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George Karypis
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- affiliation: University of Minnesota, USA
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2020 – today
- 2024
- [j87]Zhuosheng Zhang, Aston Zhang, Mu Li, Hai Zhao, George Karypis, Alex Smola:
Multimodal Chain-of-Thought Reasoning in Language Models. Trans. Mach. Learn. Res. 2024 (2024) - [j86]Zonghan Wu, Da Zheng, Shirui Pan, Quan Gan, Guodong Long, George Karypis:
TraverseNet: Unifying Space and Time in Message Passing for Traffic Forecasting. IEEE Trans. Neural Networks Learn. Syst. 35(2): 2003-2013 (2024) - [c232]Vyas Raina, Samson Tan, Volkan Cevher, Aditya Rawal, Sheng Zha, George Karypis:
Extreme Miscalibration and the Illusion of Adversarial Robustness. ACL (1) 2024: 2500-2525 - [c231]Rami Aly, Zhiqiang Tang, Samson Tan, George Karypis:
Learning to Generate Answers with Citations via Factual Consistency Models. ACL (1) 2024: 11876-11896 - [c230]Kezhi Kong, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Chuan Lei, Christos Faloutsos, Huzefa Rangwala, George Karypis:
OpenTab: Advancing Large Language Models as Open-domain Table Reasoners. ICLR 2024 - [c229]Hengrui Zhang, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Xiao Qin, Christos Faloutsos, Huzefa Rangwala, George Karypis:
Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space. ICLR 2024 - [c228]Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis:
Differentially Private Bias-Term Fine-tuning of Foundation Models. ICML 2024 - [c227]Da Zheng, Xiang Song, Qi Zhu, Jian Zhang, Theodore Vasiloudis, Runjie Ma, Houyu Zhang, Zichen Wang, Soji Adeshina, Israt Nisa, Alejandro Mottini, Qingjun Cui, Huzefa Rangwala, Belinda Zeng, Christos Faloutsos, George Karypis:
GraphStorm: All-in-one Graph Machine Learning Framework for Industry Applications. KDD 2024: 6356-6367 - [c226]Youngsuk Park, Kailash Budhathoki, Liangfu Chen, Jonas M. Kübler, Jiaji Huang, Matthäus Kleindessner, Jun Huan, Volkan Cevher, Yida Wang, George Karypis:
Inference Optimization of Foundation Models on AI Accelerators. KDD 2024: 6605-6615 - [c225]Yuan Ling, Shujing Dong, Yarong Feng, Zongyi Joe Liu, George Karypis, Chandan K. Reddy:
KDD workshop on Evaluation and Trustworthiness of Generative AI Models. KDD 2024: 6729-6730 - [c224]Narges Tabari, Aniket Anand Deshmukh, Wang-Cheng Kang, Hamed Zamani, Rashmi Gangadharaiah, Julian J. McAuley, George Karypis:
First Workshop on Generative AI for Recommender Systems and Personalization. KDD 2024: 6737-6738 - [c223]Petros Karypis, Julian J. McAuley, George Karypis:
Extending Input Contexts of Language Models through Training on Segmented Sequences. NAACL-HLT (Findings) 2024: 3040-3052 - [c222]Costas Mavromatis, Petros Karypis, George Karypis:
SemPool: Simple, Robust, and Interpretable KG Pooling for Enhancing Language Models. PKDD (4) 2024: 154-166 - [c221]Vachik S. Dave, Linsey Pang, Xiquan Cui, Chen Luo, Hamed Zamani, Lingfei Wu, George Karypis:
The 3rd International Workshop on Interactive and Scalable Information Retrieval Methods for eCommerce (ISIR-eCom 2024). WSDM 2024: 1208-1209 - [i97]Costas Mavromatis, Petros Karypis, George Karypis:
SemPool: Simple, robust, and interpretable KG pooling for enhancing language models. CoRR abs/2402.02289 (2024) - [i96]Kezhi Kong, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Chuan Lei, Christos Faloutsos, Huzefa Rangwala, George Karypis:
