Discovery of Interesting Usage Patterns from Web Data. - Robert Cooley; Pang-Ning Tan; Jaideep Srivastava (WEBKDD, 1999)

Textual data mining of service center call records. - Pang-Ning Tan; Hannah Blau; Steven A. Harp; Robert P. Goldman (KDD, 2000)

Indirect Association: Mining Higher Order Dependencies in Data. - Pang-Ning Tan; Vipin Kumar 001; Jaideep Srivastava (PKDD, 2000)

Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data. - Jaideep Srivastava; Robert Cooley; Mukund Deshpande; Pang-Ning Tan (SIGKDD Explor., 2000)

Mining Indirect Associations in Web Data. - Pang-Ning Tan; Vipin Kumar 001 (WEBKDD, 2001)

Selecting the right interestingness measure for association patterns. - Pang-Ning Tan; Vipin Kumar 001; Jaideep Srivastava (KDD, 2002)

High Performance Data Mining. - Vipin Kumar 001; Mahesh V. Joshi; Eui-Hong Han; Pang-Ning Tan; Michael S. Steinbach (VECPAR, 2002)

Discovery of Web Robot Sessions Based on their Navigational Patterns. - Pang-Ning Tan; Vipin Kumar 001 (Data Min. Knowl. Discov., 2002)

Mining Strong Affinity Association Patterns in Data Sets with Skewed Support Distribution. - Hui Xiong 001; Pang-Ning Tan; Vipin Kumar 001 (ICDM, 2003)

Discovery of climate indices using clustering. - Michael S. Steinbach; Pang-Ning Tan; Vipin Kumar 001; Steven A. Klooster; Christopher Potter (KDD, 2003)

Mining interesting contrast rules for a web-based educational system. - Behrouz Minaei-Bidgoli; Pang-Ning Tan; William F. Punch (ICMLA, 2004)

Support envelopes: a technique for exploring the structure of association patterns. - Michael S. Steinbach; Pang-Ning Tan; Vipin Kumar 001 (KDD, 2004)

Generalizing the notion of support. - Michael S. Steinbach; Pang-Ning Tan; Hui Xiong 001; Vipin Kumar 001 (KDD, 2004)

Ordering patterns by combining opinions from multiple sources. - Pang-Ning Tan; Rong Jin 001 (KDD, 2004)

Exploiting a support-based upper bound of Pearson's correlation coefficient for efficiently identifying strongly correlated pairs. - Hui Xiong 001; Shashi Shekhar 001; Pang-Ning Tan; Vipin Kumar 001 (KDD, 2004)

RBA: An Integrated Framework for Regression based on Association Rules. - Aysel Ozgur; Pang-Ning Tan; Vipin Kumar 001 (SDM, 2004)

HICAP: Hierarchical Clustering with Pattern Preservation. - Hui Xiong 001; Michael S. Steinbach; Pang-Ning Tan; Vipin Kumar 001 (SDM, 2004)

Selecting the right objective measure for association analysis. - Pang-Ning Tan; Vipin Kumar 001; Jaideep Srivastava (Inf. Syst., 2004)

Data Mining. - Vipin Kumar 001; Pang-Ning Tan; Michael S. Steinbach (Handbook of Data Structures and Applications, 2004)

Introduction to Data Mining - Pang-Ning Tan; Michael S. Steinbach; Vipin Kumar 001 (Addison-Wesley, 2005)

An Incremental Data Stream Clustering Algorithm Based on Dense Units Detection. - Jing Gao; Jianzhong Li 001; Zhaogong Zhang; Pang-Ning Tan (PAKDD, 2005)

Converting Output Scores from Outlier Detection Algorithms into Probability Estimates. - Jing Gao; Pang-Ning Tan (ICDM, 2006)

Frequent Closed Itemset Mining Using Prefix Graphs with an Efficient Flow-Based Pruning Strategy. - H. D. K. Moonesinghe; Samah Jamal Fodeh; Pang-Ning Tan (ICDM, 2006)

