Zhenheng Tang
Orcid: 0000-0001-8769-9974
According to our database1,
Zhenheng Tang
authored at least 29 papers
between 2019 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2024
FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion.
CoRR, 2024
CoRR, 2024
ExpertFlow: Optimized Expert Activation and Token Allocation for Efficient Mixture-of-Experts Inference.
CoRR, 2024
FusionLLM: A Decentralized LLM Training System on Geo-distributed GPUs with Adaptive Compression.
CoRR, 2024
Bandwidth-Aware and Overlap-Weighted Compression for Communication-Efficient Federated Learning.
Proceedings of the 53rd International Conference on Parallel Processing, 2024
Pruner-Zero: Evolving Symbolic Pruning Metric From Scratch for Large Language Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
VMRNN: Integrating Vision Mamba and LSTM for Efficient and Accurate Spatiotemporal Forecasting.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
2023
GossipFL: A Decentralized Federated Learning Framework With Sparsified and Adaptive Communication.
IEEE Trans. Parallel Distributed Syst., March, 2023
Reliable and Efficient In-Memory Fault Tolerance of Large Language Model Pretraining.
CoRR, 2023
FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs.
CoRR, 2023
FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training.
CoRR, 2023
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning.
Proceedings of the International Conference on Machine Learning, 2022
2021
IEEE Netw., 2021
2020
Communication-Efficient Distributed Deep Learning: Survey, Evaluation, and Challenges.
CoRR, 2020
CoRR, 2020
Communication-Efficient Decentralized Learning with Sparsification and Adaptive Peer Selection.
Proceedings of the 40th IEEE International Conference on Distributed Computing Systems, 2020
Layer-Wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020
Benchmarking the Performance and Energy Efficiency of AI Accelerators for AI Training.
Proceedings of the 20th IEEE/ACM International Symposium on Cluster, 2020
2019
A Convergence Analysis of Distributed SGD with Communication-Efficient Gradient Sparsification.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
A Distributed Synchronous SGD Algorithm with Global Top-k Sparsification for Low Bandwidth Networks.
Proceedings of the 39th IEEE International Conference on Distributed Computing Systems, 2019
The Impact of GPU DVFS on the Energy and Performance of Deep Learning: an Empirical Study.
Proceedings of the Tenth ACM International Conference on Future Energy Systems, 2019
Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019