OpenTab: Advancing Large Language Models as Open-domain Table Reasoners. CoRR abs/2402.14361 (2024) - [i95]Vyas Raina, Samson Tan, Volkan Cevher, Aditya Rawal, Sheng Zha, George Karypis:
Extreme Miscalibration and the Illusion of Adversarial Robustness. CoRR abs/2402.17509 (2024) - [i94]Zhiqi Bu, Xinwei Zhang, Mingyi Hong, Sheng Zha, George Karypis:
Pre-training Differentially Private Models with Limited Public Data. CoRR abs/2402.18752 (2024) - [i93]Christos Koutras, Jiani Zhang, Xiao Qin, Chuan Lei, Vasileios Ioannidis, Christos Faloutsos, George Karypis, Asterios Katsifodimos:
OmniMatch: Effective Self-Supervised Any-Join Discovery in Tabular Data Repositories. CoRR abs/2403.07653 (2024) - [i92]Costas Mavromatis, Petros Karypis, George Karypis:
Pack of LLMs: Model Fusion at Test-Time via Perplexity Optimization. CoRR abs/2404.11531 (2024) - [i91]Zhiqiang Tang, Haoyang Fang, Su Zhou, Taojiannan Yang, Zihan Zhong, Tony Hu, Katrin Kirchhoff, George Karypis:
AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models. CoRR abs/2404.16233 (2024) - [i90]Qi Zhu, Da Zheng, Xiang Song, Shichang Zhang, Bowen Jin, Yizhou Sun, George Karypis:
Parameter-Efficient Tuning Large Language Models for Graph Representation Learning. CoRR abs/2404.18271 (2024) - [i89]Costas Mavromatis, George Karypis:
GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning. CoRR abs/2405.20139 (2024) - [i88]Da Zheng, Xiang Song, Qi Zhu, Jiani Zhang, Theodore Vasiloudis, Runjie Ma, Houyu Zhang, Zichen Wang, Soji Adeshina, Israt Nisa, Alejandro Mottini, Qingjun Cui, Huzefa Rangwala, Belinda Zeng, Christos Faloutsos, George Karypis:
GraphStorm: all-in-one graph machine learning framework for industry applications. CoRR abs/2406.06022 (2024) - [i87]Shichang Zhang, Da Zheng, Jiani Zhang, Qi Zhu, Xiang Song, Soji Adeshina, Christos Faloutsos, George Karypis, Yizhou Sun:
Hierarchical Compression of Text-Rich Graphs via Large Language Models. CoRR abs/2406.11884 (2024) - [i86]Rami Aly, Zhiqiang Tang, Samson Tan, George Karypis:
Learning to Generate Answers with Citations via Factual Consistency Models. CoRR abs/2406.13124 (2024) - [i85]Youngsuk Park, Kailash Budhathoki, Liangfu Chen, Jonas M. Kübler, Jiaji Huang, Matthäus Kleindessner, Jun Huan, Volkan Cevher, Yida Wang, George Karypis:
Inference Optimization of Foundation Models on AI Accelerators. CoRR abs/2407.09111 (2024) - [i84]Soumajyoti Sarkar, Leonard Lausen, Volkan Cevher, Sheng Zha, Thomas Brox, George Karypis:
Revisiting SMoE Language Models by Evaluating Inefficiencies with Task Specific Expert Pruning. CoRR abs/2409.01483 (2024) - 2023
- [j85]Fan Yang, Fuzhong Xue, Yanchun Zhang, George Karypis:
Kernelized Multitask Learning Method for Personalized Signaling Adverse Drug Reactions. IEEE Trans. Knowl. Data Eng. 35(2): 1681-1694 (2023) - [c220]Hengzhi Pei, Jinman Zhao, Leonard Lausen, Sheng Zha, George Karypis:
Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion. AAAI 2023: 5230-5238 - [c219]Xuming Hu, Shen Wang, Xiao Qin, Chuan Lei, Zhengyuan Shen, Christos Faloutsos, Asterios Katsifodimos, George Karypis, Lijie Wen, Philip S. Yu:
Automatic Table Union Search with Tabular Representation Learning. ACL (Findings) 2023: 3786-3800 - [c218]Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Shen Wang, Huzefa Rangwala, George Karypis:
NameGuess: Column Name Expansion for Tabular Data. EMNLP 2023: 13276-13290 - [c217]Costas Mavromatis, George Karypis:
Global and Nodal Mutual Information Maximization in Heterogeneous Graphs. ICASSP 2023: 1-5 - [c216]Danilo Neves Ribeiro, Shen Wang, Xiaofei Ma, Henghui Zhu, Rui Dong, Deguang Kong, Juliette Burger, Anjelica Ramos, Zhiheng Huang, William Yang Wang, George Karypis, Bing Xiang, Dan Roth:
STREET: A Multi-Task Structured Reasoning and Explanation Benchmark. ICLR 2023 - [c215]Yulun Wu, Robert A. Barton, Zichen Wang, Vassilis N. Ioannidis, Carlo De Donno, Layne C. Price, Luis F. Voloch, George Karypis:
Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information. ICLR 2023 - [c214]Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis:
Differentially Private Optimization on Large Model at Small Cost. ICML 2023: 3192-3218 - [c213]Bingzhao Zhu, Xingjian Shi, Nick Erickson, Mu Li, George Karypis, Mahsa Shoaran:
XTab: Cross-table Pretraining for Tabular Transformers. ICML 2023: 43181-43204 - [c212]Israt Nisa, Minjie Wang, Da Zheng, Qiang Fu, Ümit V. Çatalyürek, George Karypis:
Optimizing Irregular Dense Operators of Heterogeneous GNN Models on GPU. IPDPS Workshops 2023: 199-206 - [c211]Yuan Ling, Fanyou Wu, Shujing Dong, Yarong Feng, George Karypis, Chandan K. Reddy:
International Workshop on Multimodal Learning - 2023 Theme: Multimodal Learning with Foundation Models. KDD 2023: 5868-5869 - [c210]Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis:
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger. NeurIPS 2023 - [c209]Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis:
HyTrel: Hypergraph-enhanced Tabular Data Representation Learning. NeurIPS 2023 - [c208]Tuan Dinh, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis:
Large Language Models of Code Fail at Completing Code with Potential Bugs. NeurIPS 2023 - [c207]Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang, Da Zheng, Soji Adeshina, Jun Ma, Han Zhao, Christos Faloutsos, George Karypis:
Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs. ECML/PKDD (3) 2023: 157-173 - [c206]Zhenkun Cai, Qihui Zhou, Xiao Yan, Da Zheng, Xiang Song, Chenguang Zheng, James Cheng, George Karypis:
DSP: Efficient GNN Training with Multiple GPUs. PPoPP 2023: 392-404 - [c205]Hongkuan Zhou, Da Zheng, Xiang Song, George Karypis, Viktor K. Prasanna:
DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training. SC 2023: 39:1-39:12 - [c204]Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espín-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu:
Tutorials at The Web Conference 2023. WWW (Companion Volume) 2023: 648-658 - [c203]Vachik S. Dave, Linsey Pang, Xiquan Cui, Lingfei Wu, Hamed Zamani, George Karypis:
The 2nd Workshop on Interactive and Scalable Information Retrieval Methods for eCommerce (ISIR-eCom). WWW (Companion Volume) 2023: 850-853 - [i83]Hengrui Zhang, Shen Wang, Vassilis N. Ioannidis, Soji Adeshina, Jiani Zhang, Xiao Qin, Christos Faloutsos, Da Zheng, George Karypis, Philip S. Yu:
OrthoReg: Improving Graph-regularized MLPs via Orthogonality Regularization. CoRR abs/2302.00109 (2023) - [i82]Zhuosheng Zhang, Aston Zhang, Mu Li, Hai Zhao, George Karypis, Alex Smola:
Multimodal Chain-of-Thought Reasoning in Language Models. CoRR abs/2302.00923 (2023) - [i81]Danilo Neves Ribeiro, Shen Wang, Xiaofei Ma, Henry Zhu, Rui Dong, Deguang Kong, Juliette Burger, Anjelica Ramos, William Yang Wang, Zhiheng Huang, George Karypis, Bing Xiang, Dan Roth:
STREET: A Multi-Task Structured Reasoning and Explanation Benchmark. CoRR abs/2302.06729 (2023) - [i80]Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang, Da Zheng, Soji Adeshina, Jun Ma, Han Zhao, Christos Faloutsos, George Karypis:
Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs. CoRR abs/2304.10668 (2023) - [i79]Bingzhao Zhu, Xingjian Shi, Nick Erickson, Mu Li, George Karypis, Mahsa Shoaran:
XTab: Cross-table Pretraining for Tabular Transformers. CoRR abs/2305.06090 (2023) - [i78]Hengzhi Pei, Jinman Zhao, Leonard Lausen, Sheng Zha, George Karypis:
Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion. CoRR abs/2306.00381 (2023) - [i77]Tuan Dinh, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis:
Large Language Models of Code Fail at Completing Code with Potential Bugs. CoRR abs/2306.03438 (2023) - [i76]Hongkuan Zhou, Da Zheng, Xiang Song, George Karypis, Viktor K. Prasanna:
DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training. CoRR abs/2307.07649 (2023) - [i75]Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis:
HYTREL: Hypergraph-enhanced Tabular Data Representation Learning. CoRR abs/2307.08623 (2023) - [i74]Ruixuan Liu, Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis:
Coupling public and private gradient provably helps optimization. CoRR abs/2310.01304 (2023) - [i73]Hengrui Zhang, Jiani Zhang, Balasubramaniam Srinivasan, Zhengyuan Shen, Xiao Qin, Christos Faloutsos, Huzefa Rangwala, George Karypis:
Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space. CoRR abs/2310.09656 (2023) - [i72]Deepak Ajwani, Rob H. Bisseling, Katrin Casel, Ümit V. Çatalyürek, Cédric Chevalier, Florian Chudigiewitsch, Marcelo Fonseca Faraj, Michael R. Fellows, Lars Gottesbüren, Tobias Heuer, George Karypis, Kamer Kaya, Jakub Lacki, Johannes Langguth, Xiaoye Sherry Li, Ruben Mayer, Johannes Meintrup, Yosuke Mizutani, François Pellegrini, Fabrizio Petrini, Frances A. Rosamond, Ilya Safro, Sebastian Schlag, Christian Schulz, Roohani Sharma, Darren Strash, Blair D. Sullivan, Bora Uçar, Albert-Jan Yzelman:
Open Problems in (Hyper)Graph Decomposition. CoRR abs/2310.11812 (2023) - [i71]Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Shen Wang, Huzefa Rangwala, George Karypis:
NameGuess: Column Name Expansion for Tabular Data. CoRR abs/2310.13196 (2023) - [i70]Petros Karypis, Julian J. McAuley, George Karypis:
Extending Input Contexts of Language Models through Training on Segmented Sequences. CoRR abs/2310.14633 (2023) - [i69]Zhiqi Bu, Ruixuan Liu, Yu-Xiang Wang, Sheng Zha, George Karypis:
On the accuracy and efficiency of group-wise clipping in differentially private optimization. CoRR abs/2310.19215 (2023) - [i68]Costas Mavromatis, Balasubramaniam Srinivasan, Zhengyuan Shen, Jiani Zhang, Huzefa Rangwala, Christos Faloutsos, George Karypis:
Which Examples to Annotate for In-Context Learning? Towards Effective and Efficient Selection. CoRR abs/2310.20046 (2023) - [i67]Zhiqi Bu, Justin Chiu, Ruixuan Liu, Sheng Zha, George Karypis:
Zero redundancy distributed learning with differential privacy. CoRR abs/2311.11822 (2023) - [i66]George Karypis, Christian Schulz, Darren Strash, Deepak Ajwani, Rob H. Bisseling, Katrin Casel, Ümit V. Çatalyürek, Cédric Chevalier, Florian Chudigiewitsch, Marcelo Fonseca Faraj, Michael R. Fellows, Lars Gottesbüren, Tobias Heuer, Kamer Kaya, Jakub Lacki, Johannes Langguth, Xiaoye Sherry Li, Ruben Mayer, Johannes Meintrup, Yosuke Mizutani, François Pellegrini, Fabrizio Petrini, Frances A. Rosamond, Ilya Safro, Sebastian Schlag, Roohani Sharma, Blair D. Sullivan, Bora Uçar, Albert-Jan Yzelman:
Recent Trends in Graph Decomposition (Dagstuhl Seminar 23331). Dagstuhl Reports 13(8): 1-45 (2023) - 2022
- [j84]Hongkuan Zhou, Da Zheng, Israt Nisa, Vassilis N. Ioannidis, Xiang Song, George Karypis:
TGL: A General Framework for Temporal GNN Training onBillion-Scale Graphs. Proc. VLDB Endow. 15(8): 1572-1580 (2022) - [j83]Zhen Zhang, Shuai Zheng, Yida Wang, Justin Chiu, George Karypis, Trishul Chilimbi, Mu Li, Xin Jin:
MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud. Proc. VLDB Endow. 16(1): 37-50 (2022) - [j82]Zhuliu Li, Raphael Petegrosso, Shaden Smith, David Sterling, George Karypis, Rui Kuang:
Scalable Label Propagation for Multi-Relational Learning on the Tensor Product of Graphs. IEEE Trans. Knowl. Data Eng. 34(12): 5964-5978 (2022) - [j81]Maria Kalantzi, Agoritsa Polyzou, George Karypis:
FERN: Fair Team Formation for Mutually Beneficial Collaborative Learning. IEEE Trans. Learn. Technol. 15(6): 757-770 (2022) - [j80]Yixin Liu, Zhao Li, Shirui Pan, Chen Gong, Chuan Zhou, George Karypis:
Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2378-2392 (2022) - [c202]Costas Mavromatis, Prasanna Lakkur Subramanyam, Vassilis N. Ioannidis, Adesoji Adeshina, Phillip Ryan Howard, Tetiana Grinberg, Nagib Hakim, George Karypis:
TempoQR: Temporal Question Reasoning over Knowledge Graphs. AAAI 2022: 5825-5833 - [c201]Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He:
Meta-learning via Language Model In-context Tuning. ACL (1) 2022: 719-730 - [c200]Trong Nghia Hoang, Anoop Deoras, Tong Zhao, Jin Li, George Karypis:
Learning Personalized Item-to-Item Recommendation Metric via Implicit Feedback. AISTATS 2022: 1062-1077 - [c199]Costas Mavromatis, George Karypis:
ReaRev: Adaptive Reasoning for Question Answering over Knowledge Graphs. EMNLP (Findings) 2022: 2447-2458 - [c198]Soji Adeshina, Jian Zhang, Muhyun Kim, Min Chen, Rizal Fathony, Advitiya Vashisht, Jia Chen, George Karypis:
PropInit: Scalable Inductive Initialization for Heterogeneous Graph Neural Networks. ICKG 2022: 6-13 - [c197]Chunxing Yin, Da Zheng, Israt Nisa, Christos Faloutsos, George Karypis, Richard W. Vuduc:
Nimble GNN Embedding with Tensor-Train Decomposition. KDD 2022: 2327-2335 - [c196]Da Zheng, Xiang Song, Chengru Yang, Dominique LaSalle, George Karypis:
Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Heterogeneous Graphs. KDD 2022: 4582-4591 - [c195]Zhenwei Dai, Vasileios Ioannidis, Soji Adeshina, Zak Jost, Christos Faloutsos, George Karypis:
ScatterSample: Diversified Label Sampling for Data Efficient Graph Neural Network Learning. LoG 2022: 35 - [c194]Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis:
Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. NAACL-HLT 2022: 2542-2550 - [c193]Zeren Shui, Daniel S. Karls, Mingjian Wen, Ilia A. Nikiforov, Ellad B. Tadmor, George Karypis:
Injecting Domain Knowledge from Empirical Interatomic Potentials to Neural Networks for Predicting Material Properties. NeurIPS 2022 - [c192]Ancy Sarah Tom, Nesreen K. Ahmed, George Karypis:
Joint Learning of Hierarchical Community Structure and Node Representations: An Unsupervised Approach. ECML/PKDD (2) 2022: 86-103 - [c191]Jiacheng Li, Tong Zhao, Jin Li, Jim Chan, Christos Faloutsos, George Karypis, Soo-Min Pantel, Julian J. McAuley:
Coarse-to-Fine Sparse Sequential Recommendation. SIGIR 2022: 2082-2086 - [c190]George Karypis:
Graph Neural Network Research at AWS AI. WSDM 2022: 4 - [r6]Athanasios N. Nikolakopoulos, Xia Ning, Christian Desrosiers, George Karypis:
Trust Your Neighbors: A Comprehensive Survey of Neighborhood-Based Methods for Recommender Systems. Recommender Systems Handbook 2022: 39-89 - [i65]Ancy Sarah Tom, Nesreen K. Ahmed, George Karypis:
