Shahin Shahrampour

According to our database1, Shahin Shahrampour authored at least 44 papers between 2013 and 2021.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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On csauthors.net:

Bibliography

2021
Distributed Mirror Descent With Integral Feedback: Asymptotic Convergence Analysis of Continuous-Time Dynamics.
IEEE Control. Syst. Lett., 2021

Decentralized Riemannian Gradient Descent on the Stiefel Manifold.
CoRR, 2021

On the Local Linear Rate of Consensus on the Stiefel Manifold.
CoRR, 2021

2020
An Online Mechanism for Resource Allocation in Networks.
IEEE Trans. Control. Netw. Syst., 2020

Finite-Time Guarantees for Byzantine-Resilient Distributed State Estimation With Noisy Measurements.
IEEE Trans. Autom. Control., 2020

Linear Convergence of Distributed Mirror Descent with Integral Feedback for Strongly Convex Problems.
CoRR, 2020

Distributed Online Linear Quadratic Control for Linear Time-invariant Systems.
CoRR, 2020

Unconstrained Online Optimization: Dynamic Regret Analysis of Strongly Convex and Smooth Problems.
CoRR, 2020

Learning from Non-IID Data in Hilbert Spaces: An Optimal Recovery Perspective.
CoRR, 2020

Overcoming the Curse of Dimensionality in Density Estimation with Mixed Sobolev GANs.
CoRR, 2020

Distributed Projected Subgradient Method for Weakly Convex Optimization.
CoRR, 2020

Generalized Sliced Distances for Probability Distributions.
CoRR, 2020

A Random-Feature Based Newton Method for Empirical Risk Minimization in Reproducing Kernel Hilbert Space.
CoRR, 2020

Statistical and Topological Properties of Sliced Probability Divergences.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features.
Proceedings of the 37th International Conference on Machine Learning, 2020

Distributed Parameter Estimation in Randomized One-hidden-layer Neural Networks.
Proceedings of the 2020 American Control Conference, 2020

2019
Cell Association via Boundary Detection: A Scalable Approach Based on Data-Driven Random Features.
CoRR, 2019

A General Scoring Rule for Randomized Kernel Approximation with Application to Canonical Correlation Analysis.
CoRR, 2019

A Mean-Field Theory for Kernel Alignment with Random Features in Generative Adversarial Networks.
CoRR, 2019

On Sampling Random Features From Empirical Leverage Scores: Implementation and Theoretical Guarantees.
CoRR, 2019

N-Dimensional Distributed Network Localization with Noisy Range Measurements and Arbitrary Anchor Placement.
Proceedings of the 2019 American Control Conference, 2019

2018
Analysis of Multistate Autoregressive Models.
IEEE Trans. Signal Process., 2018

Online Learning for Multimodal Data Fusion With Application to Object Recognition.
IEEE Trans. Circuits Syst. II Express Briefs, 2018

Distributed Online Optimization in Dynamic Environments Using Mirror Descent.
IEEE Trans. Autom. Control., 2018

Learning Bounds for Greedy Approximation with Explicit Feature Maps from Multiple Kernels.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Supervised Learning Using Data-dependent Random Features with Application to Seizure Detection.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

On Data-Dependent Random Features for Improved Generalization in Supervised Learning.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
On Sequential Elimination Algorithms for Best-Arm Identification in Multi-Armed Bandits.
IEEE Trans. Signal Process., 2017

On Optimal Generalizability in Parametric Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Multi-armed bandits in multi-agent networks.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

An online optimization approach for multi-agent tracking of dynamic parameters in the presence of adversarial noise.
Proceedings of the 2017 American Control Conference, 2017

Nonlinear sequential accepts and rejects for identification of top arms in stochastic bandits.
Proceedings of the 55th Annual Allerton Conference on Communication, 2017

2016
Distributed Detection: Finite-Time Analysis and Impact of Network Topology.
IEEE Trans. Autom. Control., 2016

Online optimization in dynamic environments: Improved regret rates for strongly convex problems.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Distributed estimation of dynamic parameters: Regret analysis.
Proceedings of the 2016 American Control Conference, 2016

2015
Topology Identification of Directed Dynamical Networks via Power Spectral Analysis.
IEEE Trans. Autom. Control., 2015

Learning without recall by random walks on directed graphs.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

Switching to learn.
Proceedings of the American Control Conference, 2015

Finite-time analysis of the distributed detection problem.
Proceedings of the 53rd Annual Allerton Conference on Communication, 2015

Online Optimization : Competing with Dynamic Comparators.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2013
Exponentially Fast Parameter Estimation in Networks Using Distributed Dual Averaging.
CoRR, 2013

Online Learning of Dynamic Parameters in Social Networks.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Exponentially fast parameter estimation in networks using distributed dual averagingy.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Reconstruction of directed networks from consensus dynamics.
Proceedings of the American Control Conference, 2013


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