The Michigan State University AI Research (MAIR), housed within the Department of Computer Science and Engineering (CSE) at Michigan State University (MSU), holds a distinguished position in the dynamic field of Artificial Intelligence (AI). With a rich history of innovation and a commitment to pushing the boundaries of technology, MAIR provides a hub of creativity and discovery in AI research. Led by a diverse team of renowned experts, MAIR endeavors include a wide range of research domains, spanning biometrics, computer vision, data mining, natural language processing, and machine learning. Leveraging interdisciplinary collaborations and state-of-the-art facilities, MAIR is not only advancing the frontiers of AI but also nurturing the next generation of AI leaders and problem solvers. Welcome to the dynamic world of AI research at MSU, where innovation knows no bounds.

Michigan State University AI Research (MAIR) provides a hub of creativity and discovery in AI research
Jan 01, 2024 - Michigan State University AI Research (MAIR) provides a hub of creativity and discovery in AI research

The Michigan State University AI Research (MAIR), housed within the Department of Computer Science and Engineering (CSE) at Michigan State University (MSU), holds a distinguished position in the dynamic field of Artificial Intelligence (AI). With a rich history of innovation and a commitment to pushing the boundaries of technology, MAIR provides a hub of creativity and discovery in AI research. Led by a diverse team of renowned experts, MAIR endeavors include a wide range of research domains, spanning biometrics, computer vision, data mining, natural language processing, and machine learning. Leveraging interdisciplinary collaborations and state-of-the-art facilities, MAIR is not only advancing the frontiers of AI but also nurturing the next generation of AI leaders and problem solvers. Welcome to the dynamic world of AI research at MSU, where innovation knows no bounds.


Tags:
Data Science and Engineering Lab: Tutorial on Scaling New Heights with Large-Scale GNNs has been accepted and will be presented at  AAAI’24
Jan 08, 2024 - Data Science and Engineering Lab: Tutorial on Scaling New Heights with Large-Scale GNNs has been accepted and will be presented at AAAI’24

The Data Science and Engineering Lab is set to present a tutorial at AAAI-24, “Large-Scale Graph Neural Networks: Navigating the Past and Pioneering New Horizons.” Focusing on Graph Neural Networks (GNNs) and their scalability in handling large-scale, real-world graphs, this session will explore the challenges and cutting-edge techniques in deploying GNNs effectively. Ideal for engineers and researchers, the tutorial promises a deep dive into scalable GNN strategies, their evaluation, and practical applications. Details are available on the tutorial’s website: https://sites.google.com/ncsu.edu/largescalegnn/home/aaai_2024.


Tags:

« First ‹ Previous 1 2 3 4 5 Next › Last »

SeaBird: Segmentation in Bird’s View with Dice Loss Improves Monocular 3D Detection of Large Objects
SeaBird: Segmentation in Bird’s View with Dice Loss Improves Monocular 3D Detection of Large Objects
Abhinav Kumar, Yuliang Guo, Xinyu Huang, Liu Ren, Xiaoming Liu. Conference on Computer Vision and Pattern Recognition (CVPR), 2024
Tags:
Code   Article
DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training
DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training
A. Chen*, Y. Zhang*, J. Jia, J. Diffenderfer, J. Liu, K. Parasyris, Y. Zhang, Z. Zhang, B. Kailkhura, S. Liu. International Conference on Learning Representations (ICLR), 2024
Tags:
Code  
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation
C. Fan*, J. Liu*, Y. Zhang, D. Wei, E. Wong, S. Liu. International Conference on Learning Representations (ICLR), 2024 (Spotlight).
Tags:
Code  
FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude
FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude
F. Liu, R. Ashbaugh, N. Chimitt, N. Hassan, A. Hassani, A. Jaiswal, M. Kim, Z. Mao, C. Perry, Z. Ren, Y. Su, P. Varghaei, K. Wang, X. Zhang, S. Chan, A. Ross, H. Shi, Z. Wang, A. Jain, X. Liu. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024
Tags: