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20212023
most citedInformed Learning by Wide Neural Networks: Convergence, Generalization and Sampling Complexity

1 citations · 3 across the 5 of their papers we have counts for

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5 papers

physics.optics20231 cited

Graphene/silicon heterojunction for reconfigurable phase-relevant activation function in coherent optical neural networks

Chuyu Zhong, Kun Liao, Tianxiang Dai +18

Optical neural networks (ONNs) herald a new era in information and communication technologies and have implemented various intelligent applications. In an ONN, the activation funct…

cs.LG20231 cited

Learning for Edge-Weighted Online Bipartite Matching with Robustness Guarantees

Pengfei Li, Jianyi Yang, Shaolei Ren

Many problems, such as online ad display, can be formulated as online bipartite matching. The crucial challenge lies in the nature of sequentially-revealed online item information,…

cs.LG2023

Robustified Learning for Online Optimization with Memory Costs

Pengfei Li, Jianyi Yang, Shaolei Ren

Online optimization with memory costs has many real-world applications, where sequential actions are made without knowing the future input. Nonetheless, the memory cost couples the…

cs.LG20221 cited

Informed Learning by Wide Neural Networks: Convergence, Generalization and Sampling Complexity

Jianyi Yang, Shaolei Ren

By integrating domain knowledge with labeled samples, informed machine learning has been emerging to improve the learning performance for a wide range of applications. Nonetheless,…

cs.LG2021

Learning for Robust Combinatorial Optimization: Algorithm and Application

Zhihui Shao, Jianyi Yang, Cong Shen +1

Learning to optimize (L2O) has recently emerged as a promising approach to solving optimization problems by exploiting the strong prediction power of neural networks and offering l…