Scalable Parallel Quadrilateral Mesh Generation Coupled with Mesh Partitioning. - Jianjun Chen 002; Yao Zheng 003; Xia Ning (PDCAT, 2005)

The Set Classification Problem and Solution Methods. - Xia Ning; George Karypis (ICDM Workshops, 2008)

Multi-Assay-Based Structure-Activity Relationship Models: Improving Structure-Activity Relationship Models by Incorporating Activity Information from Related Targets. - Xia Ning; Huzefa Rangwala; George Karypis (J. Chem. Inf. Model., 2009)

Semi-supervised Abstraction-Augmented String Kernel for Multi-level Bio-Relation Extraction. - Pavel P. Kuksa; Yanjun Qi; Bing Bai; Ronan Collobert; Jason Weston; Vladimir Pavlovic 001; Xia Ning (ECML/PKDD (2), 2010)

Multi-task Learning for Recommender System. - Xia Ning; George Karypis (ACML, 2010)

Trends in Chemical Graph Data Mining. - Nikil Wale; Xia Ning; George Karypis (Managing and Mining Graph Data, 2010)

SLIM: Sparse Linear Methods for Top-N Recommender Systems. - Xia Ning; George Karypis (ICDM, 2011)

Semi-Supervised Convolution Graph Kernels for Relation Extraction. - Xia Ning; Yanjun Qi (SDM, 2011)

Sparse linear methods with side information for Top-N recommendations. - Xia Ning; George Karypis (WWW (Companion Volume), 2012)

Multi-view learning via probabilistic latent semantic analysis. - Fuzhen Zhuang; George Karypis; Xia Ning; Qing He 003; Zhongzhi Shi (Inf. Sci., 2012)

Improved Machine Learning Models for Predicting Selective Compounds. - Xia Ning; Michael A. Walters; George Karypis (J. Chem. Inf. Model., 2012)

FISM: factored item similarity models for top-N recommender systems. - Santosh Kabbur; Xia Ning; George Karypis (KDD, 2013)

Interpretable Sparse High-Order Boltzmann Machines. - Martin Renqiang Min; Xia Ning; Chao Cheng; Mark Gerstein (AISTATS, 2014)

Discover and Tame Long-running Idling Processes in Enterprise Systems. - Jun Wang 141; Zhiyun Qian; Zhichun Li; Zhenyu Wu 003; Junghwan Rhee; Xia Ning; Peng Liu 005; Guofei Jiang (AsiaCCS, 2015)

Multi-Task Multi-Dimensional Hawkes Processes for Modeling Event Sequences. - Dixin Luo; Hongteng Xu; Yi Zhen; Xia Ning; Hongyuan Zha; Xiaokang Yang 001; Wenjun Zhang 001 (IJCAI, 2015)

Latent Space Tracking from Heterogeneous Data with an Application for Anomaly Detection. - Jiaji Huang; Xia Ning (PAKDD (1), 2015)

Hierarchical Sparse Dictionary Learning. - Xiao Bian; Xia Ning; Geoff Jiang (ECML/PKDD (2), 2015)

Recent Advances in Recommender Systems and Future Directions. - Xia Ning; George Karypis (PReMI, 2015)

Multi-Perspective Modeling for Click Event Prediction. - Tzu-Chun Lin; Xia Ning (RecSys Challenge, 2015)

A Comprehensive Survey of Neighborhood-Based Recommendation Methods. - Xia Ning; Christian Desrosiers; George Karypis (Recommender Systems Handbook, 2015)

PInfer: Learning to Infer Concurrent Request Paths from System Kernel Events. - Hongteng Xu; Xia Ning; Hui Zhang 002; Junghwan Rhee; Guofei Jiang (ICAC, 2016)

Kernelized Sparse Self-Representation for Clustering and Recommendation. - Xiao Bian; Feng Li; Xia Ning (SDM, 2016)

Trust from the past: Bayesian Personalized Ranking based Link Prediction in Knowledge Graphs. - Baichuan Zhang; Sutanay Choudhury; Mohammad Al Hasan; Xia Ning; Khushbu Agarwal; Sumit Purohit; Paola Gabriela Pesntez Cabrera (CoRR, 2016)

Differential Compound Prioritization via Bi-Directional Selectivity Push with Power. - Junfeng Liu; Xia Ning (BCB, 2017)

Grade Prediction with Temporal Course-wise Influence. - Zhiyun Ren; Xia Ning; Huzefa Rangwala (EDM, 2017)

Predicting High-Order Directional Drug-Drug Interaction Relations. - Xia Ning; Li Shen 001; Lang Li 001 (ICHI, 2017)

Pattern Discovery from Directional High-Order Drug-Drug Interaction Relations. - Xia Ning; Titus Schleyer; Li Shen 001; Lang Li 001 (ICHI, 2017)

Multi-Assay-Based Compound Prioritization via Assistance Utilization: A Machine Learning Framework. - Junfeng Liu; Xia Ning (J. Chem. Inf. Model., 2017)

Differential Compound Prioritization via Bidirectional Selectivity Push with Power. - Junfeng Liu; Xia Ning (J. Chem. Inf. Model., 2017)

Enhance E-Learning through Data Mining for Personalized Intervention. - Lingma Lu Acheson; Xia Ning (CSEDU (1), 2018)

ALE: Additive Latent Effect Models for Grade Prediction. - Zhiyun Ren; Xia Ning; Huzefa Rangwala (SDM, 2018)

Drug Selection via Joint Push and Learning to Rank. - Yicheng He; Junfeng Liu; Lijun Cheng; Xia Ning (CoRR, 2018)

Drug Recommendation toward Safe Polypharmacy. - Wen-Hao Chiang; Li Shen 001; Lang Li 001; Xia Ning (CoRR, 2018)

Pattern Discovery from High-Order Drug-Drug Interaction Relations. - Wen-Hao Chiang; Titus Schleyer; Li Shen 001; Lang Li 001; Xia Ning (J. Heal. Informatics Res., 2018)

Deep Learning for High-Order Drug-Drug Interaction Prediction. - Bo Peng 009; Xia Ning (BCB, 2019)

Prioritization of Cognitive Assessments in Alzheimer's Disease via Learning to Rank using Brain Morphometric Data. - Bo Peng 009; Xiaohui Yao; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001; Xia Ning (BHI, 2019)

Grade Prediction with Neural Collaborative Filtering. - Zhiyun Ren; Xia Ning; Andrew S. Lan; Huzefa Rangwala (DSAA, 2019)

Grade Prediction Based on Cumulative Knowledge and Co-taken Courses. - Zhiyun Ren; Xia Ning; Andrew S. Lan; Huzefa Rangwala (EDM, 2019)

Improving information retrieval from electronic health records using dynamic and multi-collaborative filtering. - Ziwei Fan 001; Evan Burgun; Titus Schleyer; Xia Ning (ICHI, 2019)

Prioritizing Amyloid Imaging Biomarkers in Alzheimer's Disease via Learning to Rank. - Bo Peng 009; Zhiyun Ren; Xiaohui Yao; Kefei Liu 001; Andrew J. Saykin; Li Shen 001; Xia Ning (MBIA/MFCA@MICCAI, 2019)

CNN-based Dual-Chain Models for Knowledge Graph Learning. - Bo Peng 009; Renqiang Min; Xia Ning (CoRR, 2019)

Mining Directional Drug Interaction Effects on Myopathy Using the FAERS Database. - Danai Chasioti; Xiaohui Yao; Pengyue Zhang; Samuel Lerner; Sara K. Quinney; Xia Ning; Lang Li 001; Li Shen 001 (IEEE J. Biomed. Health Informatics, 2019)

Personalized Prioritization of Cognitive Biomarkers in Alzheimer's Disease via Learning to Rank using Brain Morphometric Data. - Bo Peng 009; Xiaohui Yao; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001; Xia Ning (CoRR, 2020)

HAM: Hybrid Associations Model with Pooling for Sequential Recommendation. - Bo Peng 009; Zhiyun Ren; Srinivasan Parthasarathy 001; Xia Ning (CoRR, 2020)

