Giuseppe Manco

Latest

• Boosting Cyber-Threat Intelligence via Collaborative Intrusion Detection
• A Factorization Approach for Survival Analysis on Diffusion Networks
• Adversarial Regularized Reconstruction for Anomaly Detection and Generation
• Machine learning methods for generating high dimensional discrete datasets
• Hyper-Parameter Optimization for Latent Spaces in Dynamic Recommender Systems
• Learning Ideological Embeddings from Information Cascades
• Using an autoencoder in the design of an anomaly detector for smart manufacturing
• Sequential Variational Autoencoders for Collaborative Filtering
• Predicting Temporal Activation Patterns via Recurrent Neural Networks
• Fault detection and explanation through big data analysis on sensor streams
• Differential Privacy and Neural Networks: A Preliminary Analysis
• Survival Factorization on Diffusion Networks
• Efficient Methods for Influence-Based Network-Oblivious Community Detection
• Rialto: A Knowledge Discovery suite for data analysis
• How Can SMEs Benefit from Big Data? Challenges and a Path Forward
• Outlying property detection with numerical attributes
• Probabilistic Approaches to Recommendations
• A Generative Bayesian Model for Item and User Recommendation in Social Rating Networks with Trust Relationships
• Who to follow and why
• Influence-Based Network-Oblivious Community Detection
• Dealing with trajectory streams by clustering and mathematical transforms
• Probabilistic topic models for sequence data
• Topic-aware social influence propagation models
• Hierarchical clustering of XML documents focused on structural components
• Cascade-based community detection
• Topic-Aware Social Influence Propagation Models
• Balancing Prediction and Recommendation Accuracy: Hierarchical Latent Factors for Preference Data
• Probabilistic Sequence Modeling for Recommender Systems
• From global to local and viceversa: uses of associative rule learning for classification in imprecise environments
• A Probabilistic Hierarchical Approach for Pattern Discovery in Collaborative Filtering Data
• An Analysis of Probabilistic Methods for Top-N Recommendation in Collaborative Filtering
• Modeling item selection and relevance for accurate recommendations
• An incremental clustering scheme for data de-duplication
• Mining unconnected patterns in workflows
• Boosting text segmentation via progressive classification
• Exploiting structural similarity for effective Web information extraction
• Mining categories for emails via clustering and pattern discovery