Adaptively Routing P2P Queries Using Association Analysis. - Brian D. Connelly; Christopher W. Bowron; Li Xiao 001; Pang-Ning Tan; Chen Wang 010 (ICPP, 2006)

Outlier Detection Using Random Walks. - H. D. K. Moonesinghe; Pang-Ning Tan (ICTAI, 2006)

Multistep-Ahead Time Series Prediction. - Haibin Cheng; Pang-Ning Tan; Jing Gao; Jerry Scripps (PAKDD, 2006)

Semi-supervised outlier detection. - Jing Gao; Haibin Cheng; Pang-Ning Tan (SAC, 2006)

A Novel Framework for Incorporating Labeled Examples into Anomaly Detection. - Jing Gao; Haibin Cheng; Pang-Ning Tan (SDM, 2006)

Semi-Supervised Clustering with Partial Background Information. - Jing Gao; Pang-Ning Tan; Haibin Cheng (SDM, 2006)

Clustering in the Presence of Bridge-Nodes. - Jerry Scripps; Pang-Ning Tan (SDM, 2006)

Hyperclique pattern discovery. - Hui Xiong 001; Pang-Ning Tan; Vipin Kumar 001 (Data Min. Knowl. Discov., 2006)

Local Detection of Selfish Routing Behavior in Ad Hoc Networks. - Bo Wang 001; Sohraab Soltani; Jonathan K. Shapiro; Pang-Ning Tan (J. Interconnect. Networks, 2006)

TAPER: A Two-Step Approach for All-Strong-Pairs Correlation Query in Large Databases. - Hui Xiong 001; Shashi Shekhar 001; Pang-Ning Tan; Vipin Kumar 001 (IEEE Trans. Knowl. Data Eng., 2006)

A Prototype-driven Framework for Change Detection in Data Stream Classification. - Hamed Valizadegan; Pang-Ning Tan (CIDM, 2007)

Recommendation via Query Centered Random Walk on K-Partite Graph. - Haibin Cheng; Pang-Ning Tan; Jon Sticklen; William F. Punch (ICDM, 2007)

Exploration of Link Structure and Community-Based Node Roles in Network Analysis. - Jerry Scripps; Pang-Ning Tan; Abdol-Hossein Esfahanian (ICDM, 2007)

Incorporating Background Knowledge for Subjective Rule Evaluation. - Samah Jamal Fodeh; Pang-Ning Tan (ICTAI (2), 2007)

A Probabilistic Substructure-Based Approach for Graph Classification. - H. D. K. Moonesinghe; Hamed Valizadegan; Samah Jamal Fodeh; Pang-Ning Tan (ICTAI (1), 2007)

Localized Support Vector Machine and Its Efficient Algorithm. - Haibin Cheng; Pang-Ning Tan; Rong Jin 001 (SDM, 2007)

Kernel Based Detection of Mislabeled Training Examples. - Hamed Valizadegan; Pang-Ning Tan (SDM, 2007)

Detecting Ecosystem Disturbances and Land Cover Change Using Data Mining. - Shyam Boriah; Vipin Kumar 001; Michael S. Steinbach; Pang-Ning Tan; Christopher Potter; Steven A. Klooster (Next Generation of Data Mining, 2008)

Data mining for visual exploration and detection of ecosystem disturbances. - Haibin Cheng; Pang-Ning Tan; Christopher Potter; Steven A. Klooster (GIS, 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 (ICDM Workshops, 2008)

A matrix alignment approach for link prediction. - Jerry Scripps; Pang-Ning Tan; Feilong Chen; Abdol-Hossein Esfahanian (ICPR, 2008)

Maximum Margin Active Learning for Sequence Labeling with Different Length. - Haibin Cheng; Ruofei Zhang; Yefei Peng; Jianchang Mao; Pang-Ning Tan (ICDM, 2008)