M2pht: Mixed Models with Preferences and Hybrid Transitions for Next-Basket Recommendation. - Bo Peng 009; Zhiyun Ren; Srinivasan Parthasarathy 001; Xia Ning (CoRR, 2020)

Hybrid Collaborative Filtering Models for Clinical Search Recommendation. - Zhiyun Ren; Bo Peng 009; Titus K. Schleyer; Xia Ning (CoRR, 2020)

Improving information retrieval from electronic health records using dynamic and multi-collaborative filtering. - Ziwei Fan 001; Evan Burgun; Zhiyun Ren; Titus Schleyer; Xia Ning (CoRR, 2020)

Understanding Breast Implant Illness via Social Media Data Analysis. - Vishal Dey; Peter Krasniak; Minh Nguyen; Clara Lee; Xia Ning (CoRR, 2020)

Ranking-based Convolutional Neural Network Models for Peptide-MHC Binding Prediction. - Ziqi Chen; Martin Renqiang Min; Xia Ning (CoRR, 2020)

Molecule Optimization via Fragment-based Generative Models. - Ziqi Chen; Martin Renqiang Min; Srinivasan Parthasarathy 001; Xia Ning (CoRR, 2020)

Drug-drug interaction prediction based on co-medication patterns and graph matching. - Wen-Hao Chiang; Li Shen 001; Lang Li 001; Xia Ning (Int. J. Comput. Biol. Drug Des., 2020)

Correction to: The International Conference on Intelligent Biology and Medicine 2019: computational methods for drug interactions. - Xia Ning; Chi Zhang; Kai Wang 063; Zhongming Zhao; Ewy A. Mathé (BMC Medical Informatics Decis. Mak., 2020)

Cognitive biomarker prioritization in Alzheimer's Disease using brain morphometric data. - Bo Peng 009; Xiaohui Yao; Shannon L. Risacher; Andrew J. Saykin; Li Shen 001; Xia Ning (BMC Medical Informatics Decis. Mak., 2020)

Drug Selection via Joint Push and Learning to Rank. - Yicheng He; Junfeng Liu; Xia Ning (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

The International Conference on Intelligent Biology and Medicine 2019: computational methods for drug interactions. - Xia Ning; Chi Zhang; Kai Wang 063; Zhongming Zhao; Ewy A. Mathé (BMC Medical Informatics Decis. Mak., 2020)

Mining and visualizing high-order directional drug interaction effects using the FAERS database. - Xiaohui Yao; Tiffany Tsang; Qing Sun; Sara K. Quinney; Pengyue Zhang; Xia Ning; Lang Li 001; Li Shen 001 (BMC Medical Informatics Decis. Mak., 2020)

Improving MHC Class I Antigen Processing Prediction via Representation Learning and Cleavage Site-Specific Kernels. - Patrick J. Lawrence; Xia Ning (AMIA, 2021)

Flame: A Self-Adaptive Auto-Labeling System for Heterogeneous Mobile Processors. - Jie Liu; Jiawen Liu; Zhen Xie; Xia Ning; Dong Li 001 (SEC, 2021)

Use, Impact, Weaknesses, and Advanced Features of Search Functions for Clinical Use in Electronic Health Records: A Scoping Review. - Jordan R. Hill; Shyam Visweswaran; Xia Ning; Titus K. Schleyer (Appl. Clin. Inform., 2021)

Trust your neighbors: A comprehensive survey of neighborhood-based methods for recommender systems. - Athanasios N. Nikolakopoulos; Xia Ning; Christian Desrosiers; George Karypis (CoRR, 2021)

Improving Compound Activity Classification via Deep Transfer and Representation Learning. - Vishal Dey; Raghu Machiraju; Xia Ning (CoRR, 2021)

Hybrid collaborative filtering methods for recommending search terms to clinicians. - Zhiyun Ren; Bo Peng 009; Titus K. Schleyer; Xia Ning (J. Biomed. Informatics, 2021)

A deep generative model for molecule optimization via one fragment modification. - Ziqi Chen; Martin Renqiang Min; Srinivasan Parthasarathy 001; Xia Ning (Nat. Mach. Intell., 2021)

