SIGKDD(KDD) 2018 论文列表
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2018, London, UK, August 19-23, 2018.
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SysML: On System and Algorithm Co-design for Practical Machine Learning.
Data Science and Entertainment Production.
Algorithms, Data, Hardware and Tools: A Perfect Storm.
Planet-Scale Land Cover Classification with FPGAs.
Software 2.0 and Snorkel: Beyond Hand-Labeled Data.
Computational Advertising at Scale.
Building Near Realtime Contextual Recommendations for Active Communities on LinkedIn.
Societal Impact of Data Science and Artificial Intelligence.
Humans, Jobs, and the Economy: The Future of Finance in the Age of Big Data.
The Pinterest Approach to Machine Learning.
Challenges and Innovations in Building a Product Knowledge Graph.
Data Science at Flipkart - An Indian E-Commerce company.
The U.S. Census Bureau Adopts Differential Privacy.
Embedding Temporal Network via Neighborhood Formation.
Adversarial Attacks on Neural Networks for Graph Data.
XiaoIce Band: A Melody and Arrangement Generation Framework for Pop Music.
Deep Variational Network Embedding in Wasserstein Space.
Unlearn What You Have Learned: Adaptive Crowd Teaching with Exponentially Decayed Memory Learners.
SPARC: Self-Paced Network Representation for Few-Shot Rare Category Characterization.
REST: A Reference-based Framework for Spatio-temporal Trajectory Compression.
Prediction-time Efficient Classification Using Feature Computational Dependencies.
Arbitrary-Order Proximity Preserved Network Embedding.
Online Adaptive Asymmetric Active Learning for Budgeted Imbalanced Data.
Discrete Ranking-based Matrix Factorization with Self-Paced Learning.
Trajectory-driven Influential Billboard Placement.
Multi-Label Inference for Crowdsourcing.
TextTruth: An Unsupervised Approach to Discover Trustworthy Information from Multi-Sourced Text Data.
On the Generative Discovery of Structured Medical Knowledge.
StockAssIstant: A Stock AI Assistant for Reliability Modeling of Stock Comments.
TaxoGen: Unsupervised Topic Taxonomy Construction by Adaptive Term Embedding and Clustering.
Simultaneous Urban Region Function Discovery and Popularity Estimation via an Infinite Urbanization Process Model.
Learning and Interpreting Complex Distributions in Empirical Data.
NetWalk: A Flexible Deep Embedding Approach for Anomaly Detection in Dynamic Networks.
Learning Deep Network Representations with Adversarially Regularized Autoencoders.
Safe Triplet Screening for Distance Metric Learning.
Transcribing Content from Structural Images with Spotlight Mechanism.
Model-based Clustering of Short Text Streams.
Multi-User Mobile Sequential Recommendation: An Efficient Parallel Computing Paradigm.
An Iterative Global Structure-Assisted Labeled Network Aligner.
Can Who-Edits-What Predict Edit Survival?
Complex Object Classification: A Multi-Modal Multi-Instance Multi-Label Deep Network with Optimal Transport.
HeavyGuardian: Separate and Guard Hot Items in Data Streams.
Coupled Context Modeling for Deep Chit-Chat: Towards Conversations between Human and Computer.
RAIM: Recurrent Attentive and Intensive Model of Multimodal Patient Monitoring Data.
New Robust Metric Learning Model Using Maximum Correntropy Criterion.
Geographical Hidden Markov Tree for Flood Extent Mapping.
On Discrimination Discovery and Removal in Ranked Data using Causal Graph.
Deep Censored Learning of the Winning Price in the Real Time Bidding.
Decoupled Learning for Factorial Marked Temporal Point Processes.
Scalable Spectral Clustering Using Random Binning Features.
IntelliLight: A Reinforcement Learning Approach for Intelligent Traffic Light Control.
Smoothed Dilated Convolutions for Improved Dense Prediction.
Towards Evolutionary Compression.
Neural Memory Streaming Recommender Networks with Adversarial Training.
You Are How You Drive: Peer and Temporal-Aware Representation Learning for Driving Behavior Analysis.
Supervised Reinforcement Learning with Recurrent Neural Network for Dynamic Treatment Recommendation.
Multilevel Wavelet Decomposition Network for Interpretable Time Series Analysis.
Towards Mitigating the Class-Imbalance Problem for Partial Label Learning.
Learning Credible Models.
Not Just Privacy: Improving Performance of Private Deep Learning in Mobile Cloud.
Multi-Type Itemset Embedding for Learning Behavior Success.