Semi-supervised learning with data calibration for long-term time series forecasting. - Haibin Cheng; Pang-Ning Tan (KDD, 2008)

Link Mining for a Social Bookmarking Web Site. - Feilong Chen; Jerry Scripps; Pang-Ning Tan (Web Intelligence, 2008)

Outrank: a Graph-Based Outlier Detection Framework Using Random Walk. - H. D. K. Moonesinghe; Pang-Ning Tan (Int. J. Artif. Intell. Tools, 2008)

History-Based Email Prioritization. - Ronald Nussbaum; Abdol-Hossein Esfahanian; Pang-Ning Tan (ASONAM, 2009)

A Matrix Alignment Approach for Collective Classification. - Jerry Scripps; Pang-Ning Tan; Feilong Chen; Abdol-Hossein Esfahanian (ASONAM, 2009)

A co-classification framework for detecting web spam and spammers in social media web sites. - Feilong Chen; Pang-Ning Tan; Anil K. Jain 001 (CIKM, 2009)

A Semi-supervised Framework for Simultaneous Classification and Regression of Zero-Inflated Time Series Data with Application to Precipitation Prediction. - Zubin Abraham; Pang-Ning Tan (ICDM Workshops, 2009)

Measuring the effects of preprocessing decisions and network forces in dynamic network analysis. - Jerry Scripps; Pang-Ning Tan; Abdol-Hossein Esfahanian (KDD, 2009)

Combining statistics and semantics via ensemble model for document clustering. - Samah Jamal Fodeh; William F. Punch; Pang-Ning Tan (SAC, 2009)

Detection and Characterization of Anomalies in Multivariate Time Series. - Haibin Cheng; Pang-Ning Tan; Christopher Potter; Steven A. Klooster (SDM, 2009)

Pattern Preserving Clustering. - Hui Xiong 001; Michael S. Steinbach; Pang-Ning Tan; Vipin Kumar 001; Wenjun Zhou 001 (Encyclopedia of Data Warehousing and Mining, 2009)

Neural Networks. - Pang-Ning Tan (Encyclopedia of Database Systems, 2009)

Receiver Operating Characteristic. - Pang-Ning Tan (Encyclopedia of Database Systems, 2009)

Clustering Social Networks Using Distance-Preserving Subgraphs. - Ronald Nussbaum; Abdol-Hossein Esfahanian; Pang-Ning Tan (ASONAM, 2010)

Multi task learning on multiple related networks. - Prakash Mandayam Comar; Pang-Ning Tan; Anil Kumar Jain (CIKM, 2010)

An Integrated Framework for Simultaneous Classification and Regression of Time-Series Data. - Zubin Abraham; Pang-Ning Tan (SDM, 2010)

Identifying Cohesive Subgroups and Their Correspondences in Multiple Related Networks. - Prakash Mandayam Comar; Pang-Ning Tan; Anil Kumar Jain (Web Intelligence, 2010)

A Framework for Co-classification of Articles and Users in Wikipedia. - Lei Liu; Pang-Ning Tan (Web Intelligence, 2010)

Constrained overlapping clusters: minimizing the negative effects of bridge-nodes. - Jerry Scripps; Pang-Ning Tan (Stat. Anal. Data Min., 2010)

Efficient Algorithm for Localized Support Vector Machine. - Haibin Cheng; Pang-Ning Tan; Rong Jin 001 (IEEE Trans. Knowl. Data Eng., 2010)

Link-Based Network Mining. - Jerry Scripps; Ronald Nussbaum; Pang-Ning Tan; Abdol-Hossein Esfahanian (Structural Analysis of Complex Networks, 2011)

Smoothed Quantile Regression for Statistical Downscaling of Extreme Events in Climate Modeling. - Zubin Abraham; Pang-Ning Tan; Fan Xin (CIDU, 2011)

LinkBoost: A Novel Cost-Sensitive Boosting Framework for Community-Level Network Link Prediction. - Prakash Mandayam Comar; Pang-Ning Tan; Anil K. Jain 001 (ICDM, 2011)