Using recommender systems to improve proactive modeling. - Arvind Nair; Xia Ning; James H. Hill (Softw. Syst. Model., 2021)

Mediation Analysis and Mixed-Effects Models for the Identification of Stage-specific Imaging Genetics Patterns in Alzheimer's Disease. - Daniele Pala; Brian Lee; Xia Ning; Dokyoon Kim; Li Shen 001 (BIBM, 2022)

Prospective Preference Enhanced Mixed Attentive Model for Session-based Recommendation. - Bo Peng 009; Chang-Yu Tai; Srinivasan Parthasarathy 001; Xia Ning (CoRR, 2022)

G2Retro: Two-Step Graph Generative Models for Retrosynthesis Prediction. - Ziqi Chen; Oluwatosin R. Ayinde; James R. Fuchs; Huan Sun 001; Xia Ning (CoRR, 2022)

Recursive Attentive Methods with Reused Item Representations for Sequential Recommendation. - Bo Peng 009; Srinivasan Parthasarathy 001; Xia Ning (CoRR, 2022)

Predicting pharmacotherapeutic outcomes for type 2 diabetes: An evaluation of three approaches to leveraging electronic health record data from multiple sources. - Shinji Tarumi; Wataru Takeuchi; Rong Qi; Xia Ning; Laura Ruppert; Hideyuki Ban; Daniel H. Robertson; Titus Schleyer; Kensaku Kawamoto (J. Biomed. Informatics, 2022)

$ mathop { mathtt {HAM}}$HAM: Hybrid Associations Models for Sequential Recommendation. - Bo Peng 009; Zhiyun Ren; Srinivasan Parthasarathy 001; Xia Ning (IEEE Trans. Knowl. Data Eng., 2022)

Trust Your Neighbors: A Comprehensive Survey of Neighborhood-Based Methods for Recommender Systems. - Athanasios N. Nikolakopoulos; Xia Ning; Christian Desrosiers; George Karypis (Recommender Systems Handbook, 2022)

A Multi-Layered GRU Model for COVID-19 Patient Representation and Phenotyping from Large-Scale EHR Data. - Arpita Saha; Maggie Samaan; Bo Peng 009; Xia Ning (BCB, 2023)

HAM: Hybrid Associations Models for Sequential Recommendation (Extended abstract). - Bo Peng 009; Zhiyun Ren; Srinivasan Parthasarathy 001; Xia Ning (ICDE, 2023)

T-Cell Receptor Optimization with Reinforcement Learning and Mutation Polices for Precision Immunotherapy. - Ziqi Chen; Martin Renqiang Min; Hongyu Guo; Chao Cheng; Trevor Clancy; Xia Ning (RECOMB, 2023)

T-Cell Receptor Optimization with Reinforcement Learning and Mutation Policies for Precesion Immunotherapy. - Ziqi Chen; Martin Renqiang Min; Hongyu Guo; Chao Cheng; Trevor Clancy; Xia Ning (CoRR, 2023)

Precision Anti-Cancer Drug Selection via Neural Ranking. - Vishal Dey; Xia Ning (CoRR, 2023)

Shape-conditioned 3D Molecule Generation via Equivariant Diffusion Models. - Ziqi Chen; Bo Peng 009; Srinivasan Parthasarathy 001; Xia Ning (CoRR, 2023)

RLSynC: Offline-Online Reinforcement Learning for Synthon Completion. - Frazier N. Baker; Ziqi Chen; Xia Ning (CoRR, 2023)

Multi-modality Meets Re-learning: Mitigating Negative Transfer in Sequential Recommendation. - Bo Peng 009; Srinivasan Parthasarathy 001; Xia Ning (CoRR, 2023)

Towards Efficient and Effective Adaptation of Large Language Models for Sequential Recommendation. - Bo Peng 009; Ben Burns; Ziqi Chen; Srinivasan Parthasarathy 001; Xia Ning (CoRR, 2023)

Enhancing drug and cell line representations via contrastive learning for improved anti-cancer drug prioritization. - Patrick J. Lawrence; Xia Ning (CoRR, 2023)

