icdm 2019 论文列表
2019 IEEE International Conference on Data Mining, ICDM 2019, Beijing, China, November 8-11, 2019.
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ICDM 2019 Knowledge Graph Contest: Team UWA.
Automatic Knowledge Graph Construction: A Report on the 2019 ICDM/ICBK Contest.
Relation Structure-Aware Heterogeneous Graph Neural Network.
A Model-Agnostic Approach for Explaining the Predictions on Clustered Data.
ADMIRING: Adversarial Multi-network Mining.
Inquiry Spam Detection via Jointly Exploiting Temporal-Categorical Behavior and Linguistics.
Constrained Matrix Factorization for Course Score Prediction.
Elastic Bulk Synchronous Parallel Model for Distributed Deep Learning.
Collective Protection: Preventing Sensitive Inferences via Integrative Transformation.
KnowRisk: An Interpretable Knowledge-Guided Model for Disease Risk Prediction.
Generation of Low Distortion Adversarial Attacks via Convex Programming.
Unveiling Taxi Drivers' Strategies via cGAIL: Conditional Generative Adversarial Imitation Learning.
TrafficGAN: Off-Deployment Traffic Estimation with Traffic Generative Adversarial Networks.
Discovering Relevant Reviews for Answering Product-Related Queries.
Fast Sparse Coding Inference with Historical Information.
Dynamic News Recommendation with Hierarchical Attention Network.
Learning Attentional Temporal Cues of Brainwaves with Spatial Embedding for Motion Intent Detection.
Learning Review Representations from user and Product Level Information for Spam Detection.
EDiT: Interpreting Ensemble Models via Compact Soft Decision Trees.
ACE: Adaptively Similarity-Preserved Representation Learning for Individual Treatment Effect Estimation.
Scene Text Recognition with Auto-Aligned Feature Generator.
On the Robust Splitting Criterion of Random Forest.
From Joint Feature Selection and Self-Representation Learning to Robust Multi-view Subspace Clustering.
MIX: A Joint Learning Framework for Detecting Both Clustered and Scattered Outliers in Mixed-Type Data.
Adaptive Neural Network for Node Classification in Dynamic Networks.
Deep Technology Tracing for High-Tech Companies.
Collaborative Label Correction via Entropy Thresholding.
Personalized Neural Usefulness Network for Rating Prediction.
Learning Robust Representations with Graph Denoising Policy Network.
TMDA: Task-Specific Multi-source Domain Adaptation via Clustering Embedded Adversarial Training.
Competitive Multi-agent Deep Reinforcement Learning with Counterfactual Thinking.
Learning to Hash for Efficient Search Over Incomplete Knowledge Graphs.
Fast Classification Algorithms via Distributed Accelerated Alternating Direction Method of Multipliers.
Fast Semantic Preserving Hashing for Large-Scale Cross-Modal Retrieval.
Adaptive Teacher-and-Student Model for Heterogeneous Domain Adaptation.
Curve Fitting from Probabilistic Emissions and Applications to Dynamic Item Response Theory.
Permutation Strategies for Mining Significant Sequential Patterns.
User Response Driven Content Understanding with Causal Inference.
An Arm-Wise Randomization Approach to Combinatorial Linear Semi-Bandits.
Space-Efficient Feature Maps for String Alignment Kernels.
Multi-graph Convolution Collaborative Filtering.
Nearest Neighbor Classifiers Versus Random Forests and Support Vector Machines.
On Privacy of Socially Contagious Attributes.
Dual Adversarial Learning Based Network Alignment.
An Integrated Multimodal Attention-Based Approach for Bank Stress Test Prediction.
Efficient Mining and Exploration of Multiple Axis-Aligned Intersecting Objects.
Efficient Bayesian Optimization for Uncertainty Reduction Over Perceived Optima Locations.
Recognizing Variables from Their Data via Deep Embeddings of Distributions.
Deep Embedded Cluster Tree.
Discovering Reliable Correlations in Categorical Data.
Triple-Shapelet Networks for Time Series Classification.
I-CARS: An Interactive Context-Aware Recommender System.
Learning Local and Global Multi-context Representations for Document Classification.
Spatio-Temporal GRU for Trajectory Classification.
What is the Value of Experimentation & Measurement?
First Index-Free Manifold Ranking-Based Image Retrieval with Output Bound.
Predicting Water Quality for the Woronora Delivery Network with Sparse Samples.
Consistency Meets Inconsistency: A Unified Graph Learning Framework for Multi-view Clustering.
Mining Maximal Clique Summary with Effective Sampling.
Contrast Feature Dependency Pattern Mining for Controlled Experiments with Application to Driving Behavior.
Dense Semantic Matching Network for Multi-turn Conversation.
To Be or Not to Be: Analyzing & Modeling Social Recommendation in Online Social Networks.
SENTI2POP: Sentiment-Aware Topic Popularity Prediction on Social Media.
Transfer Metric Learning for Unseen Domains.
Iterative Graph Alignment via Supermodular Approximation.
