Shahin Shahrampour
Orcid: 0000-0003-3093-8510
According to our database1,
Shahin Shahrampour
authored at least 71 papers
between 2013 and 2024.
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Bibliography
2024
IEEE Trans. Autom. Control., April, 2024
IEEE Trans. Autom. Control., January, 2024
Trans. Mach. Learn. Res., 2024
Linear Convergence of Independent Natural Policy Gradient in Games With Entropy Regularization.
IEEE Control. Syst. Lett., 2024
IEEE Control. Syst. Lett., 2024
Online Optimization Perspective on First-Order and Zero-Order Decentralized Nonsmooth Nonconvex Stochastic Optimization.
CoRR, 2024
Global Convergence of Decentralized Retraction-Free Optimization on the Stiefel Manifold.
CoRR, 2024
Regret Analysis of Policy Optimization over Submanifolds for Linearly Constrained Online LQG.
CoRR, 2024
An Online Optimization Perspective on First-Order and Zero-Order Decentralized Nonsmooth Nonconvex Stochastic Optimization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
TAKDE: Temporal Adaptive Kernel Density Estimator for Real-Time Dynamic Density Estimation.
IEEE Trans. Pattern Anal. Mach. Intell., November, 2023
IEEE Trans. Neural Networks Learn. Syst., August, 2023
On Centralized and Distributed Mirror Descent: Convergence Analysis Using Quadratic Constraints.
IEEE Trans. Autom. Control., May, 2023
Dynamic Regret Analysis of Safe Distributed Online Optimization for Convex and Non-convex Problems.
Trans. Mach. Learn. Res., 2023
Regret Analysis of Distributed Online Control for LTI Systems with Adversarial Disturbances.
CoRR, 2023
CoRR, 2023
Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the American Control Conference, 2023
2022
RFN: A Random-Feature Based Newton Method for Empirical Risk Minimization in Reproducing Kernel Hilbert Spaces.
IEEE Trans. Signal Process., 2022
On Distributed Nonconvex Optimization: Projected Subgradient Method for Weakly Convex Problems in Networks.
IEEE Trans. Autom. Control., 2022
Proceedings of the IEEE International Conference on Acoustics, 2022
Tracking Dynamic Gaussian Density with a Theoretically Optimal Sliding Window Approach.
Proceedings of the Dynamic Data Driven Applications Systems - 4th International Conference, 2022
Distributed Online System Identification for LTI Systems Using Reverse Experience Replay.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022
2021
Classification of Officers' Driving Situations Based on Eye-Tracking and Driver Performance Measures.
IEEE Trans. Hum. Mach. Syst., 2021
Distributed Mirror Descent With Integral Feedback: Asymptotic Convergence Analysis of Continuous-Time Dynamics.
IEEE Control. Syst. Lett., 2021
On Centralized and Distributed Mirror Descent: Exponential Convergence Analysis Using Quadratic Constraints.
CoRR, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Distributed Mirror Descent with Integral Feedback: Convergence Analysis from a Dynamical System Perspective.
Proceedings of the 55th Annual Conference on Information Sciences and Systems, 2021
Linear Convergence of Distributed Mirror Descent with Integral Feedback for Strongly Convex Problems.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021
Proceedings of the 2021 American Control Conference, 2021
On Online Optimization: Dynamic Regret Analysis of Strongly Convex and Smooth Problems.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
IEEE Trans. Control. Netw. Syst., 2020
Finite-Time Guarantees for Byzantine-Resilient Distributed State Estimation With Noisy Measurements.
IEEE Trans. Autom. Control., 2020
Unconstrained Online Optimization: Dynamic Regret Analysis of Strongly Convex and Smooth Problems.
CoRR, 2020
CoRR, 2020
Overcoming the Curse of Dimensionality in Density Estimation with Mixed Sobolev GANs.
CoRR, 2020
A Random-Feature Based Newton Method for Empirical Risk Minimization in Reproducing Kernel Hilbert Space.
CoRR, 2020
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
Proceedings of the 2020 American Control Conference, 2020
Cell Association via Boundary Detection: A Scalable Approach Based on Data-Driven Random Features.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020
Global Convergence of Newton Method for Empirical Risk Minimization in Reproducing Kernel Hilbert Space.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020
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
IEEE Trans. Circuits Syst. II Express Briefs, 2018
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
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
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
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
Proceedings of the 2016 American Control Conference, 2016
2015
IEEE Trans. Autom. Control., 2015
Proceedings of the 54th IEEE Conference on Decision and Control, 2015
Proceedings of the 53rd Annual Allerton Conference on Communication, 2015
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
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
Proceedings of the American Control Conference, 2013