Modeling Path Importance for Effective Alzheimer's Disease Drug Repurposing. - Shunian Xiang; Patrick J. Lawrence; Bo Peng 009; Chienwei Chiang; Dokyoon Kim; Li Shen 001; Xia Ning (CoRR, 2023)

Binding peptide generation for MHC Class I proteins with deep reinforcement learning. - Ziqi Chen; Baoyi Zhang; Hongyu Guo; Prashant S. Emani; Trevor Clancy; Chongming Jiang; Mark Gerstein; Xia Ning; Chao Cheng; Martin Renqiang Min (Bioinform., 2023)

M2: Mixed Models With Preferences, Popularities and Transitions for Next-Basket Recommendation. - Bo Peng 009; Zhiyun Ren; Srinivasan Parthasarathy 001; Xia Ning (IEEE Trans. Knowl. Data Eng., 2023)

eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction Data. - Bo Peng 009; Xinyi Ling; Ziru Chen; Huan Sun 001; Xia Ning (ICML, 2024)

LlaSMol: Advancing Large Language Models for Chemistry with a Large-Scale, Comprehensive, High-Quality Instruction Tuning Dataset. - Botao Yu; Frazier N. Baker; Ziqi Chen; Xia Ning; Huan Sun 001 (CoRR, 2024)

Captions Speak Louder than Images (CASLIE): Generalizing Foundation Models for E-commerce from High-quality Multimodal Instruction Data. - Xinyi Ling; Bo Peng; Hanwen Du; Zhihui Zhu; Xia Ning (CoRR, 2024)

log-RRIM: Yield Prediction via Local-to-global Reaction Representation Learning and Interaction Modeling. - Xiao Hu; Ziqi Chen; Bo Peng; Daniel Adu-Ampratwum; Xia Ning (CoRR, 2024)

RLSynC: Offline-Online Reinforcement Learning for Synthon Completion. - Frazier N. Baker; Ziqi Chen; Daniel Adu-Ampratwum; Xia Ning (J. Chem. Inf. Model., 2024)

Improving Anticancer Drug Selection and Prioritization via Neural Learning to Rank. - Vishal Dey; Xia Ning (J. Chem. Inf. Model., 2024)

SAR-CDSS: A Semi-Supervised Cross-Domain Object Detection from Optical to SAR Domain. - Cheng Luo; Yueting Zhang; Jiayi Guo; Yuxin Hu; Guangyao Zhou; Hongjian You; Xia Ning (Remote. Sens., 2024)

Intention enhanced mixed attentive model for session-based recommendation. - Bo Peng 009; Srinivasan Parthasarathy 001; Xia Ning (Data Min. Knowl. Discov., 2024)

Modeling Sequences as Star Graphs to Address Over-Smoothing in Self-Attentive Sequential Recommendation. - Bo Peng 009; Ziqi Chen; Srinivasan Parthasarathy 001; Xia Ning (ACM Trans. Knowl. Discov. Data, 2024)

Enhancing molecular property prediction with auxiliary learning and task-specific adaptation. - Vishal Dey; Xia Ning (J. Cheminformatics, 2024)

mathttGeLLM³O: Generalizing Large Language Models for Multi-property Molecule Optimization. - Vishal Dey; Xiao Hu; Xia Ning (ACL (1), 2025)

Planning with Diffusion Models for Target-Oriented Dialogue Systems. - Hanwen Du; Bo Peng; Xia Ning (ACL (1), 2025)

ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery. - Ziru Chen; Shijie Chen; Yuting Ning; Qianheng Zhang; Boshi Wang; Botao Yu; Yifei Li 005; Zeyi Liao; Chen Wei; Zitong Lu; Vishal Dey; Mingyi Xue 001; et al. (ICLR, 2025)

Entity Decomposition with Filtering: A Zero-Shot Clinical Named Entity Recognition Framework. - Reza Averly; Xia Ning (NAACL (Long Papers), 2025)

SAPIENT: Mastering Multi-turn Conversational Recommendation with Strategic Planning and Monte Carlo Tree Search. - Hanwen Du; Bo Peng; Xia Ning (NAACL (Long Papers), 2025)

