Relay-Linking Models for Prominence and Obsolescence in Evolving Networks
Journal ref 2017. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '17). ACM, Halifax, Canada, 1077-1086
期刊&会议
KDD
ACM SIGKDD Conference on Knowledge Discovery and Data Mining · 会议 · Data Mining
Fake News Detection on Social Media: A Data Mining Perspective
Comments ACM SIGKDD Explorations Newsletter, 2017
End-to-end Learning for Short Text Expansion
Comments KDD'2017
Incorporating Feedback into Tree-based Anomaly Detection
Comments 8 Pages, KDD 2017 Workshop on Interactive Data Exploration and Analytics (IDEA'17), August 14th, 2017, Halifax, Nova Scotia, Canada
Exploring the Ideological Nature of Journalists' Social Networks on Twitter and Associations with News Story Content
Comments Presented at DS+J workshop at KDD'17
Story Generation from Sequence of Independent Short Descriptions
Comments Accepted in SIGKDD Workshop on Machine Learning for Creativity (ML4Creativity), 2017
mAnI: Movie Amalgamation using Neural Imitation
Comments Accepted in ML4Creativity workshop in KDD 2017. Preprint
Exploring Dimensionality Reductions with Forward and Backward Projections
Comments KDD IDEA'17
A Coupon-Collector Model of Machine-Aided Discovery
Comments 5 pages, 9 figures, 2017 KDD Workshop on Data-Driven Discovery
TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks
Comments 8 pages, Appeared at KDD 2017, August 13--17, 2017, Halifax, NS, Canada
Rookie: A unique approach for exploring news archives
Comments Presented at KDD 2017: Data Science + Journalism workshop
A Graph Analytics Framework for Ranking Authors, Papers and Venues
Comments International Workshop on Mining and Learning with Graphs, ACM KDD 2016. arXiv admin note: text overlap with arXiv:1501.04894
Attribution Modeling Increases Efficiency of Bidding in Display Advertising
Comments The first two authors contributed equally to this paper, and should be regarded as co-first authors. Accepted at AdKDD TargetAd workshop at KDD'17
A Machine Learning Approach for Evaluating Creative Artifacts
Comments Accepted at SIGKDD Workshop on Machine Learning for Creativity (ML4Creativity), 2017
"Everything I Disagree With is #FakeNews": Correlating Political Polarization and Spread of Misinformation
Comments 8 pages, 10 figures, to be presented at DS+J Workshop @ KDD'17
Visual Search at eBay
Comments To appear in 23rd SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2017. A demonstration video can be found at https://youtu.be/iYtjs32vh4g
Automated Lane Detection in Crowds using Proximity Graphs
Comments Presented at the 6th International Workshop on Urban Computing (UrbComp 2017) held in conjunction with the 23th ACM SIGKDD
A Data Science Approach to Understanding Residential Water Contamination in Flint
Comments Applied Data Science track paper at KDD 2017. For associated promotional video, see https://www.youtube.com/watch?v=0g66ImaV8Ag
Efficient Correlated Topic Modeling with Topic Embedding
Comments KDD 2017 oral. The first two authors contributed equally
Adaptive Candidate Generation for Scalable Edge-discovery Tasks on Data Graphs
Comments 8 pages,published at MLG workshop at KDD'17
Bolt: Accelerated Data Mining with Fast Vector Compression
Comments Research track paper at KDD 2017
A Temporal Tree Decomposition for Generating Temporal Graphs
Comments 8 pages; appeared at Mining and Learning with Graphs Workshop at KDD 2017
Effective Evaluation using Logged Bandit Feedback from Multiple Loggers
Comments KDD 2018
On Sampling Strategies for Neural Network-based Collaborative Filtering
Comments This is a longer version (with supplementary attached) of the KDD'17 paper
Interpretable Predictions of Tree-based Ensembles via Actionable Feature Tweaking
Comments 10 pages, KDD 2017
Distributed Multi-Task Relationship Learning
Comments To appear in KDD 2017
A Location-Sentiment-Aware Recommender System for Both Home-Town and Out-of-Town Users
Comments Accepted by KDD 2017
ReasoNet: Learning to Stop Reading in Machine Comprehension
Comments in KDD 2017
Accelerating Innovation Through Analogy Mining
Comments KDD 2017
Discovering Reliable Approximate Functional Dependencies
Comments Accepted: In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), August 13-17, 2017, Halifax, NS, Canada
