Publications (127)
All that structure matches does not glitter
Maya M. Martirossyan, Thomas Egg, Philipp Hoellmer +7
Mitra: Mixed Synthetic Priors for Enhancing Tabular Foundation Models
Xiyuan Zhang, Danielle C. Maddix, Junming Yin +11
Optimizing CUDA like a Human: Micro-Profiling Tools as Expert Surrogates for LLM-Based GPU Kernel Optimization
Jiading Gai, Shuai Zhang, Kaj Bostrom +6
HetRL: Efficient Reinforcement Learning for LLMs in Heterogeneous Environments
Yongjun He, Shuai Zhang, Jiading Gai +5
Open Problems in (Hyper)Graph Decomposition
Deepak Ajwani, Rob H. Bisseling, Katrin Casel +26
Will this Course Increase or Decrease Your GPA? Towards Grade-aware Course Recommendation
Sara Morsy, George Karypis
MaxCode: A Max-Reward Reinforcement Learning Framework for Automated Code Optimization
Jiefu Ou, Sapana Chaudhary, Kaj Bostrom +4
Chronos-2: From Univariate to Universal Forecasting
Abdul Fatir Ansari, Oleksandr Shchur, Jaris Küken +20
AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models
Zhiqiang Tang, Haoyang Fang, Su Zhou +5
Adaptive Matrix Completion for the Users and the Items in Tail
Mohit Sharma, George Karypis
Trust your neighbors: A comprehensive survey of neighborhood-based methods for recommender systems
Athanasios N. Nikolakopoulos, Xia Ning, Christian Desrosiers +1
OmniMatch: Effective Self-Supervised Any-Join Discovery in Tabular Data Repositories
Christos Koutras, Jiani Zhang, Xiao Qin +5
DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training
Hongkuan Zhou, Da Zheng, Xiang Song +2
FERN: Fair Team Formation for Mutually Beneficial Collaborative Learning
Maria Kalantzi, Agoritsa Polyzou, George Karypis
Coarse-to-Fine Sparse Sequential Recommendation
Jiacheng Li, Tong Zhao, Jin Li +5
Causal Inference in Higher Education: Building Better Curriculums
Prableen Kaur, Agoritsa Polyzou, George Karypis
DGL-KE: Training Knowledge Graph Embeddings at Scale
Da Zheng, Xiang Song, Chao Ma +6
An Empirical Comparison of Deep Learning Models for Knowledge Tracing on Large-Scale Dataset
Shalini Pandey, George Karypis, Jaideep Srivastava
Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion
Hengzhi Pei, Jinman Zhao, Leonard Lausen +2
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks
Minjie Wang, Da Zheng, Zihao Ye +12
TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs
Hongkuan Zhou, Da Zheng, Israt Nisa +3
Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers
Yingheng Wang, Zichen Wang, Gil Sadeh +4
Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning
Yixin Liu, Zhao Li, Shirui Pan +3
Grade prediction with course and student specific models
Agoritsa Polyzou, George Karypis
Hierarchical Compression of Text-Rich Graphs via Large Language Models
Shichang Zhang, Da Zheng, Jiani Zhang +6
Learning Personalized Item-to-Item Recommendation Metric via Implicit Feedback
Trong Nghia Hoang, Anoop Deoras, Tong Zhao +2
Learning over Families of Sets -- Hypergraph Representation Learning for Higher Order Tasks
Balasubramaniam Srinivasan, Da Zheng, George Karypis
Distributed representation of multi-sense words: A loss-driven approach
Saurav Manchanda, George Karypis
Differentially Private Bias-Term Fine-tuning of Foundation Models
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha +1
Joint Learning of Hierarchical Community Structure and Node Representations: An Unsupervised Approach
Ancy Sarah Tom, Nesreen K. Ahmed, George Karypis
GraphStorm: all-in-one graph machine learning framework for industry applications
Da Zheng, Xiang Song, Qi Zhu +13
NameGuess: Column Name Expansion for Tabular Data
Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan +3
MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud
Zhen Zhang, Shuai Zheng, Yida Wang +5
Differentially Private Optimization on Large Model at Small Cost