Detecting bots via incremental LS-SVM learning with dynamic feature adaptation. - Feilong Chen; Supranamaya Ranjan; Pang-Ning Tan (KDD, 2011)

On ontology-driven document clustering using core semantic features. - Samah Jamal Fodeh; William F. Punch; Pang-Ning Tan (Knowl. Inf. Syst., 2011)

Weighted linear kernel with tree transformed features for malware detection. - Prakash Mandayam Comar; Lei Liu; Sabyasachi Saha; Antonio Nucci; Pang-Ning Tan (CIKM, 2012)

Recursive NMF: Efficient label tree learning for large multi-class problems. - Lei Liu; Prakash Mandayam Comar; Sabyasachi Saha; Pang-Ning Tan; Antonio Nucci (ICPR, 2012)

Simultaneous classification and community detection on heterogeneous network data. - Prakash Mandayam Comar; Pang-Ning Tan; Anil K. Jain 001 (Data Min. Knowl. Discov., 2012)

A framework for joint community detection across multiple related networks. - Prakash Mandayam Comar; Pang-Ning Tan; Anil K. Jain 001 (Neurocomputing, 2012)

Combining supervised and unsupervised learning for zero-day malware detection. - Prakash Mandayam Comar; Lei Liu; Sabyasachi Saha; Pang-Ning Tan; Antonio Nucci (INFOCOM, 2013)

Position Preserving Multi-Output Prediction. - Zubin Abraham; Pang-Ning Tan; Perdinan; Julie Winkler; Shiyuan Zhong; Malgorzata Liszewska (ECML/PKDD (2), 2013)

Distribution Regularized Regression Framework for Climate Modeling. - Zubin Abraham; Malgorzata Liszewska; Perdinan; Pang-Ning Tan; Julie Winkler; Shiyuan Zhong (SDM, 2013)

Missing or Inapplicable: Treatment of Incomplete Continuous-valued Features in Supervised Learning. - Lei Liu; Prakash Mandayam Comar; Antonio Nucci; Sabyasachi Saha; Pang-Ning Tan (SDM, 2013)

Clustering Social Networks Using Distance-Preserving Subgraphs. - Ronald Nussbaum; Abdol-Hossein Esfahanian; Pang-Ning Tan (The Influence of Technology on Social Network Analysis and Mining, 2013)

Detecting malicious clients in ISP networks using HTTP connectivity graph and flow information. - Lei Liu; Sabyasachi Saha; Ruben Torres; Jianpeng Xu; Pang-Ning Tan; Antonio Nucci; Marco Mellia (ASONAM, 2014)

ORION: Online Regularized Multi-task Regression and Its Application to Ensemble Forecasting. - Jianpeng Xu; Pang-Ning Tan; Lifeng Luo (ICDM, 2014)

Contour regression: A distribution-regularized regression framework for climate modeling. - Zubin Abraham; Pang-Ning Tan; Perdinan; Julie A. Winkler; Shiyuan Zhong; Malgorzata Liszewska (Stat. Anal. Data Min., 2014)

MF-Tree: Matrix Factorization Tree for Large Multi-Class Learning. - Lei Liu; Pang-Ning Tan; Xi Liu (CIKM, 2015)

Constrained spectral clustering for regionalization: Exploring the trade-off between spatial contiguity and landscape homogeneity. - Shuai Yuan 003; Pang-Ning Tan; Kendra Spence Cheruvelil; Sarah M. Collins; Patricia A. Soranno (DSAA, 2015)

FORMULA: FactORized MUlti-task LeArning for task discovery in personalized medical models. - Jianpeng Xu; Jiayu Zhou; Pang-Ning Tan (SDM, 2015)

WISDOM: Weighted incremental spatio-temporal multi-task learning via tensor decomposition. - Jianpeng Xu; Jiayu Zhou; Pang-Ning Tan; Xi Liu; Lifeng Luo (IEEE BigData, 2016)