Joint Learning of Hierarchical Community Structure and Node Representations: An Unsupervised Approach. CoRR abs/2201.09086 (2022) - [i64]Trong Nghia Hoang, Anoop Deoras, Tong Zhao, Jin Li, George Karypis:
Learning Personalized Item-to-Item Recommendation Metric via Implicit Feedback. CoRR abs/2203.12598 (2022) - [i63]Hongkuan Zhou, Da Zheng, Israt Nisa, Vasileios Ioannidis, Xiang Song, George Karypis:
TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs. CoRR abs/2203.14883 (2022) - [i62]Jiacheng Li, Tong Zhao, Jin Li, Jim Chan, Christos Faloutsos, George Karypis, Soo-Min Pantel, Julian J. McAuley:
Coarse-to-Fine Sparse Sequential Recommendation. CoRR abs/2204.01839 (2022) - [i61]Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis:
Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. CoRR abs/2204.11117 (2022) - [i60]Zhen Zhang, Shuai Zheng, Yida Wang, Justin Chiu, George Karypis, Trishul Chilimbi, Mu Li, Xin Jin:
MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud. CoRR abs/2205.00119 (2022) - [i59]Zhenwei Dai, Vasileios Ioannidis, Soji Adeshina, Zak Jost, Christos Faloutsos, George Karypis:
ScatterSample: Diversified Label Sampling for Data Efficient Graph Neural Network Learning. CoRR abs/2206.04255 (2022) - [i58]Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis:
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger. CoRR abs/2206.07136 (2022) - [i57]Chunxing Yin, Da Zheng, Israt Nisa, Christos Faloutsos, George Karypis, Richard W. Vuduc:
Nimble GNN Embedding with Tensor-Train Decomposition. CoRR abs/2206.10581 (2022) - [i56]Vassilis N. Ioannidis, Xiang Song, Da Zheng, Houyu Zhang, Jun Ma, Yi Xu, Belinda Zeng, Trishul Chilimbi, George Karypis:
Efficient and effective training of language and graph neural network models. CoRR abs/2206.10781 (2022) - [i55]Yulun Wu, Layne C. Price, Zichen Wang, Vassilis N. Ioannidis, George Karypis:
Variational Causal Inference. CoRR abs/2209.05935 (2022) - [i54]Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis:
Differentially Private Bias-Term only Fine-tuning of Foundation Models. CoRR abs/2210.00036 (2022) - [i53]Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis:
Differentially Private Optimization on Large Model at Small Cost. CoRR abs/2210.00038 (2022) - [i52]Yulun Wu, Robert A. Barton, Zichen Wang, Vassilis N. Ioannidis, Carlo De Donno, Layne C. Price, Luis F. Voloch, George Karypis:
Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information. CoRR abs/2210.00116 (2022) - [i51]Zeren Shui, Daniel S. Karls, Mingjian Wen, Ilia A. Nikiforov, Ellad B. Tadmor, George Karypis:
Injecting Domain Knowledge from Empirical Interatomic Potentials to Neural Networks for Predicting Material Properties. CoRR abs/2210.08047 (2022) - [i50]Costas Mavromatis, George Karypis:
ReaRev: Adaptive Reasoning for Question Answering over Knowledge Graphs. CoRR abs/2210.13650 (2022) - [i49]Chaoyang He, Shuai Zheng, Aston Zhang, George Karypis, Trishul Chilimbi, Mahdi Soltanolkotabi, Salman Avestimehr:
SMILE: Scaling Mixture-of-Experts with Efficient Bi-level Routing. CoRR abs/2212.05191 (2022) - 2021
- [c189]Saurav Manchanda, George Karypis:
Importance Assessment in Scholarly Networks. SDU@AAAI 2021 - [c188]Saurav Manchanda, Da Zheng, George Karypis:
Schema-Aware Deep Graph Convolutional Networks for Heterogeneous Graphs. IEEE BigData 2021: 480-489 - [c187]Saurav Manchanda, Mohit Sharma, George Karypis:
Distant-Supervised Slot-Filling for E-Commerce Queries. IEEE BigData 2021: 677-686 - [c186]Maria Kalantzi, George Karypis:
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