A General Framework for Feature Selection Under Orthogonal Regression With Global Redundancy Minimization
A High Performance Concurrency Protocol for Smart Contracts of Permissioned Blockchain
A New Belief-Based Incomplete Pattern Unsupervised Classification Method
A Novel Probabilistic Label Enhancement Algorithm for Multi-Label Distribution Learning
A Semantic Network Encoder for Associated Fact Prediction
A Unified Collaborative Representation Learning for Neural-Network Based Recommender Systems
Achieving Privacy-Preserving and Lightweight Truth Discovery in Mobile Crowdsensing
An Integrated Multi-Task Model for Fake News Detection
An Online Offline Framework for Anomaly Scoring and Detecting New Traffic in Network Streams
An Unsupervised Bayesian Neural Network for Truth Discovery in Social Networks
Attentive Representation Learning With Adversarial Training for Short Text Clustering
Auditing Network Embedding: An Edge Influence Based Approach
Context-Aware Service Recommendation Based on Knowledge Graph Embedding
CPiX: Real-Time Analytics Over Out-of-Order Data Streams by Incremental Sliding-Window Aggregation
Deep Bayesian Active Learning for Learning to Rank: A Case Study in Answer Selection
Density-Based Top-K Spatial Textual Clusters Retrieval
Differentially Private Triangle Counting in Large Graphs
Discovering Structural Errors From Business Process Event Logs
Efficient and Effective Multi-Modal Queries Through Heterogeneous Network Embedding
Efficient Sink-Reachability Analysis via Graph Reduction
Erasable Virtual HyperLogLog for Approximating Cumulative Distribution over Data Streams
Estimating the Total Volume of Queries to a Search Engine
Fast Error-Bounded Distance Distribution Computation
GPSC: A Grid-Based Privacy-Reserving Framework for Online Spatial Crowdsourcing
Imitation Learning of Neural Spatio-Temporal Point Processes
Intention-Aware Sequential Recommendation With Structured Intent Transition
Learning Dynamics and Heterogeneity of Spatial-Temporal Graph Data for Traffic Forecasting
Learning to Solve Task-Optimized Group Search for Social Internet of Things
Modeling Dynamic User Preference via Dictionary Learning for Sequential Recommendation
MOLER: Incorporate Molecule-Level Reward to Enhance Deep Generative Model for Molecule Optimization
Open Named Entity Modeling From Embedding Distribution
Point-of-Interest Recommendation With Global and Local Context
Prediction of Treatment Medicines With Dual Adaptive Sequential Networks
Pre-Training Time-Aware Location Embeddings from Spatial-Temporal Trajectories
Transfer Learning for Dynamic Feature Extraction Using Variational Bayesian Inference
Transferable Feature Selection for Unsupervised Domain Adaptation
Comparing Alternative Route Planning Techniques: A Comparative User Study on Melbourne, Dhaka and Copenhagen Road Networks
