Xia Ning

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 75

Top Topics

Collaborative Filtering

Boltzmann Machines

Recommender Systems

Learning To Rank

Top Venues

BMC Medical Informatics Decis. Mak.

J. Chem. Inf. Model.

Publications

Reza Averly, Xia Ning
Entity Decomposition with Filtering: A Zero-Shot Clinical Named Entity Recognition Framework. CoRR (2024)
Bo Peng, Srinivasan Parthasarathy, Xia Ning
Intention enhanced mixed attentive model for session-based recommendation. Data Min. Knowl. Discov. 38 (4) (2024)
Vishal Dey, Xia Ning
Improving Anticancer Drug Selection and Prioritization via Neural Learning to Rank. J. Chem. Inf. Model. 64 (10) (2024)
Bo Peng, Xinyi Ling, Ziru Chen, Huan Sun, Xia Ning
eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction Data. CoRR (2024)
Botao Yu, Frazier N. Baker, Ziqi Chen, Xia Ning, Huan Sun
LlaSMol: Advancing Large Language Models for Chemistry with a Large-Scale, Comprehensive, High-Quality Instruction Tuning Dataset. CoRR (2024)
Vishal Dey, Xia Ning
Enhancing molecular property prediction with auxiliary learning and task-specific adaptation. J. Cheminformatics 16 (1) (2024)
Vishal Dey, Xia Ning
Enhancing Molecular Property Prediction with Auxiliary Learning and Task-Specific Adaptation. CoRR (2024)
Cheng Luo, Yueting Zhang, Jiayi Guo, Yuxin Hu, Guangyao Zhou, Hongjian You, Xia Ning
SAR-CDSS: A Semi-Supervised Cross-Domain Object Detection from Optical to SAR Domain. Remote. Sens. 16 (6) (2024)
Bo Peng, Zhiyun Ren, Srinivasan Parthasarathy, Xia Ning
: Mixed Models With Preferences, Popularities and Transitions for Next-Basket Recommendation. IEEE Trans. Knowl. Data Eng. 35 (4) (2023)
Ziqi Chen, Bo Peng, Srinivasan Parthasarathy, Xia Ning
Shape-conditioned 3D Molecule Generation via Equivariant Diffusion Models. CoRR (2023)
Bo Peng, Zhiyun Ren, Srinivasan Parthasarathy, Xia Ning
HAM: Hybrid Associations Models for Sequential Recommendation (Extended abstract). ICDE (2023)
Frazier N. Baker, Ziqi Chen, Xia Ning
RLSynC: Offline-Online Reinforcement Learning for Synthon Completion. CoRR (2023)
Arpita Saha, Maggie Samaan, Bo Peng, Xia Ning
A Multi-Layered GRU Model for COVID-19 Patient Representation and Phenotyping from Large-Scale EHR Data. BCB (2023)
Bo Peng, Ziqi Chen, Srinivasan Parthasarathy, Xia Ning
Modeling Sequences as Star Graphs to Address Over-smoothing in Self-attentive Sequential Recommendation. CoRR (2023)
Vishal Dey, Xia Ning
Precision Anti-Cancer Drug Selection via Neural Ranking. CoRR (2023)
Shunian Xiang, Patrick J. Lawrence, Bo Peng, Chienwei Chiang, Dokyoon Kim, Li Shen, Xia Ning
Modeling Path Importance for Effective Alzheimer's Disease Drug Repurposing. CoRR (2023)
Patrick J. Lawrence, Xia Ning
Enhancing drug and cell line representations via contrastive learning for improved anti-cancer drug prioritization. CoRR (2023)
Ziqi Chen, Baoyi Zhang, Hongyu Guo, Prashant S. Emani, Trevor Clancy, Chongming Jiang, Mark Gerstein, Xia Ning, Chao Cheng, Martin Renqiang Min
Binding peptide generation for MHC Class I proteins with deep reinforcement learning. Bioinform. 39 (2) (2023)
Bo Peng, Srinivasan Parthasarathy, Xia Ning
Multi-modality Meets Re-learning: Mitigating Negative Transfer in Sequential Recommendation. CoRR (2023)
Bo Peng, Ben Burns, Ziqi Chen, Srinivasan Parthasarathy, Xia Ning
Towards Efficient and Effective Adaptation of Large Language Models for Sequential Recommendation. CoRR (2023)
Ziqi Chen, Martin Renqiang Min, Hongyu Guo, Chao Cheng, Trevor Clancy, Xia Ning
T-Cell Receptor Optimization with Reinforcement Learning and Mutation Polices for Precision Immunotherapy. RECOMB (2023)
Ziqi Chen, Martin Renqiang Min, Hongyu Guo, Chao Cheng, Trevor Clancy, Xia Ning
T-Cell Receptor Optimization with Reinforcement Learning and Mutation Policies for Precesion Immunotherapy. CoRR (2023)
