| 2008 |
|---|
| 12 | EE | Haibin Cheng,
Pang-Ning Tan,
Christopher Potter,
Steven A. Klooster:
Data mining for visual exploration and detection of ecosystem disturbances.
GIS 2008: 60 |
| 11 | EE | Haifeng Chen,
Haibin Cheng,
Guofei Jiang,
Kenji Yoshihira:
Exploiting Local and Global Invariants for the Management of Large Scale Information Systems.
ICDM 2008: 113-122 |
| 10 | EE | Haibin Cheng,
Ruofei Zhang,
Yefei Peng,
Jianchang Mao,
Pang-Ning Tan:
Maximum Margin Active Learning for Sequence Labeling with Different Length.
ICDM 2008: 345-359 |
| 9 | EE | Haibin Cheng,
Pang-Ning Tan,
Christopher Potter,
Steven A. Klooster:
A Robust Graph-Based Algorithm for Detection and Characterization of Anomalies in Noisy Multivariate Time Series.
ICDM Workshops 2008: 349-358 |
| 8 | EE | Haibin Cheng,
Pang-Ning Tan:
Semi-supervised learning with data calibration for long-term time series forecasting.
KDD 2008: 133-141 |
| 2007 |
|---|
| 7 | EE | Haibin Cheng,
Pang-Ning Tan,
Jon Sticklen,
William F. Punch:
Recommendation via Query Centered Random Walk on K-Partite Graph.
ICDM 2007: 457-462 |
| 6 | EE | Haibin Cheng,
Haifeng Chen,
Guofei Jiang,
Kenji Yoshihira:
Nonlinear Feature Selection by Relevance Feature Vector Machine.
MLDM 2007: 144-159 |
| 5 | EE | Haibin Cheng,
Pang-Ning Tan,
Rong Jin:
Localized Support Vector Machine and Its Efficient Algorithm.
SDM 2007 |
| 2006 |
|---|
| 4 | EE | Haibin Cheng,
Pang-Ning Tan,
Jing Gao,
Jerry Scripps:
Multistep-Ahead Time Series Prediction.
PAKDD 2006: 765-774 |
| 3 | EE | Jing Gao,
Haibin Cheng,
Pang-Ning Tan:
Semi-supervised outlier detection.
SAC 2006: 635-636 |
| 2 | EE | Jing Gao,
Haibin Cheng,
Pang-Ning Tan:
A Novel Framework for Incorporating Labeled Examples into Anomaly Detection.
SDM 2006 |
| 1 | EE | Jing Gao,
Pang-Ning Tan,
Haibin Cheng:
Semi-Supervised Clustering with Partial Background Information.
SDM 2006 |
