
Cheng-Lin Liu
Mixtures of Large Margin Nearest Neighbor Classifiers
675(14)
Murat Semerci
Ethem Alpaydin
Author Index 689