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Nitesh V. Chawla

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

181

Venues

48

Active years

1998–2026

Best venue rank

A*

Where they publish

Papers

181 indexed papers, newest first.

YearVenueTitleAuthors
2026AAAIAdaptive and Context-rich Generative Self-supervised Learning on Graphs.Yijun Tian, Chuxu Zhang, Ziyi Kou, Zheyuan Liu, Xiangliang Zhang, Nitesh V. Chawla
2026ACLPolicyLLM: Towards Excellent Comprehension of Public Policy for Large Language Models.Han Bao, Penghao Zhang, Yue Huang, Zhengqing Yuan, Yanchi Ru, S. U. Rui, Yujun Zhou, Xiangqi Wang, Kehan Guo, Nitesh V. Chawla, Yanfang Ye, Xiangliang Zhang
2026ACLContinuous Context Sampling Allows Extending Diversity Boundaries of Large Language Models.Mateusz Bystronski, Do Heon Han, Nitesh V. Chawla, Tomasz Jan Kajdanowicz
2026ACLCrochetBench: Can Vision-Language Models Move from Describing to Doing in Crochet Domain?Peiyu Li, Xiaobao Huang, Ting Hua, Nitesh V. Chawla
2026ACLContext Attribution with Multi-Armed Bandit Optimization.Deng Pan, Keerthiram Murugesan, Ting Hua, Nuno Moniz, Nitesh V. Chawla
2026IUIFrom Verification Burden to Trusted Collaboration: Design Goals for LLM-Assisted Literature Reviews.Brenda Nogueira, Werner Geyer, Andrew A. Anderson, Toby Jia-Jun Li, Dongwhi Kim, Nuno Moniz, Nitesh V. Chawla
2025ACLNGQA: A Nutritional Graph Question Answering Benchmark for Personalized Health-aware Nutritional Reasoning.Zheyuan Zhang, Yiyang Li, Nhi Ha Lan Le, Zehong Wang, Tianyi Ma, Vincent Galassi, Keerthiram Murugesan, Nuno Moniz, Werner Geyer, Nitesh V. Chawla, Chuxu Zhang, Yanfang Ye
2025AIEDBridging the AI Adoption Gap: Designing an Interactive Pedagogical Agent for Higher Education Instructors.Si Chen, Reid Metoyer, Khiem Le, Adam Acunin, Izzy Molnar, Alex Ambrose, James Lang, Nitesh V. Chawla, Ronald A. Metoyer
2025AIESExplanation Difference: Bridging Procedural and Distributional Fairness.Joe Germino, Yuying Zhao, Tyler Derr, Nuno Moniz, Nitesh V. Chawla
2025CIKMSocially Responsible and Trustworthy Generative Foundation Models: Principles, Challenges, and Practices.Yue Huang, Canyu Chen, Lu Cheng, Bhavya Kailkhura, Nitesh V. Chawla, Xiangliang Zhang
2025CIKMThink it Image by Image: Multi-Image Moral Reasoning of Large Vision-Language Models.Chujie Gao, Yue Huang, Xiangqi Wang, Siyuan Wu, Nitesh V. Chawla, Xiangliang Zhang
2025CIKMProto-Yield: An Uncertainty-Aware Prototype Network for Yield Prediction in Real-world Chemical Reactions.Kehan Guo, Zhen Liu, Zhichun Guo, Bozhao Nan, Olexandr Isayev, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang
2025EMNLPAgentDrug: Utilizing Large Language Models in an Agentic Workflow for Zero-Shot Molecular Optimization.Le Huy Khiem, Ting Hua, Nitesh V. Chawla
2025ICLRJustice or Prejudice? Quantifying Biases in LLM-as-a-Judge.Jiayi Ye, Yanbo Wang, Yue Huang, Dongping Chen, Qihui Zhang, Nuno Moniz, Tian Gao, Werner Geyer, Chao Huang, Pin-Yu Chen, Nitesh V. Chawla, Xiangliang Zhang
2025ICMLTowards Graph Foundation Models: Learning Generalities Across Graphs via Task-Trees.Zehong Wang, Zheyuan Zhang, Tianyi Ma, Nitesh V. Chawla, Chuxu Zhang, Yanfang Ye
2025ICMLBeyond Message Passing: Neural Graph Pattern Machine.Zehong Wang, Zheyuan Zhang, Tianyi Ma, Nitesh V. Chawla, Chuxu Zhang, Yanfang Ye
2025IJCAIArtificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction To Generation and Beyond.Kehan Guo, Yili Shen, Gisela Abigail Gonzalez-Montiel, Yue Huang, Yujun Zhou, Mihir Surve, Zhichun Guo, Payel Das, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang
2025IJCAIWhat is Behind Homelessness Bias? Using LLMs and NLP to Mitigate Homelessness by Acting on Social Stigma.Jonathan A. Karr Jr., Emory Smith, Matthew Hauenstein, Georgina Curto, Nitesh V. Chawla