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha +1
CAWA: An Attention-Network for Credit Attribution
Saurav Manchanda, George Karypis
Injecting Domain Knowledge from Empirical Interatomic Potentials to Neural Networks for Predicting Material Properties
Zeren Shui, Daniel S. Karls, Mingjian Wen +3
SMILE: Scaling Mixture-of-Experts with Efficient Bi-level Routing
Chaoyang He, Shuai Zheng, Aston Zhang +4
FaiREO: User Group Fairness for Equality of Opportunity in Course Recommendation
Agoritsa Polyzou, Maria Kalantzi, George Karypis
XShare: Collaborative in-Batch Expert Sharing for Faster MoE Inference
Daniil Vankov, Nikita Ivkin, Kyle Ulrich +3
TempoQR: Temporal Question Reasoning over Knowledge Graphs
Costas Mavromatis, Prasanna Lakkur Subramanyam, Vassilis N. Ioannidis +5
Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning
Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros +3
Text segmentation on multilabel documents: A distant-supervised approach
Saurav Manchanda, George Karypis
Fine-Tuning Language Models on Multiple Datasets for Citation Intention Classification
Zeren Shui, Petros Karypis, Daniel S. Karls +4
Pre-training Differentially Private Models with Limited Public Data
Zhiqi Bu, Xinwei Zhang, Mingyi Hong +2
On the accuracy and efficiency of group-wise clipping in differentially private optimization
Zhiqi Bu, Ruixuan Liu, Yu-Xiang Wang +2
ScatterSample: Diversified Label Sampling for Data Efficient Graph Neural Network Learning
Zhenwei Dai, Vasileios Ioannidis, Soji Adeshina +3
MLZero: A Multi-Agent System for End-to-end Machine Learning Automation
Haoyang Fang, Boran Han, Nick Erickson +10
Large Language Models of Code Fail at Completing Code with Potential Bugs
Tuan Dinh, Jinman Zhao, Samson Tan +4
Context-aware Non-linear and Neural Attentive Knowledge-based Models for Grade Prediction
Sara Morsy, George Karypis
Inference Optimization of Foundation Models on AI Accelerators
Youngsuk Park, Kailash Budhathoki, Liangfu Chen +7
Pack of LLMs: Model Fusion at Test-Time via Perplexity Optimization
Costas Mavromatis, Petros Karypis, George Karypis
Sparse Neural Attentive Knowledge-based Models for Grade Prediction
Sara Morsy, George Karypis
A Self-Attentive model for Knowledge Tracing
Shalini Pandey, George Karypis
ProxSparse: Regularized Learning of Semi-Structured Sparsity Masks for Pretrained LLMs
Hongyi Liu, Rajarshi Saha, Zhen Jia +5
OPERA: Online Data Pruning for Efficient Retrieval Model Adaptation
Haoyang Fang, Shuai Zhang, Yifei Ma +5
Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space
Hengrui Zhang, Jiani Zhang, Balasubramaniam Srinivasan +5
Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs
Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang +6
SemPool: Simple, robust, and interpretable KG pooling for enhancing language models
Costas Mavromatis, Petros Karypis, George Karypis
Multimodal Chain-of-Thought Reasoning in Language Models
Zhuosheng Zhang, Aston Zhang, Mu Li +3
Schema-Aware Deep Graph Convolutional Networks for Heterogeneous Graphs
Saurav Manchanda, Da Zheng, George Karypis
Scalable Prompt Routing via Fine-Grained Latent Task Discovery
Yunyi Zhang, Soji Adeshina, Sheng Guan +5
Learning Student Interest Trajectory for MOOCThread Recommendation
Shalini Pandey, Andrew Lan, George Karypis +1
Which Examples to Annotate for In-Context Learning? Towards Effective and Efficient Selection
Costas Mavromatis, Balasubramaniam Srinivasan, Zhengyuan Shen +4
Streaming and Batch Algorithms for Truss Decomposition
Venkata Rohit Jakkula, George Karypis
Position-based Hash Embeddings For Scaling Graph Neural Networks
Maria Kalantzi, George Karypis
DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life Science
Mufei Li, Jinjing Zhou, Jiajing Hu +4
