Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part II /
| Autor Corporativo: | |
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| Otros Autores: | , , , , |
| Formato: | eBook |
| Lenguaje: | English |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2017.
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| Edición: | 1st ed. 2017. |
| Colección: | Lecture Notes in Artificial Intelligence ;
10535 |
| Materias: |
Tabla de Contenidos:
- 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.