Crowdsourcing of network data. - Ding Wang; Prakash Mandayam Comar; Pang-Ning Tan (IJCNN, 2016)

Macro-scale mobile app market analysis using customized hierarchical categorization. - Xi Liu; Han Hee Song; Mario Baldi; Pang-Ning Tan (INFOCOM, 2016)

Synergies that Matter: Efficient Interaction Selection via Sparse Factorization Machine. - Jianpeng Xu; Kaixiang Lin; Pang-Ning Tan; Jiayu Zhou (SDM, 2016)

GSpartan: a Geospatio-Temporal Multi-task Learning Framework for Multi-location Prediction. - Jianpeng Xu; Pang-Ning Tan; Lifeng Luo; Jiayu Zhou (SDM, 2016)

Detecting hashtag hijacking from Twitter. - Courtland VanDam; Pang-Ning Tan (WebSci, 2016)

Multi-level Multi-task Learning for Modeling Cross-Scale Interactions in Nested Geospatial Data. - Shuai Yuan 003; Jiayu Zhou; Pang-Ning Tan; C. Emi Fergus; Tyler Wagner; Patricia A. Soranno (ICDM, 2017)

Hash-Based Feature Learning for Incomplete Continuous-Valued Data. - Shuai Yuan 003; Pang-Ning Tan; Kendra Spence Cheruvelil; C. Emi Fergus; Nicholas K. Skaff; Patricia A. Soranno (SDM, 2017)

Automated classification of EEG signals for predicting students' cognitive state during learning. - Xi Liu; Pang-Ning Tan; Lei Liu; Steven J. Simske (WI, 2017)

Understanding compromised accounts on Twitter. - Courtland VanDam; Jiliang Tang; Pang-Ning Tan (WI, 2017)

Online Multi-Task Learning Framework for Ensemble Forecasting. - Jianpeng Xu; Pang-Ning Tan; Jiayu Zhou; Lifeng Luo (IEEE Trans. Knowl. Data Eng., 2017)

Attributed Network Representation Learning Approaches for Link Prediction. - Farzan Masrour; Pang-Ning Tan; Abdol-Hossein Esfahanian; Courtland VanDam (ASONAM, 2018)

CADET: A Multi-View Learning Framework for Compromised Account Detection on Twitter. - Courtland VanDam; Pang-Ning Tan; Jiliang Tang; Hamid Karimi (ASONAM, 2018)

Distribution Preserving Multi-task Regression for Spatio-Temporal Data. - Xi Liu; Pang-Ning Tan; Zubin Abraham; Lifeng Luo; Pouyan Hatami (ICDM, 2018)

Imputing Structured Missing Values in Spatial Data with Clustered Adversarial Matrix Factorization. - Qi Wang; Pang-Ning Tan; Jiayu Zhou (ICDM, 2018)

A Low Rank Weighted Graph Convolutional Approach to Weather Prediction. - Tyler Wilson; Pang-Ning Tan; Lifeng Luo (ICDM, 2018)

MUSCAT: Multi-Scale Spatio-Temporal Learning with Application to Climate Modeling. - Jianpeng Xu; Xi Liu; Tyler Wilson; Pang-Ning Tan; Pouyan Hatami; Lifeng Luo (IJCAI, 2018)

Enhancing Predictive Modeling of Nested Spatial Data through Group-Level Feature Disaggregation. - Boyang Liu; Pang-Ning Tan; Jiayu Zhou (KDD, 2018)

STARS: Soft Multi-Task Learning for Activity Recognition from Multi-Modal Sensor Data. - Xi Liu; Pang-Ning Tan; Lei Liu (PAKDD (2), 2018)

Diffusion size and structural virality: The effects of message and network features on spreading health information on twitter. - Jingbo Meng; Wei Peng 002; Pang-Ning Tan; Wuyu Liu; Ying Cheng; Arram Bae (Comput. Hum. Behav., 2018)