Efficient Attribute Recommendation with Probabilistic Guarantee.
Quantifying Uncertainty in Discrete-Continuous and Skewed Data with Bayesian Deep Learning.
Hyperparameter Importance Across Datasets.
Deep Recursive Network Embedding with Regular Equivalence.
NetLSD: Hearing the Shape of a Graph.
Latent Variable Time-varying Network Inference.
Isolation Kernel and Its Effect on SVM.
Count-Min: Optimal Estimation and Tight Error Bounds using Empirical Error Distributions.
Multi-Pointer Co-Attention Networks for Recommendation.
Multi-Cast Attention Networks.
Ranking Distillation: Learning Compact Ranking Models With High Performance for Recommender System.
Data Diff: Interpretable, Executable Summaries of Changes in Distributions for Data Wrangling.
Exploring the Urban Region-of-Interest through the Analysis of Online Map Search Queries.
Subspace Network: Deep Multi-Task Censored Regression for Modeling Neurodegenerative Diseases.
Multi-Round Influence Maximization.
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual &Group Unfairness via Inequality Indices.
Deep r -th Root of Rank Supervised Joint Binary Embedding for Multivariate Time Series Retrieval.
Fairness of Exposure in Rankings.
Are your data gathered?
Feedback-Guided Anomaly Discovery via Online Optimization.
Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks.
HiExpan: Task-Guided Taxonomy Construction by Hierarchical Tree Expansion.
Recurrent Binary Embedding for GPU-Enabled Exhaustive Retrieval from Billion-Scale Semantic Vectors.
Accelerated Equivalence Structure Extraction via Pairwise Incremental Search.
Butterfly Counting in Bipartite Networks.
Parsing to Programs: A Framework for Situated QA.
MiSoSouP: Mining Interesting Subgroups with Sampling and Pseudodimension.
Active Search of Connections for Case Building and Combating Human Trafficking.
DeepInf: Social Influence Prediction with Deep Learning.
FAHES: A Robust Disguised Missing Values Detector.
Optimizing Cluster-based Randomized Experiments under Monotonicity.
SUSTain: Scalable Unsupervised Scoring for Tensors and its Application to Phenotyping.
Efficient Mining of the Most Significant Patterns with Permutation Testing.
Explanation Mining: Post Hoc Interpretability of Latent Factor Models for Recommendation Systems.
EvoGraph: An Effective and Efficient Graph Upscaling Method for Preserving Graph Properties.
Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection.
Unlocking the Value of Privacy: Trading Aggregate Statistics over Private Correlated Data.
Multiview Clustering via Adaptively Weighted Procrustes.
Calibrated Multi-Task Learning.
Robust Bayesian Kernel Machine via Stein Variational Gradient Descent for Big Data.
DILOF: Effective and Memory Efficient Local Outlier Detection in Data Streams.
Classifying and Counting with Recurrent Contexts.
Discovering Non-Redundant K-means Clusterings in Optimal Subspaces.
xStream: Outlier Detection in Feature-Evolving Data Streams.
Extremely Fast Decision Tree.
Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts.
Hierarchical Taxonomy Aware Network Embedding.
Risk Prediction on Electronic Health Records with Prior Medical Knowledge.
Sketched Follow-The-Regularized-Leader for Online Factorization Machine.
TINET: Learning Invariant Networks via Knowledge Transfer.
R-VQA: Learning Visual Relation Facts with Semantic Attention for Visual Question Answering.
Context-aware Academic Collaborator Recommendation.
Interactive Paths Embedding for Semantic Proximity Search on Heterogeneous Graphs.
Efficient Similar Region Search with Deep Metric Learning.
Active Opinion Maximization in Social Networks.
STAMP: Short-Term Attention/Memory Priority Model for Session-based Recommendation.
Finding Similar Exercises in Online Education Systems.
On Interpretation of Network Embedding via Taxonomy Induction.
Adversarial Detection with Model Interpretation.
Content to Node: Self-Translation Network Embedding.
Enhancing Predictive Modeling of Nested Spatial Data through Group-Level Feature Disaggregation.
Efficient Large-Scale Fleet Management via Multi-Agent Deep Reinforcement Learning.
Dynamic Embeddings for User Profiling in Twitter.
xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems.
High-order Proximity Preserving Information Network Hashing.
Learning from History and Present: Next-item Recommendation via Discriminatively Exploiting User Behaviors.
Dynamic Bike Reposition: A Spatio-Temporal Reinforcement Learning Approach.
