3 citations · 4 across the 11 of their papers we have counts for
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stat.ML2024
Self-test loss functions for learning weak-form operators and gradient flows
Yuan Gao, Quanjun Lang, Fei Lu
The construction of loss functions presents a major challenge in data-driven modeling involving weak-form operators in PDEs and gradient flows, particularly due to the need to sele…
cs.LG2024
Towards Faster Decentralized Stochastic Optimization with Communication Compression
Rustem Islamov, Yuan Gao, Sebastian U. Stich
Communication efficiency has garnered significant attention as it is considered the main bottleneck for large-scale decentralized Machine Learning applications in distributed and f…
math.OC2024
Non-convex Stochastic Composite Optimization with Polyak Momentum
Yuan Gao, Anton Rodomanov, Sebastian U. Stich
The stochastic proximal gradient method is a powerful generalization of the widely used stochastic gradient descent (SGD) method and has found numerous applications in Machine Lear…