Tooling or Not Tooling? The Impact of Tools on Language Agents for Chemistry Problem Solving. - Botao Yu; Frazier N. Baker; Ziru Chen; Garrett Herb; Boyu Gou; Daniel Adu-Ampratwum; Xia Ning; Huan Sun 001 (NAACL (Findings), 2025)

Three-Dimensional Outdoor Pedestrian Road Network Map Construction Based on Crowdsourced Trajectory Data. - Jianbo Tang; Tianyu Zhang; Junjie Ding; Ke Tao; Chen Yang; Jianbing Xiang; Xia Ning (ISPRS Int. J. Geo Inf., 2025)

Using a statewide health information exchange to enhance COVID research and surveillance: The impact of information fragmentation. - Katie S. Allen; Seho Park; John Price; Xia Ning; Titus Schleyer (Int. J. Medical Informatics, 2025)

log-RRIM: Yield Prediction via Local-to-Global Reaction Representation Learning and Interaction Modeling. - Xiao Hu; Ziqi Chen; Daniel Adu-Ampratwum; Xia Ning (J. Chem. Inf. Model., 2025)

Generating 3D Binding Molecules Using Shape-Conditioned Diffusion Models with Guidance. - Ziqi Chen; Bo Peng 009; Tianhua Zhai; Daniel Adu-Ampratwum; Xia Ning (CoRR, 2025)

GeLLM3O: Generalizing Large Language Models for Multi-property Molecule Optimization. - Vishal Dey; Xiao Hu; Xia Ning (CoRR, 2025)

LIDDIA: Language-based Intelligent Drug Discovery Agent. - Reza Averly; Frazier N. Baker; Xia Ning (CoRR, 2025)

Analyzing Fine-Grained Alignment and Enhancing Vision Understanding in Multimodal Language Models. - Jiachen Jiang; Jinxin Zhou; Bo Peng; Xia Ning; Zhihui Zhu (CoRR, 2025)

DiffER: Categorical Diffusion for Chemical Retrosynthesis. - Sean Current; Ziqi Chen; Daniel Adu-Ampratwum; Xia Ning; Srinivasan Parthasarathy 001 (CoRR, 2025)

Large Language Models for Controllable Multi-property Multi-objective Molecule Optimization. - Vishal Dey; Xiao Hu; Xia Ning (CoRR, 2025)

Discovering spatiotemporal patterns of human outdoor activities with crowdsourced trajectory data. - Ju Peng; Jianbo Tang; Min Deng; Huimin Liu; Zhiyuan Hu; Xingxiang Jiang; Jianbing Xiang; Xia Ning; Wenzhe Zhao (Geo spatial Inf. Sci., 2025)

AutoSDT: Scaling Data-Driven Discovery Tasks Toward Open Co-Scientists. - Yifei Li 005; Hanane Nour Moussa; Ziru Chen; Shijie Chen; Botao Yu; Mingyi Xue 001; Benjamin Burns; Tzu-Yao Chiu; Vishal Dey; Zitong Lu; Chen Wei; Qianheng Zhang; et al. (CoRR, 2025)

Understanding Task Vectors in In-Context Learning: Emergence, Functionality, and Limitations. - Yuxin Dong; Jiachen Jiang; Zhihui Zhu; Xia Ning (CoRR, 2025)

LARC: Towards Human-level Constrained Retrosynthesis Planning through an Agentic Framework. - Frazier N. Baker; Daniel Adu-Ampratwum; Reza Averly; Botao Yu; Huan Sun 001; Xia Ning (CoRR, 2025)

EcomMMMU: Strategic Utilization of Visuals for Robust Multimodal E-Commerce Models. - Xinyi Ling; Hanwen Du; Zhihui Zhu; Xia Ning (CoRR, 2025)

tt DiffER: categorical diffusion ensembles for single-step chemical retrosynthesis. - Sean Current; Ziqi Chen; Daniel Adu-Ampratwum; Xia Ning; Srinivasan Parthasarathy 001 (J. Cheminformatics, 2025)