Neural Networks. - Pang-Ning Tan (Encyclopedia of Database Systems (2nd ed.), 2018)

Receiver Operating Characteristic. - Pang-Ning Tan (Encyclopedia of Database Systems (2nd ed.), 2018)

Introduction to Data Mining (Second Edition) - Pang-Ning Tan; Michael S. Steinbach; Anuj Karpatne; Vipin Kumar 001 (Pearson, 2019)

OPTANE: an OPtimal transport algorithm for NEtwork alignment. - Farzan Masrour; Pang-Ning Tan; Abdol-Hossein Esfahanian (ASONAM, 2019)

You have been CAUTE!: early detection of compromised accounts on social media. - Courtland VanDam; Farzan Masrour; Pang-Ning Tan; Tyler Wilson (ASONAM, 2019)

Hierarchical LSTM Framework for Long-Term Sea Surface Temperature Forecasting. - Xi Liu; Tyler Wilson; Pang-Ning Tan; Lifeng Luo (DSAA, 2019)

Augmented Multi-Task Learning by Optimal Transport. - Boyang Liu; Pang-Ning Tan; Jiayu Zhou (SDM, 2019)

Deep Multi-view Information Bottleneck. - Qi Wang; Claire Boudreau; Qixing Luo; Pang-Ning Tan; Jiayu Zhou (SDM, 2019)

Spatially Constrained Spectral Clustering Algorithms for Region Delineation. - Shuai Yuan 003; Pang-Ning Tan; Kendra Spence Cheruvelil; Sarah M. Collins; Patricia A. Soranno (CoRR, 2019)

Bursting the Filter Bubble: Fairness-Aware Network Link Prediction. - Farzan Masrour; Tyler Wilson; Heng Yan; Pang-Ning Tan; Abdol-Hossein Esfahanian (AAAI, 2020)

OMuLeT: Online Multi-Lead Time Location Prediction for Hurricane Trajectory Forecasting. - Ding Wang; Boyang Liu; Pang-Ning Tan; Lifeng Luo (AAAI, 2020)

Fairness Perception from a Network-Centric Perspective. - Farzan Masrour; Pang-Ning Tan; Abdol-Hossein Esfahanian (ICDM, 2020)

Convolutional Methods for Predictive Modeling of Geospatial Data. - Tyler Wilson; Pang-Ning Tan; Lifeng Luo (SDM, 2020)

Learning Deep Neural Networks under Agnostic Corrupted Supervision. - Boyang Liu; Mengying Sun; Ding Wang; Pang-Ning Tan; Jiayu Zhou (ICML, 2021)

RCA: A Deep Collaborative Autoencoder Approach for Anomaly Detection. - Boyang Liu; Ding Wang; Kaixiang Lin; Pang-Ning Tan; Jiayu Zhou (IJCAI, 2021)

JOHAN: A Joint Online Hurricane Trajectory and Intensity Forecasting Framework. - Ding Wang; Pang-Ning Tan (KDD, 2021)

Automated Analysis of the US Drought Monitor Maps With Machine Learning and Multiple Drought Indicators. - Pouyan Hatami Bahman Beiglou; Lifeng Luo; Pang-Ning Tan; Lisi Pei (Frontiers Big Data, 2021)

Spatio-Temporal Multi-Task Learning via Tensor Decomposition. - Jianpeng Xu; Jiayu Zhou; Pang-Ning Tan; Xi Liu; Lifeng Luo (IEEE Trans. Knowl. Data Eng., 2021)

Unsupervised Anomaly Detection by Robust Density Estimation. - Boyang Liu; Pang-Ning Tan; Jiayu Zhou (AAAI, 2022)

DeepGPD: A Deep Learning Approach for Modeling Geospatio-Temporal Extreme Events. - Tyler Wilson; Pang-Ning Tan; Lifeng Luo (AAAI, 2022)