Open Materials Generation with Stochastic Interpolants
Philipp Hoellmer, Thomas Egg, Maya M. Martirossyan +11
P-EAGLE: Parallel-Drafting EAGLE with Scalable Training
Mude Hui, Xin Huang, Jaime Campos Salas +5
Nimble GNN Embedding with Tensor-Train Decomposition
Chunxing Yin, Da Zheng, Israt Nisa +3
Extreme Miscalibration and the Illusion of Adversarial Robustness
Vyas Raina, Samson Tan, Volkan Cevher +3
Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing
Haoyu He, Xingjian Shi, Jonas Mueller +3
ReaRev: Adaptive Reasoning for Question Answering over Knowledge Graphs
Costas Mavromatis, George Karypis
When being Weak is Brave: Privacy in Recommender Systems
Naren Ramakrishnan, Benjamin J. Keller, Batul J. Mirza +2
From Demonstrations to Rewards: Alignment Without Explicit Human Preferences
Siliang Zeng, Yao Liu, Huzefa Rangwala +3
DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs
Da Zheng, Chao Ma, Minjie Wang +6
PropMolFlow: Property-Guided Molecule Generation with Geometry-Complete Flow Matching
Cheng Zeng, Jirui Jin, Connor Ambrose +7
CoddLLM: Empowering Large Language Models for Data Analytics
Jiani Zhang, Hengrui Zhang, Rishav Chakravarti +6
HYTREL: Hypergraph-enhanced Tabular Data Representation Learning
Pei Chen, Soumajyoti Sarkar, Leonard Lausen +4
DualKV: Shared-Prompt Flash Attention for Efficient RL Training with Large Rollouts and Long Contexts
Jiading Gai, Shuai Zhang, Xiang Song +2
Parameter-Efficient Tuning Large Language Models for Graph Representation Learning
Qi Zhu, Da Zheng, Xiang Song +4
Zero redundancy distributed learning with differential privacy
Zhiqi Bu, Justin Chiu, Ruixuan Liu +2
Structured Dictionary Learning for Energy Disaggregation
Shalini Pandey, George Karypis
OpenTab: Advancing Large Language Models as Open-domain Table Reasoners
Kezhi Kong, Jiani Zhang, Zhengyuan Shen +5
Intent term selection and refinement in e-commerce queries
Saurav Manchanda, Mohit Sharma, George Karypis
Variational Causal Inference
Yulun Wu, Layne C. Price, Zichen Wang +3
PanRep: Graph neural networks for extracting universal node embeddings in heterogeneous graphs
Vassilis N. Ioannidis, Da Zheng, George Karypis
Beyond instruction-conditioning, MoTE: Mixture of Task Experts for Multi-task Embedding Models
Miguel Romero, Shuoyang Ding, Corey D. Barret +2
Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information
Yulun Wu, Robert A. Barton, Zichen Wang +5
Repurpose Open Data to Discover Therapeutics for COVID-19 using Deep Learning
Xiangxiang Zeng, Xiang Song, Tengfei Ma +6
XTab: Cross-table Pretraining for Tabular Transformers
Bingzhao Zhu, Xingjian Shi, Nick Erickson +3
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha +1
GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning
Costas Mavromatis, George Karypis
TraverseNet: Unifying Space and Time in Message Passing for Traffic Forecasting
Zonghan Wu, Da Zheng, Shirui Pan +3
Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Graphs
Da Zheng, Xiang Song, Chengru Yang +2
COVID-19 Knowledge Graph: Accelerating Information Retrieval and Discovery for Scientific Literature
Colby Wise, Vassilis N. Ioannidis, Miguel Romero Calvo +6
Understanding Silent Data Corruption in LLM Training
Jeffrey Ma, Hengzhi Pei, Leonard Lausen +1
Efficient and effective training of language and graph neural network models
Vassilis N. Ioannidis, Xiang Song, Da Zheng +6
Benchmarking Accuracy and Generalizability of Four Graph Neural Networks Using Large In Vitro ADME Datasets from Different Chemical Spaces
Fabio Broccatelli, Richard Trager, Michael Reutlinger +2
HeMI: Multi-view Embedding in Heterogeneous Graphs
Costas Mavromatis, George Karypis
A 2D Parallel Triangle Counting Algorithm for Distributed-Memory Architectures
Ancy Sarah Tom, George Karypis