2025IJCAILeveraging Artificial Intelligence to Bridge Gaps in Pediatric Oncology Care for Marginalized Spanish-Speaking Communities.Grigorii Khvatskii, Anglica Garca-Martnez, Deng Pan, Matthew Belcher, Gernimo Medrano Loera, Dayana Pineda Prez, Juan Emmanuel Ferrari Muoz-Ledo, Horacio Mrquez-Gonzlez, Nuno Moniz, Nitesh V. Chawla
2025IJCAIFast Explanations via Policy Gradient-Optimized Explainer.Deng Pan, Nuno Moniz, Nitesh V. Chawla
2025KDD8th Workshop on Machine Learning in Finance.Saurabh Nagrecha, Isha Chaturvedi, Senthil Kumar, Nitesh V. Chawla, Mahashweta Das, Daksha Yadav, Jos A. Rodrguez-Serrano, Eren Kurshan
2025KDDGraph Foundation Models: Challenges, Methods, and Open Questions.Zehong Wang, Chuxu Zhang, Jundong Li, Nitesh V. Chawla, Yanfang Ye
2025KDDMOPI-HFRS: A Multi-objective Personalized Health-aware Food Recommendation System with LLM-enhanced Interpretation.Zheyuan Zhang, Zehong Wang, Tianyi Ma, Varun Sameer Taneja, Sofia Nelson, Nhi Ha Lan Le, Keerthiram Murugesan, Mingxuan Ju, Nitesh V. Chawla, Chuxu Zhang, Yanfang Ye
2025WSDMBeyond Answers: Transferring Reasoning Capabilities to Smaller LLMs Using Multi-Teacher Knowledge Distillation.Yijun Tian, Yikun Han, Xiusi Chen, Wei Wang, Nitesh V. Chawla
2025WSDMVentana a la Verdad (Window to the Truth): A Chatbot Application for Navigating The Colombian Truth Commission's Archives.Anna Sokol, Matthew L. Sisk, Josefina Echavarra Alvarez, Nitesh V. Chawla
2025WSDMWildlifeLookup: A Chatbot Facilitating Wildlife Management with Accessible Data and Insights.Xiangqi Wang, Tianyu Yang, Jason R. Rohr, Brett Scheffers, Nitesh V. Chawla, Xiangliang Zhang
2024AAAIGraph Neural Prompting with Large Language Models.Yijun Tian, Huan Song, Zichen Wang, Haozhu Wang, Ziqing Hu, Fang Wang, Nitesh V. Chawla, Panpan Xu
2024AAAIIntroduction to the Special Track on Artificial Intelligence and COVID-19 (Abstract Reprint).Martin Michalowski, Robert Moskovitch, Nitesh V. Chawla
2024CIBCBSMOTE for gene regulatory network sampling.Gonzalo A. Ruz, Nitesh V. Chawla
2024CIKMTraversing the Journey of Data and AI: From Convergence to Translation.Nitesh V. Chawla
2024CIKMApplication of Large Language Models in Chemistry Reaction Data Extraction and Cleaning.Xiaobao Huang, Mihir Surve, Yuhan Liu, Tengfei Luo, Olaf Wiest, Xiangliang Zhang, Nitesh V. Chawla
2024CIKMChefFusion: Multimodal Foundation Model Integrating Recipe and Food Image Generation.Peiyu Li, Xiaobao Huang, Yijun Tian, Nitesh V. Chawla
2024CSCWSaludConectaMX: Lessons Learned from Deploying a Cooperative Mobile Health System for Pediatric Cancer Care in Mexico.Jennifer J. Schnur, Anglica Garca-Martnez, Patrick Soga, Karla Badillo-Urquiola, Alejandra J. Botello, Ana Calderon Raisbeck, Sugana Chawla, Josef Ernst, William Gentry, Richard P. Johnson, Michael Kennel, Jess Robles, Madison Wagner, Elizabeth Medina, Juan Garduo Espinosa, Horacio Mrquez-Gonzlez, Victor Olivar-Lpez, Luis E. Jurez-Villegas, Martha Avils-Robles, Elisa Dorantes-Acosta, Viridia Avila, Gina Chapa-Koloffon, Elizabeth Cruz, Leticia Luis, Clara Quezada, Emanuel Orozco, Edson Servn-Mori, Martha Cordero, Rubn Martn Payo, Nitesh V. Chawla
2024DSAAData Augmentation's Effect on Machine Learning Models when Learning with Imbalanced Data.Damien A. Dablain, Nitesh V. Chawla
2024ICASSPA Property-Guided Diffusion Model For Generating Molecular Graphs.Changsheng Ma, Taicheng Guo, Qiang Yang, Xiuying Chen, Xin Gao, Shangsong Liang, Nitesh V. Chawla, Xiangliang Zhang
2024ICLRMAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding.Lirong Wu, Yijun Tian, Yufei Huang, Siyuan Li, Haitao Lin, Nitesh V. Chawla, Stan Z. Li