Matrix Profile XV: Exploiting Time Series Consensus Motifs to Find Structure in Time Series Sets.
Discovering Robustly Connected Subgraphs with Simple Descriptions.
Network Identification and Authentication.
Block-Structured Optimization for Anomalous Pattern Detection in Interdependent Networks.
Multi-view Outlier Detection in Deep Intact Space.
CSNN: Contextual Sentiment Neural Network.
Semi-Supervised Adversarial Domain Adaptation for Seagrass Detection in Multispectral Images.
Unsupervised Qualitative Scoring for Binary Item Features.
Constructing Educational Concept Maps with Multiple Relationships from Multi-Source Data.
A Distributed Fair Machine Learning Framework with Private Demographic Data Protection.
Deep-Aligned Convolutional Neural Network for Skeleton-Based Action Recognition and Segmentation.
Deep Reinforcement Learning for Multi-driver Vehicle Dispatching and Repositioning Problem.
Diversity-Aware Recommendation by User Interest Domain Coverage Maximization.
Improving Disentangled Representation Learning with the Beta Bernoulli Process.
A Weighted Aggregating SGD for Scalable Parallelization in Deep Learning.
Quantized Adversarial Training: An Iterative Quantized Local Search Approach.
Fair Adversarial Gradient Tree Boosting.
An Integrated Model for Urban Subregion House Price Forecasting: A Multi-source Data Perspective.
DRCGR: Deep Reinforcement Learning Framework Incorporating CNN and GAN-Based for Interactive Recommendation.
DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums.
CAMP: Co-Attention Memory Networks for Diagnosis Prediction in Healthcare.
Intervention-Aware Early Warning.
Optimal Timelines for Network Processes.
A Factorized Version Space Algorithm for "Human-In-the-Loop" Data Exploration.
Inductive Embedding Learning on Attributed Heterogeneous Networks via Multi-task Sequence-to-Sequence Learning.
Counterfactual Attention Supervision.
Alpha-Beta Sampling for Pairwise Ranking in One-Class Collaborative Filtering.
Session-Based Recommendation with Local Invariance.
AMENDER: An Attentive and Aggregate Multi-layered Network for Dataset Recommendation.
Scalable Explanation of Inferences on Large Graphs.
VASE: A Twitter-Based Vulnerability Analysis and Score Engine.
Nearest Neighbor Ensembles: An Effective Method for Difficult Problems in Streaming Classification with Emerging New Classes.
A Wasserstein Subsequence Kernel for Time Series.
Efficient Approximate Solution Path Algorithm for Order Weight L_1-Norm with Accuracy Guarantee.
MTEX-CNN: Multivariate Time Series EXplanations for Predictions with Convolutional Neural Networks.
ChainNet: Learning on Blockchain Graphs with Topological Features.
Matrix Profile XVIII: Time Series Mining in the Face of Fast Moving Streams using a Learned Approximate Matrix Profile.
Adversarial Robustness of Similarity-Based Link Prediction.
Rank-Based Multi-task Learning for Fair Regression.
A Parallel Simulated Annealing Enhancement of the Optimal-Matching Heuristic for Ridesharing.
Know Your Mind: Adaptive Cognitive Activity Recognition with Reinforced CNN.
Aftershock Detection with Multi-scale Description Based Neural Network.
HiGitClass: Keyword-Driven Hierarchical Classification of GitHub Repositories.
Boosted Trajectory Calibration for Traffic State Estimation.
Machine Comprehension-Incorporated Relevance Matching.
Adaptive Structure-Constrained Robust Latent Low-Rank Coding for Image Recovery.
Learning Structured Twin-Incoherent Twin-Projective Latent Dictionary Pairs for Classification.
Generalized Adversarial Training in Riemannian Space.
PERCeIDs: PERiodic CommunIty Detection.
Learning Hierarchical and Shared Features for Improving 3D Neuron Reconstruction.
Jointly Embedding the Local and Global Relations of Heterogeneous Graph for Rumor Detection.
Mining Audio, Text and Visual Information for Talking Face Generation.
Transfer Learning with Dynamic Adversarial Adaptation Network.
Generating Reliable Friends via Adversarial Training to Improve Social Recommendation.
Self-Attentive Attributed Network Embedding Through Adversarial Learning.
Fast LSTM Inference by Dynamic Decomposition on Cloud Systems.
Domain Knowledge Guided Deep Learning with Electronic Health Records.
Automatic Generation of Medical Imaging Diagnostic Report with Hierarchical Recurrent Neural Network.
Identifying High Potential Talent: A Neural Network Based Dynamic Social Profiling Approach.
Discrete Overlapping Community Detection with Pseudo Supervision.
Neural Embedding Propagation on Heterogeneous Networks.
VSB-DVM: An End-to-End Bayesian Nonparametric Generalization of Deep Variational Mixture Model.
Social Trust Network Embedding.
Privacy-Preserving Auto-Driving: A GAN-Based Approach to Protect Vehicular Camera Data.
Discriminative Regularized Deep Generative Models for Semi-Supervised Learning.