Bo Peng, Zhiyun Ren, Srinivasan Parthasarathy, Xia Ning
$\mathop {\mathtt {HAM}}$HAM: Hybrid Associations Models for Sequential Recommendation. IEEE Trans. Knowl. Data Eng. 34 (10) (2022)
Bo Peng, Srinivasan Parthasarathy, Xia Ning
Recursive Attentive Methods with Reused Item Representations for Sequential Recommendation. CoRR (2022)
Bo Peng, Chang-Yu Tai, Srinivasan Parthasarathy, Xia Ning
Prospective Preference Enhanced Mixed Attentive Model for Session-based Recommendation. CoRR (2022)
Shinji Tarumi, Wataru Takeuchi, Rong Qi, Xia Ning, Laura Ruppert, Hideyuki Ban, Daniel H. Robertson, Titus Schleyer, Kensaku Kawamoto
Predicting pharmacotherapeutic outcomes for type 2 diabetes: An evaluation of three approaches to leveraging electronic health record data from multiple sources. J. Biomed. Informatics 129 (2022)
Daniele Pala, Brian Lee, Xia Ning, Dokyoon Kim, Li Shen
Mediation Analysis and Mixed-Effects Models for the Identification of Stage-specific Imaging Genetics Patterns in Alzheimer's Disease. BIBM (2022)
Ziqi Chen, Oluwatosin R. Ayinde, James R. Fuchs, Huan Sun, Xia Ning
Retro: Two-Step Graph Generative Models for Retrosynthesis Prediction. CoRR (2022)
Arvind Nair, Xia Ning, James H. Hill
Using recommender systems to improve proactive modeling. Softw. Syst. Model. 20 (4) (2021)
Vishal Dey, Raghu Machiraju, Xia Ning
Improving Compound Activity Classification via Deep Transfer and Representation Learning. CoRR (2021)
Jordan R. Hill, Shyam Visweswaran, Xia Ning, Titus K. Schleyer
Use, Impact, Weaknesses, and Advanced Features of Search Functions for Clinical Use in Electronic Health Records: A Scoping Review. Appl. Clin. Inform. 12 (3) (2021)
Jie Liu, Jiawen Liu, Zhen Xie, Xia Ning, Dong Li
Flame: A Self-Adaptive Auto-Labeling System for Heterogeneous Mobile Processors. SEC (2021)
Ziqi Chen, Martin Renqiang Min, Srinivasan Parthasarathy, Xia Ning
A deep generative model for molecule optimization via one fragment modification. Nat. Mach. Intell. 3 (12) (2021)
Zhiyun Ren, Bo Peng, Titus K. Schleyer, Xia Ning
Hybrid collaborative filtering methods for recommending search terms to clinicians. J. Biomed. Informatics 113 (2021)
Athanasios N. Nikolakopoulos, Xia Ning, Christian Desrosiers, George Karypis
Trust your neighbors: A comprehensive survey of neighborhood-based methods for recommender systems. CoRR (2021)
Patrick J. Lawrence, Xia Ning
Improving MHC Class I Antigen Processing Prediction via Representation Learning and Cleavage Site-Specific Kernels. AMIA (2021)
Ziqi Chen, Martin Renqiang Min, Srinivasan Parthasarathy, Xia Ning
Molecule Optimization via Fragment-based Generative Models. CoRR (2020)
Yicheng He, Junfeng Liu, Xia Ning
Drug Selection via Joint Push and Learning to Rank. IEEE ACM Trans. Comput. Biol. Bioinform. 17 (1) (2020)
Xiaohui Yao, Tiffany Tsang, Qing Sun, Sara K. Quinney, Pengyue Zhang, Xia Ning, Lang Li, Li Shen
Mining and visualizing high-order directional drug interaction effects using the FAERS database. BMC Medical Informatics Decis. Mak. (2) (2020)
Bo Peng, Zhiyun Ren, Srinivasan Parthasarathy, Xia Ning
M2pht: Mixed Models with Preferences and Hybrid Transitions for Next-Basket Recommendation. CoRR (2020)
Zhiyun Ren, Bo Peng, Titus K. Schleyer, Xia Ning
Hybrid Collaborative Filtering Models for Clinical Search Recommendation. CoRR (2020)
Bo Peng, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Xia Ning
Cognitive biomarker prioritization in Alzheimer's Disease using brain morphometric data. BMC Medical Informatics Decis. Mak. 20 (1) (2020)
Vishal Dey, Peter Krasniak, Minh Nguyen, Clara Lee, Xia Ning
Understanding Breast Implant Illness via Social Media Data Analysis. CoRR (2020)
Ziwei Fan, Evan Burgun, Zhiyun Ren, Titus Schleyer, Xia Ning