2024ICMLS3GCL: Spectral, Swift, Spatial Graph Contrastive Learning.Guancheng Wan, Yijun Tian, Wenke Huang, Nitesh V. Chawla, Mang Ye
2024ICMLLearning to Predict Mutational Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning.Lirong Wu, Yijun Tian, Haitao Lin, Yufei Huang, Siyuan Li, Nitesh V. Chawla, Stan Z. Li
2024IJCAILarge Language Model Based Multi-agents: A Survey of Progress and Challenges.Taicheng Guo, Xiuying Chen, Yaqi Wang, Ruidi Chang, Shichao Pei, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang
2024KDDMachine Learning in Finance.Leman Akoglu, Nitesh V. Chawla, Josep Domingo-Ferrer, Eren Kurshan, Senthil Kumar, Vidyut M. Naware, Jos A. Rodrguez-Serrano, Isha Chaturvedi, Saurabh Nagrecha, Mahashweta Das, Tanveer A. Faruquie
2024KDDAnyLoss: Transforming Classification Metrics into Loss Functions.Do Heon Han, Nuno Moniz, Nitesh V. Chawla
2024KDDA Survey of Large Language Models for Graphs.Xubin Ren, Jiabin Tang, Dawei Yin, Nitesh V. Chawla, Chao Huang
2024KDDGraph Cross Supervised Learning via Generalized Knowledge.Xiangchi Yuan, Yijun Tian, Chunhui Zhang, Yanfang Ye, Nitesh V. Chawla, Chuxu Zhang
2024KDDDiet-ODIN: A Novel Framework for Opioid Misuse Detection with Interpretable Dietary Patterns.Zheyuan Zhang, Zehong Wang, Shifu Hou, Evan Hall, Landon Bachman, Jasmine White, Vincent Galassi, Nitesh V. Chawla, Chuxu Zhang, Yanfang Ye
2024KDDRelKD 2024: The Second International Workshop on Resource-Efficient Learning for Knowledge Discovery.Chuxu Zhang, Dongkuan Xu, Kaize Ding, Jundong Li, Mojan Javaheripi, Subhabrata Mukherjee, Nitesh V. Chawla, Huan Liu
2024WWWLarge Language Models for Graphs: Progresses and Directions.Chao Huang, Xubin Ren, Jiabin Tang, Dawei Yin, Nitesh V. Chawla
2024WWWCan we Soft Prompt LLMs for Graph Learning Tasks?Zheyuan Liu, Xiaoxin He, Yijun Tian, Nitesh V. Chawla
2024WWWAre we Making Much Progress? Revisiting Chemical Reaction Yield Prediction from an Imbalanced Regression Perspective.Yihong Ma, Xiaobao Huang, Bozhao Nan, Nuno Moniz, Xiangliang Zhang, Olaf Wiest, Nitesh V. Chawla
2024WWWHetGPT: Harnessing the Power of Prompt Tuning in Pre-Trained Heterogeneous Graph Neural Networks.Yihong Ma, Ning Yan, Jiayu Li, Masood S. Mortazavi, Nitesh V. Chawla
2023AAAIHeterogeneous Graph Masked Autoencoders.Yijun Tian, Kaiwen Dong, Chunhui Zhang, Chuxu Zhang, Nitesh V. Chawla
2023AAAIBoosting Graph Neural Networks via Adaptive Knowledge Distillation.Zhichun Guo, Chunhui Zhang, Yujie Fan, Yijun Tian, Chuxu Zhang, Nitesh V. Chawla
2023AAAICross-Domain Few-Shot Graph Classification with a Reinforced Task Coordinator.Qiannan Zhang, Shichao Pei, Qiang Yang, Chuxu Zhang, Nitesh V. Chawla, Xiangliang Zhang
2023DISFairness-Aware Mixture of Experts with Interpretability Budgets.Joe Germino, Nuno Moniz, Nitesh V. Chawla
2023ICDEEfficient Augmentation for Imbalanced Deep Learning.Damien A. Dablain, Colin Bellinger, Bartosz Krawczyk, Nitesh V. Chawla
2023ICLRLearning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency.Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh V. Chawla
2023ICLRDeep Ensembles for Graphs with Higher-order Dependencies.Steven J. Krieg, William C. Burgis, Patrick M. Soga, Nitesh V. Chawla
2023ICLRChasing All-Round Graph Representation Robustness: Model, Training, and Optimization.Chunhui Zhang, Yijun Tian, Mingxuan Ju, Zheyuan Liu, Yanfang Ye, Nitesh V. Chawla, Chuxu Zhang
2023ICMLLinkless Link Prediction via Relational Distillation.Zhichun Guo, William Shiao, Shichang Zhang, Yozen Liu, Nitesh V. Chawla, Neil Shah, Tong Zhao
2023IJCAIGraph-based Molecular Representation Learning.Zhichun Guo, Kehan Guo, Bozhao Nan, Yijun Tian, Roshni G. Iyer, Yihong Ma, Olaf Wiest, Xiangliang Zhang, Wei Wang, Chuxu Zhang, Nitesh V. Chawla
