Connor Holmes

According to our database, Connor Holmes authored at least 28 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

On Semidefinite Relaxations for Matrix-Weighted State-Estimation Problems in Robotics.

Connor Holmes, Frederike Dümbgen, Timothy D. Barfoot

IEEE Trans. Robotics, 2024

Toward Globally Optimal State Estimation Using Automatically Tightened Semidefinite Relaxations.

Frederike Dümbgen, Connor Holmes, Ben Agro, Timothy D. Barfoot

IEEE Trans. Robotics, 2024

Exploiting Chordal Sparsity for Fast Global Optimality with Application to Localization.

Frederike Dümbgen, Connor Holmes, Timothy D. Barfoot

CoRR, 2024

SDPRLayers: Certifiable Backpropagation Through Polynomial Optimization Problems in Robotics.

Connor Holmes, Frederike Dümbgen, Timothy D. Barfoot

CoRR, 2024

DeepSpeed-FastGen: High-throughput Text Generation for LLMs via MII and DeepSpeed-Inference.

Connor Holmes, Masahiro Tanaka, Michael Wyatt, Ammar Ahmad Awan, Jeff Rasley, Samyam Rajbhandari, Reza Yazdani Aminabadi, Heyang Qin, Arash Bakhtiari, Lev Kurilenko, Yuxiong He

CoRR, 2024

ZeRO++: Extremely Efficient Collective Communication for Large Model Training.

Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Xiaoxia Wu, Connor Holmes, Zhewei Yao, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He

Proceedings of the Twelfth International Conference on Learning Representations, 2024

DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routing.

Conglong Li, Zhewei Yao, Xiaoxia Wu, Minjia Zhang, Connor Holmes, Cheng Li, Yuxiong He

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

An Efficient Global Optimality Certificate for Landmark-Based SLAM.

Connor Holmes, Timothy D. Barfoot

IEEE Robotics Autom. Lett., March, 2023

Safe and Smooth: Certified Continuous-Time Range-Only Localization.

Frederike Dümbgen, Connor Holmes, Timothy D. Barfoot

IEEE Robotics Autom. Lett., 2023

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies.

Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens

CoRR, 2023

STAR-loc: Dataset for STereo And Range-based localization.

Frederike Dümbgen, Mohammed Ayman Shalaby, Connor Holmes, Charles Champagne Cossette, James Richard Forbes, Jerome Le Ny, Timothy D. Barfoot

CoRR, 2023

RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Model.

Fengxiang Bie, Yibo Yang, Zhongzhu Zhou, Adam Ghanem, Minjia Zhang, Zhewei Yao, Xiaoxia Wu, Connor Holmes, Pareesa Ameneh Golnari, David A. Clifton, Yuxiong He, Dacheng Tao, Shuaiwen Leon Song

CoRR, 2023

Certifiably Optimal Rotation and Pose Estimation Based on the Cayley Map.

Timothy D. Barfoot, Connor Holmes, Frederike Dümbgen

CoRR, 2023

DeepSpeed-Chat: Easy, Fast and Affordable RLHF Training of ChatGPT-like Models at All Scales.

Zhewei Yao, Reza Yazdani Aminabadi, Olatunji Ruwase, Samyam Rajbhandari, Xiaoxia Wu, Ammar Ahmad Awan, Jeff Rasley, Minjia Zhang, Conglong Li, Connor Holmes, Zhongzhu Zhou, Michael Wyatt, Molly Smith, Lev Kurilenko, Heyang Qin, Masahiro Tanaka, Shuai Che, Shuaiwen Leon Song, Yuxiong He

CoRR, 2023

ZeRO++: Extremely Efficient Collective Communication for Giant Model Training.

Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Connor Holmes, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He

CoRR, 2023

Towards Open World NeRF-Based SLAM.

Daniil Lisus, Connor Holmes

CoRR, 2023

Towards Open World NeRF-Based SLAM.

Daniil Lisus, Connor Holmes, Steven Lake Waslander

Proceedings of the 20th Conference on Robots and Vision, 2023

2022

Random-LTD: Random and Layerwise Token Dropping Brings Efficient Training for Large-scale Transformers.

Zhewei Yao, Xiaoxia Wu, Conglong Li, Connor Holmes, Minjia Zhang, Cheng Li, Yuxiong He

CoRR, 2022

Compressing Pre-trained Transformers via Low-Bit NxM Sparsity for Natural Language Understanding.

Connor Holmes, Minjia Zhang, Yuxiong He, Bo Wu

CoRR, 2022

A Fine Line: Total Least-Squares Line Fitting as QCQP Optimization.

Timothy D. Barfoot, Connor Holmes, Frederike Dümbgen

CoRR, 2022

DGSM: A GPU-Based Subgraph Isomorphism framework with DFS exploration.

Wei Han, Connor Holmes, Bo Wu

Proceedings of the IEEE/ACM Redefining Scalability for Diversely Heterogeneous Architectures Workshop, 2022

2021

GraphZero: A High-Performance Subgraph Matching System.

Daniel Mawhirter, Sam Reinehr, Connor Holmes, Tongping Liu, Bo Wu

ACM SIGOPS Oper. Syst. Rev., 2021

Practical Design Considerations for Performance and Robustness in the Face of Uncertain Flexible Dynamics in Space Manipulators.

Connor Holmes

Frontiers Robotics AI, 2021

ELIχR: Eliminating Computation Redundancy in CNN-Based Video Processing.

Jordan Schmerge, Daniel Mawhirter, Connor Holmes, Jedidiah McClurg, Bo Wu

Proceedings of the IEEE/ACM Redefining Scalability for Diversely Heterogeneous Architectures Workshop, 2021

NxMTransformer: Semi-Structured Sparsification for Natural Language Understanding via ADMM.

Connor Holmes, Minjia Zhang, Yuxiong He, Bo Wu

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

Dryadic: Flexible and Fast Graph Pattern Matching at Scale.

Daniel Mawhirter, Sam Reinehr, Wei Han, Noah Fields, Miles Claver, Connor Holmes, Jedidiah McClurg, Tongping Liu, Bo Wu

Proceedings of the 30th International Conference on Parallel Architectures and Compilation Techniques, 2021

2019

GraphZero: Breaking Symmetry for Efficient Graph Mining.

Daniel Mawhirter, Sam Reinehr, Connor Holmes, Tongping Liu, Bo Wu

CoRR, 2019

GRNN: Low-Latency and Scalable RNN Inference on GPUs.

Connor Holmes, Daniel Mawhirter, Yuxiong He, Feng Yan, Bo Wu

Proceedings of the Fourteenth EuroSys Conference 2019, Dresden, Germany, March 25-28, 2019, 2019