Haibin Cheng

According to our database, Haibin Cheng authored at least 19 papers between 2006 and 2018.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2018

Real-time Personalization using Embeddings for Search Ranking at Airbnb.

Mihajlo Grbovic, Haibin Cheng

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2012

Post-click conversion modeling and analysis for non-guaranteed delivery display advertising.

Rómer Rosales, Haibin Cheng, Eren Manavoglu

Proceedings of the Fifth International Conference on Web Search and Web Data Mining, 2012

Multimedia features for click prediction of new ads in display advertising.

Haibin Cheng, Roelof van Zwol, Javad Azimi, Eren Manavoglu, Ruofei Zhang, Yang Zhou, Vidhya Navalpakkam

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Dynamic ad layout revenue optimization for display advertising.

Haibin Cheng, Eren Manavoglu, Ying Cui, Ruofei Zhang, Jianchang Mao

Proceedings of the Sixth International Workshop on Data Mining for Online Advertising and Internet Economy, 2012

2010

Efficient Algorithm for Localized Support Vector Machine.

Haibin Cheng, Pang-Ning Tan, Rong Jin

IEEE Trans. Knowl. Data Eng., 2010

Personalized click prediction in sponsored search.

Haibin Cheng, Erick Cantú-Paz

Proceedings of the Third International Conference on Web Search and Web Data Mining, 2010

2009

Detection and Characterization of Anomalies in Multivariate Time Series.

Haibin Cheng, Pang-Ning Tan, Christopher Potter, Steven A. Klooster

Proceedings of the SIAM International Conference on Data Mining, 2009

2008

Semi-supervised learning with data calibration for long-term time series forecasting.

Haibin Cheng, Pang-Ning Tan

Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

Maximum Margin Active Learning for Sequence Labeling with Different Length.

Haibin Cheng, Ruofei Zhang, Yefei Peng, Jianchang Mao, Pang-Ning Tan

Proceedings of the Advances in Data Mining. Medical Applications, 2008

A Robust Graph-Based Algorithm for Detection and Characterization of Anomalies in Noisy Multivariate Time Series.

Haibin Cheng, Pang-Ning Tan, Christopher Potter, Steven A. Klooster

Proceedings of the Workshops Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

Exploiting Local and Global Invariants for the Management of Large Scale Information Systems.

Haifeng Chen, Haibin Cheng, Guofei Jiang, Kenji Yoshihira

Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

Data mining for visual exploration and detection of ecosystem disturbances.

Haibin Cheng, Pang-Ning Tan, Christopher Potter, Steven A. Klooster

Proceedings of the 16th ACM SIGSPATIAL International Symposium on Advances in Geographic Information Systems, 2008

2007

Localized Support Vector Machine and Its Efficient Algorithm.

Haibin Cheng, Pang-Ning Tan, Rong Jin

Proceedings of the Seventh SIAM International Conference on Data Mining, 2007

Nonlinear Feature Selection by Relevance Feature Vector Machine.

Haibin Cheng, Haifeng Chen, Guofei Jiang, Kenji Yoshihira

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2007

Recommendation via Query Centered Random Walk on K-Partite Graph.

Haibin Cheng, Pang-Ning Tan, Jon Sticklen, William F. Punch

Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007

2006

Semi-Supervised Clustering with Partial Background Information.

Jing Gao, Pang-Ning Tan, Haibin Cheng

Proceedings of the Sixth SIAM International Conference on Data Mining, 2006

A Novel Framework for Incorporating Labeled Examples into Anomaly Detection.

Jing Gao, Haibin Cheng, Pang-Ning Tan

Proceedings of the Sixth SIAM International Conference on Data Mining, 2006

Semi-supervised outlier detection.

Jing Gao, Haibin Cheng, Pang-Ning Tan

Proceedings of the 2006 ACM Symposium on Applied Computing (SAC), 2006

Multistep-Ahead Time Series Prediction.

Haibin Cheng, Pang-Ning Tan, Jing Gao, Jerry Scripps

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2006