2023KDDKDD Workshop on Machine Learning in Finance.Leman Akoglu, Nitesh V. Chawla, Senthil Kumar, Saurabh Nagrecha, Mahashweta Das, Vidyut M. Naware, Tanveer A. Faruquie
2023KDDFoundations and Applications in Large-scale AI Models: Pre-training, Fine-tuning, and Prompt-based Learning.Derek Zhiyuan Cheng, Dhaval Patel, Linsey Pang, Sameep Mehta, Kexin Xie, Ed H. Chi, Wei Liu, Nitesh V. Chawla, James Bailey
2022CIKMHierarchical Spatio-Temporal Graph Neural Networks for Pandemic Forecasting.Yihong Ma, Patrick Grard, Yijun Tian, Zhichun Guo, Nitesh V. Chawla
2022CIKMMalicious Repositories Detection with Adversarial Heterogeneous Graph Contrastive Learning.Yiyue Qian, Yiming Zhang, Nitesh V. Chawla, Yanfang Ye, Chuxu Zhang
2022ICLRCompositional Training for End-to-End Deep AUC Maximization.Zhuoning Yuan, Zhishuai Guo, Nitesh V. Chawla, Tianbao Yang
2022IJCAIRecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation.Yijun Tian, Chuxu Zhang, Zhichun Guo, Chao Huang, Ronald A. Metoyer, Nitesh V. Chawla
2022IJCAIRecipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks.Yijun Tian, Chuxu Zhang, Zhichun Guo, Yihong Ma, Ronald A. Metoyer, Nitesh V. Chawla
2022IJCAIFew-Shot Learning on Graphs.Chuxu Zhang, Kaize Ding, Jundong Li, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla, Huan Liu
2022KDDToward Graph Minimally-Supervised Learning.Kaize Ding, Chuxu Zhang, Jie Tang, Nitesh V. Chawla, Huan Liu
2022KDDKDD Workshop on Machine Learning in Finance.Senthil Kumar, Leman Akoglu, Nitesh V. Chawla, Saurabh Nagrecha, Vidyut M. Naware, Tanveer A. Faruquie, Hays McCormick
2022RERESAM: Requirements Elicitation and Specification for Deep-Learning Anomaly Models with Applications to UAV Flight Controllers.Md Nafee Al Islam, Yihong Ma, Pedro Alarcon Granadeno, Nitesh V. Chawla, Jane Cleland-Huang
2022WSDMGraph Minimally-supervised Learning.Kaize Ding, Jundong Li, Nitesh V. Chawla, Huan Liu
2021CIKMRecipe Representation Learning with Networks.Yijun Tian, Chuxu Zhang, Ronald A. Metoyer, Nitesh V. Chawla
2021DSAAmotif2vec: Semantic-aware Representation Learning for Wearables' Time Series Data.Suwen Lin, Xian Wu, Nitesh V. Chawla
2021HCITeaching Tablet Technology to Older Adults.Beenish M. Chaudhry, Dipanwita Dasgupta, Mona A. Mohamed, Nitesh V. Chawla
2021HCIA Qualitative Usability Evaluation of Tablets and Accessibility Settings by Older Adults.Dipanwita Dasgupta, Beenish M. Chaudhry, Nitesh V. Chawla
2021ICDMDynamic Attributed Graph Prediction with Conditional Normalizing Flows.Daheng Wang, Tong Zhao, Nitesh V. Chawla, Meng Jiang
2021KDDMachine Learning in Finance.Senthil Kumar, Leman Akoglu, Nitesh V. Chawla, Jos A. Rodrguez-Serrano, Tanveer A. Faruquie, Saurabh Nagrecha
2021PERCOMLan: Learning to Augment Noise Tolerance for Self-report Survey Labels.Suwen Lin, Louis Faust, Nitesh V. Chawla
2021WWWFew-Shot Graph Learning for Molecular Property Prediction.Zhichun Guo, Chuxu Zhang, Wenhao Yu, John Herr, Olaf Wiest, Meng Jiang, Nitesh V. Chawla
2020AAAIMulti-Label Patent Categorization with Non-Local Attention-Based Graph Convolutional Network.Pingjie Tang, Meng Jiang, Bryan (Ning) Xia, Jed W. Pitera, Jeffrey Welser, Nitesh V. Chawla
2020AAAIGraph Few-Shot Learning via Knowledge Transfer.Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li
2020AAAIFew-Shot Knowledge Graph Completion.Chuxu Zhang, Huaxiu Yao, Chao Huang, Meng Jiang, Zhenhui Li, Nitesh V. Chawla
2020CIKMGraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction.Zhichun Guo, Wenhao Yu, Chuxu Zhang, Meng Jiang, Nitesh V. Chawla
2020CIKMPersonalized Imputation on Wearable-Sensory Time Series via Knowledge Transfer.Xian Wu, Stephen M. Mattingly, Shayan Mirjafari, Chao Huang, Nitesh V. Chawla