Improving information retrieval from electronic health records using dynamic and multi-collaborative filtering. CoRR (2020)
Bo Peng, Zhiyun Ren, Srinivasan Parthasarathy, Xia Ning
HAM: Hybrid Associations Model with Pooling for Sequential Recommendation. CoRR (2020)
Xia Ning, Chi Zhang, Kai Wang, Zhongming Zhao, Ewy A. Mathé
Correction to: The International Conference on Intelligent Biology and Medicine 2019: computational methods for drug interactions. BMC Medical Informatics Decis. Mak. 20 (1) (2020)
Wen-Hao Chiang, Li Shen, Lang Li, Xia Ning
Drug-drug interaction prediction based on co-medication patterns and graph matching. Int. J. Comput. Biol. Drug Des. 13 (1) (2020)
Bo Peng, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Xia Ning
Personalized Prioritization of Cognitive Biomarkers in Alzheimer's Disease via Learning to Rank using Brain Morphometric Data. CoRR (2020)
Xia Ning, Chi Zhang, Kai Wang, Zhongming Zhao, Ewy A. Mathé
The International Conference on Intelligent Biology and Medicine 2019: computational methods for drug interactions. BMC Medical Informatics Decis. Mak. (2) (2020)
Ziqi Chen, Martin Renqiang Min, Xia Ning
Ranking-based Convolutional Neural Network Models for Peptide-MHC Binding Prediction. CoRR (2020)
Ziwei Fan, Evan Burgun, Titus Schleyer, Xia Ning
Improving information retrieval from electronic health records using dynamic and multi-collaborative filtering. ICHI (2019)
Bo Peng, Zhiyun Ren, Xiaohui Yao, Kefei Liu, Andrew J. Saykin, Li Shen, Xia Ning
Prioritizing Amyloid Imaging Biomarkers in Alzheimer's Disease via Learning to Rank. MBIA/MFCA@MICCAI (2019)
Zhiyun Ren, Xia Ning, Andrew S. Lan, Huzefa Rangwala
Grade Prediction Based on Cumulative Knowledge and Co-taken Courses. EDM (2019)
Zhiyun Ren, Xia Ning, Andrew S. Lan, Huzefa Rangwala
Grade Prediction with Neural Collaborative Filtering. DSAA (2019)
Bo Peng, Renqiang Min, Xia Ning
CNN-based Dual-Chain Models for Knowledge Graph Learning. CoRR (2019)
Wen-Hao Chiang, Li Shen, Lang Li, Xia Ning
Drug-drug interaction prediction based on co-medication patterns and graph matching. CoRR (2019)
Bo Peng, Xia Ning
Deep Learning for High-Order Drug-Drug Interaction Prediction. BCB (2019)
Danai Chasioti, Xiaohui Yao, Pengyue Zhang, Samuel Lerner, Sara K. Quinney, Xia Ning, Lang Li, Li Shen
Mining Directional Drug Interaction Effects on Myopathy Using the FAERS Database. IEEE J. Biomed. Health Informatics 23 (5) (2019)
Bo Peng, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Xia Ning
Prioritization of Cognitive Assessments in Alzheimer's Disease via Learning to Rank using Brain Morphometric Data. BHI (2019)
Wen-Hao Chiang, Titus Schleyer, Li Shen, Lang Li, Xia Ning
Pattern Discovery from High-Order Drug-Drug Interaction Relations. J. Heal. Informatics Res. 2 (3) (2018)
Yicheng He, Junfeng Liu, Lijun Cheng, Xia Ning
Drug Selection via Joint Push and Learning to Rank. CoRR (2018)
Lingma Lu Acheson, Xia Ning
Enhance E-Learning through Data Mining for Personalized Intervention. CSEDU (1) (2018)
Zhiyun Ren, Xia Ning, Huzefa Rangwala
ALE: Additive Latent Effect Models for Grade Prediction. SDM (2018)
Zhiyun Ren, Xia Ning, Huzefa Rangwala
ALE: Additive Latent Effect Models for Grade Prediction. CoRR (2018)
Wen-Hao Chiang, Li Shen, Lang Li, Xia Ning
Drug Recommendation toward Safe Polypharmacy. CoRR (2018)
Zhiyun Ren, Xia Ning, Huzefa Rangwala
Grade Prediction with Temporal Course-wise Influence. EDM (2017)
Junfeng Liu, Xia Ning
Multi-Assay-Based Compound Prioritization via Assistance Utilization: A Machine Learning Framework. J. Chem. Inf. Model. 57 (3) (2017)
Xia Ning, Li Shen, Lang Li
Predicting High-Order Directional Drug-Drug Interaction Relations. ICHI (2017)
Junfeng Liu, Xia Ning
Differential Compound Prioritization via Bi-Directional Selectivity Push with Power. BCB (2017)
