Hongyi Wang

Eric P. Xing

Proceedings of the Seventh Annual Conference on Machine Learning and Systems, 2024

Position: TrustLLM: Trustworthiness in Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Maestro: Uncovering Low-Rank Structures via Trainable Decomposition.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Fusing Models with Complementary Expertise.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

LLM360: Towards Fully Transparent Open-Source LLMs.

[BibT_eX]

[DOI]

CoRR, 2023

PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices.

[BibT_eX]

[DOI]

Minghao Yan

CoRR, 2023

Redco: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs.

[BibT_eX]

[DOI]

CoRR, 2023

SlimPajama-DC: Understanding Data Combinations for LLM Training.

[BibT_eX]

[DOI]

CoRR, 2023

Memory-adaptive Depth-wise Heterogenous Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2023

FedNAR: Federated Optimization with Normalized Annealing Regularization.

[BibT_eX]

[DOI]

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

Cuttlefish: Low-Rank Model Training without All the Tuning.

[BibT_eX]

[DOI]

Pongsakorn U.-Chupala

Yoshiki Tanaka

Eric P. Xing

Dimitris Papailiopoulos

Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

MPCFORMER: Fast, Performant and Provate Transformer Inference with MPC.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

MPCFormer: fast, performant and private Transformer inference with MPC.

[BibT_eX]

[DOI]

CoRR, 2022

Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation.

[BibT_eX]

[DOI]

CoRR, 2022

Rare Gems: Finding Lottery Tickets at Initialization.

[BibT_eX]

[DOI]

CoRR, 2022

Rare Gems: Finding Lottery Tickets at Initialization.

[BibT_eX]

[DOI]

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

AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness.

[BibT_eX]

[DOI]

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

On the Utility of Gradient Compression in Distributed Training Systems.

[BibT_eX]

[DOI]

Proceedings of the Fifth Conference on Machine Learning and Systems, 2022

Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021

Solon: Communication-efficient Byzantine-resilient Distributed Training via Redundant Gradients.

[BibT_eX]

[DOI]

CoRR, 2021

A Field Guide to Federated Optimization.

[BibT_eX]

[DOI]

CoRR, 2021

Pufferfish: Communication-efficient Models At No Extra Cost.

[BibT_eX]

[DOI]

Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

Adaptive Gradient Communication via Critical Learning Regime Identification.

[BibT_eX]

[DOI]

Kangwook Lee

Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

2020

Accordion: Adaptive Gradient Communication via Critical Learning Regime Identification.

[BibT_eX]

[DOI]

Kangwook Lee

CoRR, 2020

FedML: A Research Library and Benchmark for Federated Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Attack of the Tails: Yes, You Really Can Backdoor Federated Learning.

[BibT_eX]

[DOI]

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

Federated Learning with Matched Averaging.

[BibT_eX]

[DOI]

Mikhail Yurochkin

Yuekai Sun

Yasaman Khazaeni

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

ErasureHead: Distributed Gradient Descent without Delays Using Approximate Gradient Coding.

[BibT_eX]

[DOI]

CoRR, 2019

Demonstration of Nimbus: Model-based Pricing for Machine Learning in a Data Marketplace.

[BibT_eX]

[DOI]

Proceedings of the 2019 International Conference on Management of Data, 2019

DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation.

[BibT_eX]

[DOI]

Shashank Rajput

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

DRACO: Robust Distributed Training via Redundant Gradients.

[BibT_eX]

[DOI]

Lingjiao Chen

CoRR, 2018

ATOMO: Communication-efficient Learning via Atomic Sparsification.

[BibT_eX]

[DOI]

Stephen J. Wright

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

The Effect of Network Width on the Performance of Large-batch Training.

[BibT_eX]

[DOI]

Lingjiao Chen

Jinman Zhao

Paraschos Koutris

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

DRACO: Byzantine-resilient Distributed Training via Redundant Gradients.

[BibT_eX]

[DOI]

Lingjiao Chen