2020EMNLPFew-Shot Multi-Hop Relation Reasoning over Knowledge Bases.Chuxu Zhang, Lu Yu, Mandana Saebi, Meng Jiang, Nitesh V. Chawla
2020KDDFighting a Pandemic: Convergence of Expertise, Data Science and Policy.Tina Eliassi-Rad, Nitesh V. Chawla, Vittoria Colizza, Lauren Gardner, Marcel Salath, Samuel V. Scarpino, Joseph T. Wu
2020KDDCalendar Graph Neural Networks for Modeling Time Structures in Spatiotemporal User Behaviors.Daheng Wang, Meng Jiang, Munira Syed, Oliver Conway, Vishal Juneja, Sriram Subramanian, Nitesh V. Chawla
2020KDDMulti-modal Network Representation Learning.Chuxu Zhang, Meng Jiang, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla
2020WWWLearning from Cross-Modal Behavior Dynamics with Graph-Regularized Neural Contextual Bandit.Xian Wu, Suleyman Cetintas, Deguang Kong, Miao Lu, Jian Yang, Nitesh V. Chawla
2020WWWHierarchically Structured Transformer Networks for Fine-Grained Spatial Event Forecasting.Xian Wu, Chao Huang, Chuxu Zhang, Nitesh V. Chawla
2020SDMFilling Missing Values on Wearable-Sensory Time Series Data.Suwen Lin, Xian Wu, Gonzalo J. Martnez, Nitesh V. Chawla
2019AAAIA Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data.Chuxu Zhang, Dongjin Song, Yuncong Chen, Xinyang Feng, Cristian Lumezanu, Wei Cheng, Jingchao Ni, Bo Zong, Haifeng Chen, Nitesh V. Chawla
2019ACIIImputing Missing Social Media Data Stream in Multisensor Studies of Human Behavior.Koustuv Saha, Raghu Mulukutla, Kari Nies, Pablo Robles-Granda, Anusha Sirigiri, Dong Whi Yoo, Pino G. Audia, Andrew T. Campbell, Nitesh V. Chawla, Sidney K. D'Mello, Anind K. Dey, Manikanta D. Reddy, Kaifeng Jiang, Qiang Liu, Gloria Mark, Edward Moskal, Aaron Striegel, Munmun De Choudhury, Vedant Das Swain, Julie M. Gregg, Ted Grover, Suwen Lin, Gonzalo J. Martnez, Stephen M. Mattingly, Shayan Mirjafari
2019CHIThe Tesserae Project: Large-Scale, Longitudinal,Stephen M. Mattingly, Julie M. Gregg, Pino G. Audia, Ayse Elvan Bayraktaroglu, Andrew T. Campbell, Nitesh V. Chawla, Vedant Das Swain, Munmun De Choudhury, Sidney K. D'Mello, Anind K. Dey, Ge Gao, Krithika Jagannath, Kaifeng Jiang, Suwen Lin, Qiang Liu, Gloria Mark, Gonzalo J. Martnez, Kizito Masaba, Shayan Mirjafari, Edward Moskal, Raghu Mulukutla, Kari Nies, Manikanta D. Reddy, Pablo Robles-Granda, Koustuv Saha, Anusha Sirigiri, Aaron Striegel
2019CHISocial Media as a Passive Sensor in Longitudinal Studies of Human Behavior and Wellbeing.Koustuv Saha, Ayse Elvan Bayraktaroglu, Andrew T. Campbell, Nitesh V. Chawla, Munmun De Choudhury, Sidney K. D'Mello, Anind K. Dey, Ge Gao, Julie M. Gregg, Krithika Jagannath, Gloria Mark, Gonzalo J. Martnez, Stephen M. Mattingly, Edward Moskal, Anusha Sirigiri, Aaron Striegel, Dong Whi Yoo
2019CIKMSimilarity-Aware Network Embedding with Self-Paced Learning.Chao Huang, Baoxu Shi, Xuchao Zhang, Xian Wu, Nitesh V. Chawla
2019CIKMDeep Prototypical Networks for Imbalanced Time Series Classification under Data Scarcity.Chao Huang, Xian Wu, Xuchao Zhang, Suwen Lin, Nitesh V. Chawla
2019EDMImplicit and Explicit Emotions in MOOCs.Munira Syed, Malolan Chetlur, Shazia Afzal, G. Alex Ambrose, Nitesh V. Chawla
2019EMNLPMulti-Input Multi-Output Sequence Labeling for Joint Extraction of Fact and Condition Tuples from Scientific Text.Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang
2019KDDOnline Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics.Chao Huang, Xian Wu, Xuchao Zhang, Chuxu Zhang, Jiashu Zhao, Dawei Yin, Nitesh V. Chawla
2019KDDThe Role of: A Novel Scientific Knowledge Graph Representation and Construction Model.Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang
