Mu Li

According to our database, Mu Li authored at least 63 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Improving Semantic Segmentation via Efficient Self-Training.

Yi Zhu, Zhongyue Zhang, Chongruo Wu, Zhi Zhang, Tong He, Hang Zhang, R. Manmatha, Mu Li, Alexander J. Smola

IEEE Trans. Pattern Anal. Mach. Intell., March, 2024

2023

What Makes for Good Tokenizers in Vision Transformer?

Shengju Qian, Yi Zhu, Wenbo Li, Mu Li, Jiaya Jia

IEEE Trans. Pattern Anal. Mach. Intell., November, 2023

RAF: Holistic Compilation for Deep Learning Model Training.

Cody Hao Yu, Haozheng Fan, Guangtai Huang, Zhen Jia, Yizhi Liu, Jie Wang, Zach Zheng, Yuan Zhou, Haichen Shen, Junru Shao, Mu Li, Yida Wang

CoRR, 2023

LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation.

Jiaxin Cheng, Xiao Liang, Xingjian Shi, Tong He, Tianjun Xiao, Mu Li

CoRR, 2023

GFM: Building Geospatial Foundation Models via Continual Pretraining.

Matías Mendieta, Boran Han, Xingjian Shi, Yi Zhu, Chen Chen, Mu Li

CoRR, 2023

Multimodal Chain-of-Thought Reasoning in Language Models.

Zhuosheng Zhang, Aston Zhang, Mu Li, Hai Zhao, George Karypis, Alex Smola

CoRR, 2023

MixGen: A New Multi-Modal Data Augmentation.

Xiaoshuai Hao, Yi Zhu, Srikar Appalaraju, Aston Zhang, Wanqian Zhang, Bo Li, Mu Li

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2023

Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition.

Shuhuai Ren, Aston Zhang, Yi Zhu, Shuai Zhang, Shuai Zheng, Mu Li, Alexander J. Smola, Xu Sun

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PreDiff: Precipitation Nowcasting with Latent Diffusion Models.

Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Yi Zhu, Mu Li, Yuyang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

XTab: Cross-table Pretraining for Tabular Transformers.

Bingzhao Zhu, Xingjian Shi, Nick Erickson, Mu Li, George Karypis, Mahsa Shoaran

Proceedings of the International Conference on Machine Learning, 2023

AIM: Adapting Image Models for Efficient Video Action Recognition.

Taojiannan Yang, Yi Zhu, Yusheng Xie, Aston Zhang, Chen Chen, Mu Li

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning Multimodal Data Augmentation in Feature Space.

Zichang Liu, Zhiqiang Tang, Xingjian Shi, Aston Zhang, Mu Li, Anshumali Shrivastava, Andrew Gordon Wilson

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Parameter-Efficient Fine-Tuning Design Spaces.

Jiaao Chen, Aston Zhang, Xingjian Shi, Mu Li, Alex Smola, Diyi Yang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Automatic Chain of Thought Prompting in Large Language Models.

Zhuosheng Zhang, Aston Zhang, Mu Li, Alex Smola

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Cheaper and Better Diffusion Language Model with Soft-Masked Noise.

Jiaao Chen, Aston Zhang, Mu Li, Alex Smola, Diyi Yang

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Tailoring Instructions to Student's Learning Levels Boosts Knowledge Distillation.

Yuxin Ren, Zihan Zhong, Xingjian Shi, Yi Zhu, Chun Yuan, Mu Li

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud.

Zhen Zhang, Shuai Zheng, Yida Wang, Justin Chiu, George Karypis, Trishul Chilimbi, Mu Li, Xin Jin

Proc. VLDB Endow., 2022

SPT: Semi-Parametric Prompt Tuning for Multitask Prompted Learning.

M. Saiful Bari, Aston Zhang, Shuai Zheng, Xingjian Shi, Yi Zhu, Shafiq Joty, Mu Li

CoRR, 2022

Are Multimodal Models Robust to Image and Text Perturbations?

Jielin Qiu, Yi Zhu, Xingjian Shi, Florian Wenzel, Zhiqiang Tang, Ding Zhao, Bo Li, Mu Li

CoRR, 2022

Visual Prompt Tuning for Test-time Domain Adaptation.

Yunhe Gao, Xingjian Shi, Yi Zhu, Hao Wang, Zhiqiang Tang, Xiong Zhou, Mu Li, Dimitris N. Metaxas

CoRR, 2022

Earthformer: Exploring Space-Time Transformers for Earth System Forecasting.

Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition.

Haotao Wang, Aston Zhang, Yi Zhu, Shuai Zheng, Mu Li, Alex J. Smola, Zhangyang Wang

Proceedings of the International Conference on Machine Learning, 2022

Removing Batch Normalization Boosts Adversarial Training.

Haotao Wang, Aston Zhang, Shuai Zheng, Xingjian Shi, Mu Li, Zhangyang Wang

Proceedings of the International Conference on Machine Learning, 2022

BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training.

Likun Cai, Zhi Zhang, Yi Zhu, Li Zhang, Mu Li, Xiangyang Xue

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

ResNeSt: Split-Attention Networks.

Hang Zhang, Chongruo Wu, Zhongyue Zhang, Yi Zhu, Haibin Lin, Zhi Zhang, Yue Sun, Tong He, Jonas Mueller, R. Manmatha, Mu Li, Alexander J. Smola

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

Dive into Deep Learning.

Aston Zhang, Zachary C. Lipton, Mu Li, Alexander J. Smola

CoRR, 2021

SelfNorm and CrossNorm for Out-of-Distribution Robustness.

Zhiqiang Tang, Yunhe Gao, Yi Zhu, Zhi Zhang, Mu Li, Dimitris N. Metaxas

CoRR, 2021

Progressive Coordinate Transforms for Monocular 3D Object Detection.

Li Wang, Li Zhang, Yi Zhu, Zhi Zhang, Tong He, Mu Li, Xiangyang Xue

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Benchmarking Multimodal AutoML for Tabular Data with Text Fields.

Xingjian Shi, Jonas Mueller, Nick Erickson, Mu Li, Alexander J. Smola

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Blending Anti-Aliasing into Vision Transformer.

Shengju Qian, Hao Shao, Yi Zhu, Mu Li, Jiaya Jia

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference.

Haichen Shen, Jared Roesch, Zhi Chen, Wei Chen, Yong Wu, Mu Li, Vin Sharma, Zachary Tatlock, Yida Wang

Proceedings of Machine Learning and Systems 2021, 2021

A Unified Efficient Pyramid Transformer for Semantic Segmentation.

Fangrui Zhu, Yi Zhu, Li Zhang, Chongruo Wu, Yanwei Fu, Mu Li

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

Video Contrastive Learning with Global Context.

Haofei Kuang, Yi Zhu, Zhi Zhang, Xinyu Li, Joseph Tighe, Sören Schwertfeger, Cyrill Stachniss, Mu Li

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

CrossNorm and SelfNorm for Generalization under Distribution Shifts.

Zhiqiang Tang, Yunhe Gao, Yi Zhu, Zhi Zhang, Mu Li, Dimitris N. Metaxas

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing.

Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis

Proceedings of the Second Workshop on Simple and Efficient Natural Language Processing, 2021

Lorien: Efficient Deep Learning Workloads Delivery.

Cody Hao Yu, Xingjian Shi, Haichen Shen, Zhi Chen, Mu Li, Yida Wang

Proceedings of the SoCC '21: ACM Symposium on Cloud Computing, 2021

2020

GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing.

Jian Guo, He He, Tong He, Leonard Lausen, Mu Li, Haibin Lin, Xingjian Shi, Chenguang Wang, Junyuan Xie, Sheng Zha, Aston Zhang, Hang Zhang, Zhi Zhang, Zhongyue Zhang, Shuai Zheng, Yi Zhu

J. Mach. Learn. Res., 2020

A Comprehensive Study of Deep Video Action Recognition.

Yi Zhu, Xinyu Li, Chunhui Liu, Mohammadreza Zolfaghari, Yuanjun Xiong, Chongruo Wu, Zhi Zhang, Joseph Tighe, R. Manmatha, Mu Li

CoRR, 2020

Accelerated Large Batch Optimization of BERT Pretraining in 54 minutes.

Shuai Zheng, Haibin Lin, Sheng Zha, Mu Li

CoRR, 2020

Improving Semantic Segmentation via Self-Training.

Yi Zhu, Zhongyue Zhang, Chongruo Wu, Zhi Zhang, Tong He, Hang Zhang, R. Manmatha, Mu Li, Alexander J. Smola

CoRR, 2020

AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data.

Nick Erickson, Jonas Mueller, Alexander Shirkov, Hang Zhang, Pedro Larroy, Mu Li, Alexander J. Smola

CoRR, 2020

FeatGraph: a flexible and efficient backend for graph neural network systems.

