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20172025
most citedEfficient Learning of Distributed Linear-Quadratic Controllers

8 citations · 38 across the 44 of their papers we have counts for

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Showing 2020Show all

8 papers · 1 filter

cs.LG2020★ 3 cited

Improving Fairness and Privacy in Selection Problems

Mohammad Mahdi Khalili, Xueru Zhang, Mahed Abroshan +1

Supervised learning models have been increasingly used for making decisions about individuals in applications such as hiring, lending, and college admission. These models may inher…

eess.SY2020★ 1 cited

Graph Neural Networks for Distributed Linear-Quadratic Control

Fernando Gama, Somayeh Sojoudi

The linear-quadratic controller is one of the fundamental problems in control theory. The optimal solution is a linear controller that requires access to the state of the entire sy…

cs.LG2020

A Sequential Framework Towards an Exact SDP Verification of Neural Networks

Ziye Ma, Somayeh Sojoudi

Although neural networks have been applied to several systems in recent years, they still cannot be used in safety-critical systems due to the lack of efficient techniques to certi…

cs.LG2020

Certifying Neural Network Robustness to Random Input Noise from Samples

Brendon G. Anderson, Somayeh Sojoudi

Methods to certify the robustness of neural networks in the presence of input uncertainty are vital in safety-critical settings. Most certification methods in the literature are de…

cs.LG2020

Data-Driven Certification of Neural Networks with Random Input Noise

Brendon G. Anderson, Somayeh Sojoudi

Methods to certify the robustness of neural networks in the presence of input uncertainty are vital in safety-critical settings. Most certification methods in the literature are de…

cs.LG2020

Implicit Graph Neural Networks

Fangda Gu, Heng Chang, Wenwu Zhu +2

Graph Neural Networks (GNNs) are widely used deep learning models that learn meaningful representations from graph-structured data. Due to the finite nature of the underlying recur…