2019KDDTUBE: Embedding Behavior Outcomes for Predicting Success.Daheng Wang, Tianwen Jiang, Nitesh V. Chawla, Meng Jiang
2019KDDHeterogeneous Graph Neural Network.Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami, Nitesh V. Chawla
2019LAKIntegrated Closed-loop Learning Analytics Scheme in a First Year Experience Course.Munira Syed, Trunojoyo Anggara, Alison Lanski, Xiaojing Duan, G. Alex Ambrose, Nitesh V. Chawla
2019WWWMiST: A Multiview and Multimodal Spatial-Temporal Learning Framework for Citywide Abnormal Event Forecasting.Chao Huang, Chuxu Zhang, Jiashu Zhao, Xian Wu, Nitesh V. Chawla, Dawei Yin
2019WSDMNeural Tensor Factorization for Temporal Interaction Learning.Xian Wu, Baoxu Shi, Yuxiao Dong, Chao Huang, Nitesh V. Chawla
2019WSDMSHNE: Representation Learning for Semantic-Associated Heterogeneous Networks.Chuxu Zhang, Ananthram Swami, Nitesh V. Chawla
2018CIKMDeepCrime: Attentive Hierarchical Recurrent Networks for Crime Prediction.Chao Huang, Junbo Zhang, Yu Zheng, Nitesh V. Chawla
2018CIKMRESTFul: Resolution-Aware Forecasting of Behavioral Time Series Data.Xian Wu, Baoxu Shi, Yuxiao Dong, Chao Huang, Louis Faust, Nitesh V. Chawla
2018DSAASMOTEBoost for Regression: Improving the Prediction of Extreme Values.Nuno Moniz, Rita P. Ribeiro, Vtor Cerqueira, Nitesh V. Chawla
2018IJCAITask-Guided and Semantic-Aware Ranking for Academic Author-Paper Correlation Inference.Chuxu Zhang, Lu Yu, Xiangliang Zhang, Nitesh V. Chawla
2018IUIVisPod: Content-Based Audio Visual Navigation.Qiyu Zhi, Suwen Lin, Shuai He, Ronald A. Metoyer, Nitesh V. Chawla
2018KDDMulti-Type Itemset Embedding for Learning Behavior Success.Daheng Wang, Meng Jiang, Qingkai Zeng, Zachary Eberhart, Nitesh V. Chawla
2018WWWCamel: Content-Aware and Meta-path Augmented Metric Learning for Author Identification.Chuxu Zhang, Chao Huang, Lu Yu, Xiangliang Zhang, Nitesh V. Chawla
2018SDMWho will Attend This Event Together? Event Attendance Prediction via Deep LSTM Networks.Xian Wu, Yuxiao Dong, Baoxu Shi, Ananthram Swami, Nitesh V. Chawla
2017ACIIThe ABC of MOOCs: Affect and its inter-play with behavior and cognition.Shazia Afzal, Bikram Sengupta, Munira Syed, Nitesh V. Chawla, G. Alex Ambrose, Malolan Chetlur
2017DSAAMaterials Science Literature-Patent Relevance Search: A Heterogeneous Network Analysis Approach.Pingjie Tang, Jed Pitera, Dmitry Zubarev, Nitesh V. Chawla
2017KDDmetapath2vec: Scalable Representation Learning for Heterogeneous Networks.Yuxiao Dong, Nitesh V. Chawla, Ananthram Swami
2017KDDStructural Diversity and Homophily: A Study Across More Than One Hundred Big Networks.Yuxiao Dong, Reid A. Johnson, Jian Xu, Nitesh V. Chawla
2017MOBICOMPoster: RSSI-Based Pedestrian Localization Using Artificial Neural Networks.Mehdi Golestanian, Christian Poellabauer, Nitesh V. Chawla
2017WWWMOOC Dropout Prediction: Lessons Learned from Making Pipelines Interpretable.Saurabh Nagrecha, John Z. Dillon, Nitesh V. Chawla
2016ACIIDSLink Prediction in a Semi-bipartite Network for Recommendation.Aastha Nigam, Nitesh V. Chawla
2016AMIADesign and Evaluation of a Medication Adherence Application with Communication for Seniors in Independent Living Communities.Dipanwita Dasgupta, Reid A. Johnson, Beenish M. Chaudhry, Kimberly Green Reeves, Patty Willaert, Nitesh V. Chawla
2016DSAAMedCare: Leveraging Medication Similarity for Disease Prediction.Dipanwita Dasgupta, Nitesh V. Chawla
2015DSAAPredicting online video engagement using clickstreams.Everaldo Aguiar, Saurabh Nagrecha, Nitesh V. Chawla
2015EUSFLATBeing a "Dataologist": From Data to Networks to Personalized Healthcare.Nitesh V. Chawla
2015KDDCoupledLP: Link Prediction in Coupled Networks.Yuxiao Dong, Jing Zhang, Jie Tang, Nitesh V. Chawla, Bai Wang
2015LAKQualitatively exploring electronic portfolios: a text mining approach to measuring student emotion as an early warning indicator.Frederick Nwanganga, Everaldo Aguiar, G. Alex Ambrose, Victoria Goodrich, Nitesh V. Chawla
2015MASSTowards Time-Sensitive Truth Discovery in Social Sensing Applications.Chao Huang, Dong Wang, Nitesh V. Chawla
2015PAKDDOptimizing Classifiers for Hypothetical Scenarios.Reid A. Johnson, Troy Raeder, Nitesh V. Chawla
2015WSDMWill This Paper Increase YourYuxiao Dong, Reid A. Johnson, Nitesh V. Chawla
2015SECONOn spatial-temporal truth finding in social sensing.Chao Huang, Dong Wang, Nitesh V. Chawla
2014IJCNNUsing HDDT to avoid instances propagation in unbalanced and evolving data streams.Andrea Dal Pozzolo, Reid A. Johnson, Olivier Caelen, Serge Waterschoot, Nitesh V. Chawla, Gianluca Bontempi
2014KDDInferring user demographics and social strategies in mobile social networks.Yuxiao Dong, Yang Yang, Jie Tang, Yang Yang, Nitesh V. Chawla
2014KDDImproving management of aquatic invasions by integrating shipping network, ecological, and environmental data: data mining for social good.Jian Xu, Thanuka L. Wickramarathne, Nitesh V. Chawla, Erin K. Grey, Karsten Steinhaeuser, Reuben P. Keller, John M. Drake, David M. Lodge
2014LAKEngagement vs performance: using electronic portfolios to predict first semester engineering student retention.Everaldo Aguiar, Nitesh V. Chawla, Jay B. Brockman, G. Alex Ambrose, Victoria Goodrich
2013ACIIDSComparison of Gene Co-expression Networks and Bayesian Networks.Saurabh Nagrecha, Pawan Lingras, Nitesh V. Chawla
2013IDAClassifier Evaluation with Missing Negative Class Labels.Andrew K. Rider, Reid A. Johnson, Darcy A. Davis, T. Ryan Hoens, Nitesh V. Chawla
2012ICDMLink Prediction and Recommendation across Heterogeneous Social Networks.Yuxiao Dong, Jie Tang, Sen Wu, Jilei Tian, Nitesh V. Chawla, Jinghai Rao, Huanhuan Cao
2012ICDMMaximizing Information Spread through Influence Structures in Social Networks.Saurav Pandit, Yang Yang, Nitesh V. Chawla
2012ICDMPredicting Links in Multi-relational and Heterogeneous Networks.Yang Yang, Nitesh V. Chawla, Yizhou Sun, Jiawei Han
2012KDDLearning in non-stationary environments with class imbalance.Thomas Ryan Hoens, Nitesh V. Chawla
2012PAKDDBuilding Decision Trees for the Multi-class Imbalance Problem.T. Ryan Hoens, Qi Qian, Nitesh V. Chawla, Zhi-Hua Zhou
2012PAKDDALIVE: A Multi-relational Link Prediction Environment for the Healthcare Domain.Reid A. Johnson, Yang Yang, Everaldo Aguiar, Andrew K. Rider, Nitesh V. Chawla
2012WWWVertex collocation profiles: subgraph counting for link analysis and prediction.Ryan Lichtenwalter, Nitesh V. Chawla
2012WSDMWhen will it happen?: relationship prediction in heterogeneous information networks.Yizhou Sun, Jiawei Han, Charu C. Aggarwal, Nitesh V. Chawla
2011CIDMEmpirical comparison of correlation measures and pruning levels in complex networks representing the global climate system.Alex Pelan, Karsten Steinhaeuser, Nitesh V. Chawla, Dilkushi A. de Alwis Pitts, Auroop R. Ganguly
2011DISNetwork Effects on Tweeting.Jake T. Lussier, Nitesh V. Chawla
2011ICDMHeuristic Updatable Weighted Random Subspaces for Non-stationary Environments.T. Ryan Hoens, Nitesh V. Chawla, Robi Polikar
2010COMADDigging up the Dirt on User Generated Content Consumption.Jake T. Lussier, Troy Raeder, Nitesh V. Chawla
2010ICDMConsequences of Variability in Classifier Performance Estimates.Troy Raeder, T. Ryan Hoens, Nitesh V. Chawla
2010ICPRAn Incremental Learning Algorithm for Non-stationary Environments and Class Imbalance.Gregory Ditzler, Robi Polikar, Nitesh V. Chawla
2010KDDNew perspectives and methods in link prediction.Ryan Lichtenwalter, Jake T. Lussier, Nitesh V. Chawla
