Machine learning and knowledge discovery in databases. European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings /: European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings. Part II : (2017)

• Record Type: Book
• Other Titles: ECML PKDD 2017
• Further Information: Note: Michelangelo Ceci, Jaakko Hollmén, Ljupčo Todorovski, Celine Vens, Sašo Džeroski (eds.).
• Editors: Ceci, Michelangelo; Hollmén, Jaakko; Todorovski, Ljupčo, 1969-; Vens, Celine; Džeroski, Sašo, 1968-
• Other Names: ECML PKDD (Conference)
• Contents: Pattern and Sequence Mining -- BeatLex: Summarizing and Forecasting Time Series with Patterns -- Behavioral Constraint Template-Based Sequence Classification -- Efficient Sequence Regression by Learning Linear Models in All-Subsequence Space -- Subjectively Interesting Connecting Trees -- Privacy and Security -- Malware Detection by Analysing Encrypted Network Traffic with Neural Networks -- PEM: Practical Differentially Private System for Large-Scale Cross-Institutional Data Mining -- Probabilistic Models and Methods -- Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources -- Bayesian Inference for Least Squares Temporal Difference Regularization -- Discovery of Causal Models that Contain Latent Variables through Bayesian Scoring of Independence Constraints -- Labeled DBN learning with community structure knowledge -- Multi-view Generative Adversarial Networks -- Online Sparse Collapsed Hybrid Variational-Gibbs Algorithm for Hierarchical Dirichlet Process Topic Models -- PAC-Bayesian Analysis for a two-step Hierarchical Multiview Learning Approach -- Partial Device Fingerprints -- Robust Multi-view Topic Modeling by Incorporating Detecting Anomalies -- Recommendation -- A Regularization Method with Inference of Trust and Distrust in Recommender Systems -- A Unified Contextual Bandit Framework for Long- and Short-Term Recommendations -- Perceiving the Next Choice with Comprehensive Transaction Embeddings for Online Recommendation -- Regression -- Adaptive Skip-Train Structured Regression for Temporal Networks -- ALADIN: A New Approach for Drug-Target Interaction Prediction -- Co-Regularised Support Vector Regression -- Online Regression with Controlled Label Noise Rate -- Reinforcement Learning -- Generalized Inverse Reinforcement Learning with Linearly Solvable MDP -- Max K-armed bandit: On the ExtremeHunter algorithm and beyond -- Variational Thompson Sampling for Relational Recurrent Bandits -- Subgroup Discovery -- Explaining Deviating Subsets through Explanation Networks -- Flash points: Discovering exceptional pairwise behaviors in vote or rating data -- Time Series and Streams -- A Multiscale Bezier-Representation for Time Series that Supports Elastic Matching -- Arbitrated Ensemble for Time Series Forecasting -- Cost Sensitive Time-series Classification -- Cost-Sensitive Perceptron Decision Trees for Imbalanced Drifting Data Streams -- Efficient Temporal Kernels between Feature Sets for Time Series Classification -- Forecasting and Granger modelling with non-linear dynamical dependencies -- Learning TSK Fuzzy Rules from Data Streams -- Non-Parametric Online AUC Maximization -- On-line Dynamic Time Warping for Streaming Time Series -- PowerCast: Mining and Forecasting Power Grid Sequences -- UAPD: Predicting Urban Anomalies from Spatial-Temporal Data -- Transfer and Multi-Task Learning -- A Novel Rating Pattern Transfer Model for Improving Non-Overlapping Cross-Domain Collaborative Filtering -- Distributed Multi-task Learning for Sensor Network -- Learning task structure via sparsity grouped multitask learning -- Lifelong Learning with Gaussian Processes -- Personalized Tag Recommendation for Images Using Deep Transfer Learning -- Ranking based Multitask Learning of Scoring Functions -- Theoretical Analysis of Domain Adaptation with Optimal Transport -- TSP: Learning Task-Speci_c Pivots for Unsupervised Domain Adaptation -- Unsupervised and Semisupervised Learning -- k2-means for fast and accurate large scale clustering -- A Simple Exponential Family Framework for Zero-Shot Learning -- DeepCluster: A General Clustering Framework based on Deep Learning -- Multi-view Spectral Clustering on Conflicting Views -- Pivot-based Distributed K-Nearest Neighbor Mining.
• Publisher Details: Cham, Switzerland : Springer
• Publication Date: 2017
• Extent: 1 online resource (xxxiii, 866 pages), illustrations
• Subjects: 006.3/1; Computer science; Machine learning -- Congresses; Data mining -- Congresses; Data mining; Machine learning; Computers -- Intelligence (AI) & Semantics; Computers -- Computer Graphics; Computers -- Information Technology; Computers -- Security -- General; Computers -- Social Aspects -- Human-Computer Interaction; Artificial intelligence; Image processing; Information retrieval; Computer security; Information technology: general issues; Data mining; Artificial intelligence; Computer vision; Computer security; Computers -- Database Management -- Data Mining; Data mining; Electronic books; Conference papers and proceedings
• Languages: English
• ISBNs: 9783319712468; 3319712462
• Related ISBNs: 9783319712451
• Notes: Note: Online resource; title from PDF title page (SpringerLink, viewed January 10, 2018).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.