Learning Adversarial Networks for Semi-Supervised Text Classification via Policy Gradient.
An Efficient Two-Layer Mechanism for Privacy-Preserving Truth Discovery.
Multi-task Representation Learning for Travel Time Estimation.
Offline Evaluation of Ranking Policies with Click Models.
TruePIE: Discovering Reliable Patterns in Pattern-Based Information Extraction.
Graph Classification using Structural Attention.
Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget.
A Distributed Quasi-Newton Algorithm for Empirical Risk Minimization with Nonsmooth Regularization.
Dual Memory Neural Computer for Asynchronous Two-view Sequential Learning.
Learning Dynamics of Decision Boundaries without Additional Labeled Data.
Stable Prediction across Unknown Environments.
A Treatment Engine by Predicting Next-Period Prescriptions.
Concepts-Bridges: Uncovering Conceptual Bridges Based on Biomedical Concept Evolution.
Variable Selection and Task Grouping for Multi-Task Learning.
Cost-Effective Training of Deep CNNs with Active Model Adaptation.
Active Feature Acquisition with Supervised Matrix Completion.
Accurate and Fast Asymmetric Locality-Sensitive Hashing Scheme for Maximum Inner Product Search.
Generalized Score Functions for Causal Discovery.
Metric Learning from Probabilistic Labels.
Leveraging Meta-path based Context for Top- N Recommendation with A Neural Co-Attention Model.
Disturbance Grassmann Kernels for Subspace-Based Learning.
Automated Local Regression Discontinuity Design Discovery.
PCA by Determinant Optimisation has no Spurious Local Optima.
Multi-label Learning with Highly Incomplete Data via Collaborative Embedding.
R 2 SDH: Robust Rotated Supervised Discrete Hashing.
New Incremental Learning Algorithm for Semi-Supervised Support Vector Machine.
LARC: Learning Activity-Regularized Overlapping Communities Across Time.
When Sentiment Analysis Meets Social Network: A Holistic User Behavior Modeling in Opinionated Data.
Training Big Random Forests with Little Resources.
Semi-Supervised Generative Adversarial Network for Gene Expression Inference.
Route Recommendations for Idle Taxi Drivers: Find Me the Shortest Route to a Customer!
Large-Scale Learnable Graph Convolutional Networks.
Self-Paced Network Embedding.
Scalable Active Learning by Approximated Error Reduction.
Deep Multi-Output Forecasting: Learning to Accurately Predict Blood Glucose Trajectories.
SpotLight: Detecting Anomalies in Streaming Graphs.
BagMinHash - Minwise Hashing Algorithm for Weighted Sets.
Towards Explanation of DNN-based Prediction with Guided Feature Inversion.
Multi-view Adversarially Learned Inference for Cross-domain Joint Distribution Matching.
FASTEN: Fast Sylvester Equation Solver for Graph Mining.
Demand-Aware Charger Planning for Electric Vehicle Sharing.
Learning Structural Node Embeddings via Diffusion Wavelets.
Investor-Imitator: A Framework for Trading Knowledge Extraction.
Transfer Learning via Feature Isomorphism Discovery.
An Empirical Evaluation of Sketching for Numerical Linear Algebra.
Node Similarity with q -Grams for Real-World Labeled Networks.
D2K: Scalable Community Detection in Massive Networks via Small-Diameter k-Plexes.
Approximating the Spectrum of a Graph.
Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus.
Exact and Consistent Interpretation for Piecewise Linear Neural Networks: A Closed Form Solution.
Local Latent Space Models for Top-N Recommendation.
Voxel Deconvolutional Networks for 3D Brain Image Labeling.
Learning-to-Ask: Knowledge Acquisition via 20 Questions.
Spectral Clustering of Large-scale Data by Directly Solving Normalized Cut.
Quantifying and Minimizing Risk of Conflict in Social Networks.
Stabilizing Reinforcement Learning in Dynamic Environment with Application to Online Recommendation.
PME: Projected Metric Embedding on Heterogeneous Networks for Link Prediction.
Network Connectivity Optimization: Fundamental Limits and Effective Algorithms.
Deep Adversarial Learning for Multi-Modality Missing Data Completion.
Sequences of Sets.
Optimal Distributed Submodular Optimization via Sketching.
Discovering Models from Structural and Behavioral Brain Imaging Data.
Scalable k -Means Clustering via Lightweight Coresets.
Algorithms for Hiring and Outsourcing in the Online Labor Market.
A Dual Markov Chain Topic Model for Dynamic Environments.
Opinion Dynamics with Varying Susceptibility to Persuasion.