2010PAKDDGenerating Diverse Ensembles to Counter the Problem of Class Imbalance.T. Ryan Hoens, Nitesh V. Chawla
2010PAKDDPrivacy-Preserving Network Aggregation.Troy Raeder, Marina Blanton, Nitesh V. Chawla, Keith B. Frikken
2010SDMA Robust Decision Tree Algorithm for Imbalanced Data Sets.Wei Liu, Sanjay Chawla, David A. Cieslak, Nitesh V. Chawla
2010VizSecVisualizing graph dynamics and similarity for enterprise network security and management.Qi Liao, Aaron Striegel, Nitesh V. Chawla
2009KDDMining in a mobile environment.Sean McRoskey, James Notwell, Nitesh V. Chawla, Christian Poellabauer
2009KDDAn exploration of climate data using complex networks.Karsten Steinhaeuser, Nitesh V. Chawla, Auroop R. Ganguly
2009PAKDDAdaptive Methods for Classification in Arbitrarily Imbalanced and Drifting Data Streams.Ryan Lichtenwalter, Nitesh V. Chawla
2008CIKMPredicting individual disease risk based on medical history.Darcy A. Davis, Nitesh V. Chawla, Nicholas Blumm, Nicholas A. Christakis, Albert-Lszl Barabsi
2008ICDMStart Globally, Optimize Locally, Predict Globally: Improving Performance on Imbalanced Data.David A. Cieslak, Nitesh V. Chawla
2008ICDMScaling up Classifiers to Cloud Computers.Christopher Moretti, Karsten Steinhaeuser, Douglas Thain, Nitesh V. Chawla
2008PAKDDAnalyzing PETs on Imbalanced Datasets When Training and Testing Class Distributions Differ.David A. Cieslak, Nitesh V. Chawla
2007AAAIActively Exploring Creation of Face Space(s) for Improved Face Recognition.Nitesh V. Chawla, Kevin W. Bowyer
2007CIDRA Black-Box Approach to Query Cardinality Estimation.Tanu Malik, Randal C. Burns, Nitesh V. Chawla
2007ICCSEnhanced Situational Awareness: Application of DDDAS Concepts to Emergency and Disaster Management.Gregory R. Madey, Albert-Lszl Barabsi, Nitesh V. Chawla, Marta C. Gonzlez, David Hachen, Brett Lantz, Alec Pawling, Timothy W. Schoenharl, Gbor Szab, Pu Wang, Ping Yan
2007ICDMDetecting Fractures in Classifier Performance.David A. Cieslak, Nitesh V. Chawla
2006GRCCombating imbalance in network intrusion datasets.David A. Cieslak, Nitesh V. Chawla, Aaron Striegel
2006HPDCTroubleshooting Distributed Systems via Data Mining.David A. Cieslak, Douglas Thain, Nitesh V. Chawla
2006IJCNNEvolutionary Ensemble Creation and Thinning.Jared Sylvester, Nitesh V. Chawla
2006SCData management and query - Estimating query result sizes for proxy caching in scientific database federations.Tanu Malik, Randal C. Burns, Nitesh V. Chawla, Alexander S. Szalay
2005CVPRRandom Subspaces and Subsampling for 2-D Face Recognition.Nitesh V. Chawla, Kevin W. Bowyer
2005SMCEnsembles in face recognition: tackling the extremes of high dimensionality, temporality, and variance in data.Nitesh V. Chawla, Kevin W. Bowyer
2002KDDGeneralization Methods in Bioinformatics.Steven Eschrich, Nitesh V. Chawla, Lawrence O. Hall
2001CVPRBagging Is a Small-Data-Set Phenomenon.Nitesh V. Chawla, Thomas E. Moore, Kevin W. Bowyer, Lawrence O. Hall, Clayton Springer, W. Philip Kegelmeyer
2001ICDMCreating Ensembles of Classifiers.Nitesh V. Chawla, Steven Eschrich, Lawrence O. Hall
2001KDDInvestigation of bagging-like effects and decision trees versus neural nets in protein secondary structure prediction.Nitesh V. Chawla, Thomas E. Moore, Kevin W. Bowyer, Lawrence O. Hall, Clayton Springer, W. Philip Kegelmeyer
2000SMCA parallel decision tree builder for mining very large visualization datasets.Kevin W. Bowyer, Lawrence O. Hall, Thomas Moore, Nitesh V. Chawla, W. Philip Kegelmeyer
1999KDDLearning Rules from Distributed Data.Lawrence O. Hall, Nitesh V. Chawla, Kevin W. Bowyer, W. Philip Kegelmeyer
1998SMCDecision tree learning on very large data sets.Lawrence O. Hall, Nitesh V. Chawla, Kevin W. Bowyer