Yuwei Hu, Zihao Ye, Minjie Wang, Jiali Yu, Da Zheng, Mu Li, Zheng Zhang, Zhiru Zhang, Yida Wang

Proceedings of the International Conference for High Performance Computing, 2020

CSER: Communication-efficient SGD with Error Reset.

Cong Xie, Shuai Zheng, Oluwasanmi Koyejo, Indranil Gupta, Mu Li, Haibin Lin

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

On the Powerball Method: Variants of Descent Methods for Accelerated Optimization.

Ye Yuan, Mu Li, Jun Liu, Claire J. Tomlin

IEEE Control. Syst. Lett., 2019

GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing.

Jian Guo, He He, Tong He, Leonard Lausen, Mu Li, Haibin Lin, Xingjian Shi, Chenguang Wang, Junyuan Xie, Sheng Zha, Aston Zhang, Hang Zhang, Zhi Zhang, Zhongyue Zhang, Shuai Zheng

CoRR, 2019

Dynamic Mini-batch SGD for Elastic Distributed Training: Learning in the Limbo of Resources.

Haibin Lin, Hang Zhang, Yifei Ma, Tong He, Zhi Zhang, Sheng Zha, Mu Li

CoRR, 2019

Language Models with Transformers.

Chenguang Wang, Mu Li, Alexander J. Smola

CoRR, 2019

Bag of Freebies for Training Object Detection Neural Networks.

Zhi Zhang, Tong He, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li

CoRR, 2019

Optimizing CNN Model Inference on CPUs.

Yizhi Liu, Yao Wang, Ruofei Yu, Mu Li, Vin Sharma, Yida Wang

Proceedings of the 2019 USENIX Annual Technical Conference, 2019

A Unified Optimization Approach for CNN Model Inference on Integrated GPUs.

Leyuan Wang, Zhi Chen, Yizhi Liu, Yao Wang, Lianmin Zheng, Mu Li, Yida Wang

Proceedings of the 48th International Conference on Parallel Processing, 2019

Bag of Tricks for Image Classification with Convolutional Neural Networks.

Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, Mu Li

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2017

Data Driven Resource Allocation for Distributed Learning.

Travis Dick, Mu Li, Venkata Krishna Pillutla, Colin White, Maria-Florina Balcan, Alexander J. Smola

Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

On the Powerball Method.

Ye Yuan, Mu Li, Claire J. Tomlin

CoRR, 2016

DiFacto: Distributed Factorization Machines.

Mu Li, Ziqi Liu, Alexander J. Smola, Yu-Xiang Wang

Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 2016

AdaDelay: Delay Adaptive Distributed Stochastic Optimization.

Suvrit Sra, Adams Wei Yu, Mu Li, Alexander J. Smola

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

AdaDelay: Delay Adaptive Distributed Stochastic Convex Optimization.

Suvrit Sra, Adams Wei Yu, Mu Li, Alexander J. Smola

CoRR, 2015

Graph Partitioning via Parallel Submodular Approximation to Accelerate Distributed Machine Learning.

Mu Li, Dave G. Andersen, Alexander J. Smola

CoRR, 2015

MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems.

Tianqi Chen, Mu Li, Yutian Li, Min Lin, Naiyan Wang, Minjie Wang, Tianjun Xiao, Bing Xu, Chiyuan Zhang, Zheng Zhang

CoRR, 2015

Inferring Movement Trajectories from GPS Snippets.

Mu Li, Amr Ahmed, Alexander J. Smola

Proceedings of the Eighth ACM International Conference on Web Search and Data Mining, 2015

Cuckoo Linear Algebra.

Li Zhou, David G. Andersen, Mu Li, Alexander J. Smola

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014

Scaling Distributed Machine Learning with the Parameter Server.

Mu Li, David G. Andersen, Jun Woo Park, Alexander J. Smola, Amr Ahmed, Vanja Josifovski, James Long, Eugene J. Shekita, Bor-Yiing Su

Proceedings of the 11th USENIX Symposium on Operating Systems Design and Implementation, 2014

Communication Efficient Distributed Machine Learning with the Parameter Server.

Mu Li, David G. Andersen, Alexander J. Smola, Kai Yu

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Efficient mini-batch training for stochastic optimization.

Mu Li, Tong Zhang, Yuqiang Chen, Alexander J. Smola

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014