Learning Tree-based Deep Model for Recommender Systems.
Discovering Latent Patterns of Urban Cultural Interactions in WeChat for Modern City Planning.
Deep Interest Network for Click-Through Rate Prediction.
OpenTag: Open Attribute Value Extraction from Product Profiles.
Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning.
Learning and Transferring IDs Representation in E-commerce.
Deep Reinforcement Learning for Sponsored Search Real-time Bidding.
Notification Volume Control and Optimization System at Pinterest.
Name Disambiguation in AMiner: Clustering, Maintenance, and Human in the Loop.
Visual Search at Alibaba.
Hetero-ConvLSTM: A Deep Learning Approach to Traffic Accident Prediction on Heterogeneous Spatio-Temporal Data.
Graph Convolutional Neural Networks for Web-Scale Recommender Systems.
Deep Distributed Fusion Network for Air Quality Prediction.
RapidScorer: Fast Tree Ensemble Evaluation by Maximizing Compactness in Data Level Parallelization.
Customized Regression Model for Airbnb Dynamic Pricing.
Deep Learning for Practical Image Recognition: Case Study on Kaggle Competitions.
I Know You'll Be Back: Interpretable New User Clustering and Churn Prediction on a Mobile Social Application.
Large-Scale Order Dispatch in On-Demand Ride-Hailing Platforms: A Learning and Planning Approach.
SQR: Balancing Speed, Quality and Risk in Online Experiments.
Mobile Access Record Resolution on Large-Scale Identifier-Linkage Graphs.
False Discovery Rate Controlled Heterogeneous Treatment Effect Detection for Online Controlled Experiments.
SDREGION: Fast Spotting of Changing Communities in Biological Networks.
Learning to Estimate the Travel Time.
EANN: Event Adversarial Neural Networks for Multi-Modal Fake News Detection.
Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba.
Inferring Metapopulation Propagation Network for Intra-city Epidemic Control and Prevention.
A Real-time Framework for Detecting Efficiency Regressions in a Globally Distributed Codebase.
NGUARD: A Game Bot Detection Framework for NetEase MMORPGs.
Learning Tasks for Multitask Learning: Heterogenous Patient Populations in the ICU.
Identify Susceptible Locations in Medical Records via Adversarial Attacks on Deep Predictive Models.
Estimating Glaucomatous Visual Sensitivity from Retinal Thickness with Pattern-Based Regularization and Visualization.
Corpus Conversion Service: A Machine Learning Platform to Ingest Documents at Scale.
A Dynamic Pipeline for Spatio-Temporal Fire Risk Prediction.
PittGrub: A Frustration-Free System to Reduce Food Waste by Notifying Hungry College Students.
Audience Size Forecasting: Fast and Smart Budget Planning for Media Buyers.
Anatomy of a Privacy-Safe Large-Scale Information Extraction System Over Email.
StepDeep: A Novel Spatial-temporal Mobility Event Prediction Framework based on Deep Neural Network.
Detection of Paroxysmal Atrial Fibrillation using Attention-based Bidirectional Recurrent Neural Networks.
Dynamic Pricing under Competition on Online Marketplaces: A Data-Driven Approach.
Managing Computer-Assisted Detection System Based on Transfer Learning with Negative Transfer Inhibition.
Active Deep Learning to Tune Down the Noise in Labels.
Career Transitions and Trajectories: A Case Study in Computing.
A Scalable Solution for Rule-Based Part-of-Speech Tagging on Novel Hardware Accelerators.
Improving Box Office Result Predictions for Movies Using Consumer-Centric Models.
Du-Parking: Spatio-Temporal Big Data Tells You Realtime Parking Availability.
Multi-Task Learning with Neural Networks for Voice Query Understanding on an Entertainment Platform.
An Extensible Event Extraction System With Cross-Media Event Resolution.
Infrastructure Quality Assessment in Africa using Satellite Imagery and Deep Learning.
Fatigue Prediction in Outdoor Runners Via Machine Learning and Sensor Fusion.
Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks.
COTA: Improving the Speed and Accuracy of Customer Support through Ranking and Deep Networks.
Next-Step Suggestions for Modern Interactive Data Analysis Platforms.
Where Will Dockless Shared Bikes be Stacked?: - Parking Hotspots Detection in a New City.
Lessons Learned from Developing and Deploying a Large-Scale Employer Name Normalization System for Online Recruitment.
BigIN4: Instant, Interactive Insight Identification for Multi-Dimensional Big Data.
