Zesen Wang — accepted AI-conference papers

2025

From Promise to Practice: Realizing High-performance Decentralized Training

Zesen Wang, Jiaojiao Zhang, Xuyang Wu, Mikael Johansson

ICLR 2025poster

Decentralized training of deep neural networks has attracted significant attention for its theoretically superior scalability compared to synchronous data-parallel methods like All-Reduce. However, realizing this potential in multi-node training is challenging due to the complex design space that in…

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2023

Bringing regularized optimal transport to lightspeed: a splitting method adapted for GPUs

Jacob Lindbäck, Zesen Wang, Mikael Johansson

NeurIPS 2023poster

We present an efficient algorithm for regularized optimal transport. In contrast to previous methods, we use the Douglas-Rachford splitting technique to develop an efficient solver that can handle a broad class of regularizers. The algorithm has strong global convergence guarantees, low per-iteratio…

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