Zhiyun Ren, Xia Ning, Huzefa Rangwala
Grade Prediction with Temporal Course-wise Influence. CoRR (2017)
Junfeng Liu, Xia Ning
Differential Compound Prioritization via Bidirectional Selectivity Push with Power. J. Chem. Inf. Model. 57 (12) (2017)
Xia Ning, Titus Schleyer, Li Shen, Lang Li
Pattern Discovery from Directional High-Order Drug-Drug Interaction Relations. ICHI (2017)
Xiao Bian, Feng Li, Xia Ning
Kernelized Sparse Self-Representation for Clustering and Recommendation. SDM (2016)
Hongteng Xu, Xia Ning, Hui Zhang, Junghwan Rhee, Guofei Jiang
PInfer: Learning to Infer Concurrent Request Paths from System Kernel Events. ICAC (2016)
Baichuan Zhang, Sutanay Choudhury, Mohammad Al Hasan, Xia Ning, Khushbu Agarwal, Sumit Purohit, Paola Gabriela Pesntez Cabrera
Trust from the past: Bayesian Personalized Ranking based Link Prediction in Knowledge Graphs. CoRR (2016)
Jun Wang, Zhiyun Qian, Zhichun Li, Zhenyu Wu, Junghwan Rhee, Xia Ning, Peng Liu, Guofei Jiang
Discover and Tame Long-running Idling Processes in Enterprise Systems. AsiaCCS (2015)
Jiaji Huang, Xia Ning
Latent Space Tracking from Heterogeneous Data with an Application for Anomaly Detection. PAKDD (1) (2015)
Dixin Luo, Hongteng Xu, Yi Zhen, Xia Ning, Hongyuan Zha, Xiaokang Yang, Wenjun Zhang
Multi-Task Multi-Dimensional Hawkes Processes for Modeling Event Sequences. IJCAI (2015)
Xiao Bian, Xia Ning, Geoff Jiang
Hierarchical Sparse Dictionary Learning. ECML/PKDD (2) (2015)
Tzu-Chun Lin, Xia Ning
Multi-Perspective Modeling for Click Event Prediction. RecSys Challenge (2015)
Xia Ning, George Karypis
Recent Advances in Recommender Systems and Future Directions. PReMI (2015)
Martin Renqiang Min, Xia Ning, Chao Cheng, Mark Gerstein
Interpretable Sparse High-Order Boltzmann Machines. AISTATS (2014)
Santosh Kabbur, Xia Ning, George Karypis
FISM: factored item similarity models for top-N recommender systems. KDD (2013)
Xia Ning, George Karypis
Sparse linear methods with side information for Top-N recommendations. WWW (Companion Volume) (2012)
Xia Ning, George Karypis
Sparse linear methods with side information for top-n recommendations. RecSys (2012)
Xia Ning, Michael A. Walters, George Karypis
Improved Machine Learning Models for Predicting Selective Compounds. J. Chem. Inf. Model. 52 (5) (2012)
Fuzhen Zhuang, George Karypis, Xia Ning, Qing He, Zhongzhi Shi
Multi-view learning via probabilistic latent semantic analysis. Inf. Sci. 199 (2012)
Xia Ning, Michael A. Walters, George Karypis
Improved Machine Learning Models for Predicting Selective Compounds. J. Chem. Inf. Model. 52 (1) (2012)
Xia Ning, George Karypis
SLIM: Sparse Linear Methods for Top-N Recommender Systems. ICDM (2011)
Xia Ning, Michael A. Walters, George Karypis
Improved machine learning models for predicting selective compounds. BCB (2011)
Xia Ning, Yanjun Qi
Semi-Supervised Convolution Graph Kernels for Relation Extraction. SDM (2011)
Xia Ning, George Karypis
Multi-task Learning for Recommender System. ACML (2010)
Pavel P. Kuksa, Yanjun Qi, Bing Bai, Ronan Collobert, Jason Weston, Vladimir Pavlovic, Xia Ning
Semi-supervised Abstraction-Augmented String Kernel for Multi-level Bio-Relation Extraction. ECML/PKDD (2) (2010)
Xia Ning, George Karypis
The Set Classification Problem and Solution Methods. SDM (2009)
Xia Ning, Huzefa Rangwala, George Karypis
Multi-Assay-Based Structure-Activity Relationship Models: Improving Structure-Activity Relationship Models by Incorporating Activity Information from Related Targets. J. Chem. Inf. Model. 49 (11) (2009)
Xia Ning, George Karypis
The Set Classification Problem and Solution Methods. ICDM Workshops (2008)
Jianjun Chen, Yao Zheng, Xia Ning
Scalable Parallel Quadrilateral Mesh Generation Coupled with Mesh Partitioning. PDCAT (2005)