Deep Sequence Learning with Auxiliary Information for Traffic Prediction.
A Data-Driven Three-Layer Algorithm for Split Delivery Vehicle Routing Problem with 3D Container Loading Constraint.
E-tail Product Return Prediction via Hypergraph-based Local Graph Cut.
TATC: Predicting Alzheimer's Disease with Actigraphy Data.
Rare Query Expansion Through Generative Adversarial Networks in Search Advertising.
Winner's Curse: Bias Estimation for Total Effects of Features in Online Controlled Experiments.
Collaborative Deep Metric Learning for Video Understanding.
Using Machine Learning to Assess the Risk of and Prevent Water Main Breaks.
PrePeP: A Tool for the Identification and Characterization of Pan Assay Interference Compounds.
Dynamic Recommendations for Sequential Hiring Decisions in Online Labor Markets.
Autotune: A Derivative-free Optimization Framework for Hyperparameter Tuning.
Resolving Abstract Anaphora Implicitly in Conversational Assistants using a Hierarchically stacked RNN.
Optimization of a SSP's Header Bidding Strategy using Thompson Sampling.
Optimal Allocation of Real-Time-Bidding and Direct Campaigns.
Explaining Aviation Safety Incidents Using Deep Temporal Multiple Instance Learning.
WattHome: A Data-driven Approach for Energy Efficiency Analytics at City-scale.
Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding.
Towards Station-Level Demand Prediction for Effective Rebalancing in Bike-Sharing Systems.
Reinforcement Learning to Rank in E-Commerce Search Engine: Formalization, Analysis, and Application.
Web-Scale Responsive Visual Search at Bing.
Multimodal Sentiment Analysis To Explore the Structure of Emotions.
Detecting Vehicle Illegal Parking Events using Sharing Bikes' Trajectories.
Accelerating Prototype-Based Drug Discovery using Conditional Diversity Networks.
Exploring Student Check-In Behavior for Improved Point-of-Interest Prediction.
Real-time Personalization using Embeddings for Search Ranking at Airbnb.
Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction.
Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist.
Near Real-time Optimization of Activity-based Notifications.
Device Graphing by Example.
Towards Knowledge Discovery from the Vatican Secret Archives. In Codice Ratio - Episode 1: Machine Transcription of the Manuscripts.
Gotcha - Sly Malware!: Scorpion A Metagraph2vec Based Malware Detection System.
Releasing eHealth Analytics into the Wild: Lessons Learnt from the SPHERE Project.
Applying the Delta Method in Metric Analytics: A Practical Guide with Novel Ideas.
Automatic Discovery of Tactics in Spatio-Temporal Soccer Match Data.
Tax Fraud Detection for Under-Reporting Declarations Using an Unsupervised Machine Learning Approach.
Adaptive Paywall Mechanism for Digital News Media.
SHIELD: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression.
Automated Audience Segmentation Using Reputation Signals.
State Space Models for Forecasting Water Quality Variables: An Application in Aquaculture Prawn Farming.
Pangloss: Fast Entity Linking in Noisy Text Environments.
Assessing Candidate Preference through Web Browsing History.
Detection of Apathy in Alzheimer Patients by Analysing Visual Scanning Behaviour with RNNs.
Q&R: A Two-Stage Approach toward Interactive Recommendation.
Scalable Optimization for Embedding Highly-Dynamic and Recency-Sensitive Data.
How LinkedIn Economic Graph Bonds Information and Product: Applications in LinkedIn Salary.
MIX: Multi-Channel Information Crossing for Text Matching.
Distributed Collaborative Hashing and Its Applications in Ant Financial.
Rotation-blended CNNs on a New Open Dataset for Tropical Cyclone Image-to-intensity Regression.
Product Characterisation towards Personalisation: Learning Attributes from Unstructured Data to Recommend Fashion Products.
Rosetta: Large Scale System for Text Detection and Recognition in Images.
Buy It Again: Modeling Repeat Purchase Recommendations.
Scalable Query N-Gram Embedding for Improving Matching and Relevance in Sponsored Search.
Interpretable Representation Learning for Healthcare via Capturing Disease Progression through Time.
Predicting Estimated Time of Arrival for Commercial Flights.
Online Parameter Selection for Web-based Ranking Problems.
Deploying Machine Learning Models for Public Policy: A Framework.
ActiveRemediation: The Search for Lead Pipes in Flint, Michigan.
Data for Good: Abstract.
On Big Data Learning for Small Data Problems.
Market Design and Computerized Marketplaces.
Data Science for Financial Applications.