Using Deep Learning to Identify Linguistic Features that Facilitate or Inhibit the Propagation of Anti- and Pro-Vaccine Content on Social Media. - Young Anna Argyris; Nan Zhang; Bidhan Bashyal; Pang-Ning Tan (ICDH, 2022)

Fairness-Aware Graph Sampling for Network Analysis. - Farzan Masrour; Francisco Santos; Pang-Ning Tan; Abdol-Hossein Esfahanian (ICDM, 2022)

DeepExtrema: A Deep Learning Approach for Forecasting Block Maxima in Time Series Data. - Asadullah Hill Galib; Andrew McDonald 003; Tyler Wilson; Lifeng Luo; Pang-Ning Tan (IJCAI, 2022)

COMET Flows: Towards Generative Modeling of Multivariate Extremes and Tail Dependence. - Andrew McDonald 003; Pang-Ning Tan; Lifeng Luo (IJCAI, 2022)

FACS-GCN: Fairness-Aware Cost-Sensitive Boosting of Graph Convolutional Networks. - Francisco Santos; Junke Ye; Farzan Masrour; Pang-Ning Tan; Abdol-Hossein Esfahanian (IJCNN, 2022)

Beyond Point Prediction: Capturing Zero-Inflated & Heavy-Tailed Spatiotemporal Data with Deep Extreme Mixture Models. - Tyler Wilson; Andrew McDonald 003; Asadullah Hill Galib; Pang-Ning Tan; Lifeng Luo (KDD, 2022)

SimEXT: Self-supervised Representation Learning for Extreme Values in Time Series. - Asadullah Hill Galib; Pang-Ning Tan; Lifeng Luo (ICDM, 2023)

Influence Propagation for Linear Threshold Model with Graph Neural Networks. - Francisco Santos; Anna Stephens; Pang-Ning Tan; Abdol-Hossein Esfahanian (ICDM (Workshops), 2023)

Population Graph Cross-Network Node Classification for Autism Detection Across Sample Groups. - Anna Stephens; Francisco Santos; Pang-Ning Tan; Abdol-Hossein Esfahanian (ICDM (Workshops), 2023)

Self-Recover: Forecasting Block Maxima in Time Series from Predictors with Disparate Temporal Coverage Using Self-Supervised Learning. - Asadullah Hill Galib; Andrew McDonald 003; Pang-Ning Tan; Lifeng Luo (IJCAI, 2023)

DeepFairRank: A Multi-objective Framework for Fair Top-k Node Ranking in Network Data. - Francisco Santos; Farzan Masrour; Pang-Ning Tan; Abdol-Hossein Esfahanian (ASONAM (1), 2024)

FOCI: Fair Cross-Network Node Classification via Optimal Transport. - Anna Stephens; Francisco Santos; Pang-Ning Tan; Abdol-Hossein Esfahanian (ASONAM (2), 2024)

Conversational Agents as an Aid for Cancer Survivors' Information Search. - Barikisu Issaka; Young Anna Argyris; Pang-Ning Tan (HICSS, 2024)

Unraveling Block Maxima Forecasting Models with Counterfactual Explanation. - Yue Deng 004; Asadullah Hill Galib; Pang-Ning Tan; Lifeng Luo (KDD, 2024)

FIDE: Frequency-Inflated Conditional Diffusion Model for Extreme-Aware Time Series Generation. - Asadullah Hill Galib; Pang-Ning Tan; Lifeng Luo (NeurIPS, 2024)

Yield estimation from SAR data using patch-based deep learning and machine learning techniques. - Mahya G. Z. Hashemi; Pang-Ning Tan; Ehsan Jalilvand; Brook Wilke; Hamed Alemohammad; Narendra N. Das (Comput. Electron. Agric., 2024)

FABLE: A Localized, Targeted Adversarial Attack on Weather Forecasting Models. - Yue Deng 004; Asadullah Hill Galib; Xin Lan; Pang-Ning Tan; Lifeng Luo (CoRR, 2025)