Domain-Adversarial Graph Neural Networks for Text Classification.
XOR-Based Boolean Matrix Decomposition.
A Coarse-to-Fine Multi-stream Hybrid Deraining Network for Single Image Deraining.
DeepTrust: A Deep User Model of Homophily Effect for Trust Prediction.
DMFP: A Dynamic Multi-faceted Fine-Grained Preference Model for Recommendation.
A Semi-Supervised Graph Attentive Network for Financial Fraud Detection.
Generative Correlation Discovery Network for Multi-label Learning.
Towards Making Deep Transfer Learning Never Hurt.
M-estimation in Low-Rank Matrix Factorization: A General Framework.
Modeling Graphs with Vertex Replacement Grammars.
Reinforced Molecule Generation with Heterogeneous States.
Learning to Sample: An Active Learning Framework.
Personalized Knowledge Graph Summarization: From the Cloud to Your Pocket.
Exploiting Multi-domain Visual Information for Fake News Detection.
Efficient Sketching Algorithm for Sparse Binary Data.
Temporal Self-Attention Network for Medical Concept Embedding.
Sharp Characterization of Optimal Minibatch Size for Stochastic Finite Sum Convex Optimization.
RiWalk: Fast Structural Node Embedding via Role Identification.
Matching Novelty While Training: Novel Recommendation Based on Personalized Pairwise Loss Weighting.
Performing Co-membership Attacks Against Deep Generative Models.
Cross-Modal Zero-Shot Hashing.
Exploring Semantic Relationships for Image Captioning without Parallel Data.
Guiding Cross-lingual Entity Alignment via Adversarial Knowledge Embedding.
One-Stage Deep Instrumental Variable Method for Causal Inference from Observational Data.
Learning a Low-Rank Tensor of Pharmacogenomic Multi-relations from Biomedical Networks.
Learning Classifiers on Positive and Unlabeled Data with Policy Gradient.
Classify EEG and Reveal Latent Graph Structure with Spatio-Temporal Graph Convolutional Neural Network.
HierCon: Hierarchical Organization of Technical Documents Based on Concepts.
Collaborative Distillation for Top-N Recommendation.
Multi-hop Knowledge Base Question Answering with an Iterative Sequence Matching Model.
Computing Optimal Assignments in Linear Time for Approximate Graph Matching.
Forest Distance Closeness Centrality in Disconnected Graphs.
Matrix Profile XIX: Time Series Semantic Motifs: A New Primitive for Finding Higher-Level Structure in Time Series.
Bi-directional Causal Graph Learning through Weight-Sharing and Low-Rank Neural Network.
Online Budgeted Least Squares with Unlabeled Data.
Multi-aspect Mining of Complex Sensor Sequences.
Distribution of Node Embeddings as Multiresolution Features for Graphs.
Discriminatively Relabel for Partial Multi-label Learning.
Interpretable Feature Learning of Graphs using Tensor Decomposition.
Efficient Data Representation by Selecting Prototypes with Importance Weights.
Deep Multi-attributed Graph Translation with Node-Edge Co-Evolution.
Streaming Random Patches for Evolving Data Stream Classification.
Tabular Cell Classification Using Pre-Trained Cell Embeddings.
Discovering Subdimensional Motifs of Different Lengths in Large-Scale Multivariate Time Series.
Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text.
DCMN: Double Core Memory Network for Patient Outcome Prediction with Multimodal Data.
Large-Scale Personalized Delivery for Guaranteed Display Advertising with Real-Time Pacing.
Modeling Engagement Dynamics of Online Discussions using Relativistic Gravitational Theory.
Improving Spectral Clustering with Deep Embedding and Cluster Estimation.
Beyond Geo-First Law: Learning Spatial Representations via Integrated Autocorrelations and Complementarity.
Learning Credible Deep Neural Networks with Rationale Regularization.
Reinforcement Learning Based Monte Carlo Tree Search for Temporal Path Discovery.
Closed Form Word Embedding Alignment.
Learning Dynamic Author Representations with Temporal Language Models.
MUSE-RNN: A Multilayer Self-Evolving Recurrent Neural Network for Data Stream Classification.
Generative Oversampling with a Contrastive Variational Autoencoder.
Automatic Clustering by Detecting Significant Density Dips in Multiple Dimensions.
Preference Relationship-Based CrossCMN Scheme for Answer Ranking in Community QA.
Neural Feature Search: A Neural Architecture for Automated Feature Engineering.
InBEDE: Integrating Contextual Bandit with TD Learning for Joint Pricing and Dispatch of Ride-Hailing Platforms.
NVSRN: A Neural Variational Scaling Reasoning Network for Initiative Response Generation.
Supervised Class Distribution Learning for GANs-Based Imbalanced Classification.
An Efficient Policy Gradient Method for Conditional Dialogue Generation.
CUDA: Contradistinguisher for Unsupervised Domain Adaptation.
Dataset Recommendation via Variational Graph Autoencoder.
Collaborative Graph Walk for Semi-Supervised Multi-label Node Classification.
