Arunselvan Ramaswamy

发表

Stability of Stochastic Approximations With “Controlled Markov” Noise and Temporal Difference Learning

Shalabh Bhatnagar, Arunselvan Ramaswamy, S. Bhatnagar, 2015, IEEE Transactions on Automatic Control.

Stochastic recursive inclusion in two timescales with an application to the Lagrangian dual problem

S. Bhatnagar, Arunselvan Ramaswamy, 2015 .

Conditions for Stability and Convergence of Set-Valued Stochastic Approximations: Applications to Approximate Value and Fixed point Iterations with Noise pdf

Shalabh Bhatnagar, Arunselvan Ramaswamy, S. Bhatnagar, 2017, ArXiv.

Analysis of Gradient Descent Methods With Nondiminishing Bounded Errors

Shalabh Bhatnagar, Arunselvan Ramaswamy, S. Bhatnagar, 2016, IEEE Transactions on Automatic Control.

On the lock-in probability estimate of stochastic approximation with controlled Markov noise

Vivek S. Borkar, Shalabh Bhatnagar, Prasenjit Karmakar, 2016 .

Optimization over time-varying networks with unbounded delays

Arunselvan Ramaswamy, D. Quevedo, Adrian Redder, 2019, 1912.07055.

Asymptotic and non-asymptotic convergence properties of stochastic approximation with controlled Markov noise using lock-in probability

S. Bhatnagar, V. Borkar, Prasenjit Karmakar, 2016 .

Age of Information Process under Strongly Mixing Communication - Moment Bound, Mixing Rate and Strong Law

Arunselvan Ramaswamy, Holger Karl, Adrian Redder, 2022, 2022 58th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

3DPG: Distributed Deep Deterministic Policy Gradient Algorithms for Networked Multi-Agent Systems

Arunselvan Ramaswamy, Holger Karl, Adrian Redder, 2022, 2201.00570.

Asymptotic Convergence of Deep Multi-Agent Actor-Critic Algorithms

Arunselvan Ramaswamy, Adrian Redder, Holger Karl, 2022 .

A Reinforcement Learning QoI/QoS-Aware Approach in Acoustic Sensor Networks

Holger Karl, Haitham Afifi, Arunselvan Ramaswamy, 2021, 2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC).

Gradient-based learning algorithms with constant-error estimators: stability and convergence

S. Bhatnagar, Arunselvan Ramaswamy, 2016, ArXiv.

Stochastic recursive inclusions with two timescales pdf

Shalabh Bhatnagar, Arunselvan Ramaswamy, S. Bhatnagar, 2015, ArXiv.

Distributed gradient-based optimization in the presence of dependent aperiodic communication

Arunselvan Ramaswamy, Adrian Redder, Holger Karl, 2022, ArXiv.

Deep Reinforcement Learning for Wireless Sensor Scheduling in Cyber-Physical Systems

Ling Shi, Daniel E. Quevedo, Alex S. Leong, 2018, Autom..

DeepCAS: A Deep Reinforcement Learning Algorithm for Control-Aware Scheduling

Daniel E. Quevedo, Holger Karl, Burak Demirel, 2018, IEEE Control Systems Letters.

Reinforcement Learning for Autonomous Vehicle Movements in Wireless Sensor Networks

H. Karl, Arunselvan Ramaswamy, Haitham Afifi, 2021, ICC 2021 - IEEE International Conference on Communications.

A Generalization of the Borkar-Meyn Theorem for Stochastic Recursive Inclusions pdf

Shalabh Bhatnagar, Arunselvan Ramaswamy, S. Bhatnagar, 2015, Math. Oper. Res..

Theory of Deep Q-Learning: A Dynamical Systems Perspective pdf

Arunselvan Ramaswamy, Arunselvan Ramaswamy, 2020, ArXiv.

Analysis of Set-Valued Stochastic Approximations: Applications to Noisy Approximate Value and Fixed point Iterations

S. Bhatnagar, Arunselvan Ramaswamy, 2017 .

Reinforcement learning for autonomous vehicle movements in wireless multimedia applications

Arunselvan Ramaswamy, Holger Karl, Haitham Afifi, 2023, Pervasive and Mobile Computing.

DSPG: Decentralized Simultaneous Perturbations Gradient Descent Scheme

Arunselvan Ramaswamy, Arunselvan Ramaswamy, 2019, 2020 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP).

Automated Information Leakage Detection: A New Method Combining Machine Learning and Hypothesis Testing with an Application to Side-channel Detection in Cryptographic Protocols

Arunselvan Ramaswamy, E. Hüllermeier, Tibor Jager, 2022, ICAART.

Stability and Convergence of Distributed Stochastic Approximations with large Unbounded Stochastic Information Delays

Arunselvan Ramaswamy, Holger Karl, Adrian Redder, 2023, ArXiv.

Practical Network Conditions for the Convergence of Distributed Optimization

Arunselvan Ramaswamy, Holger Karl, Adrian Redder, 2022, IFAC-PapersOnLine.

A Framework for Provably Stable and Consistent Training of Deep Feedforward Networks

S. Bhatnagar, Arunselvan Ramaswamy, Naman Saxena, 2023, ArXiv.

Deep reinforcement learning for scheduling in large-scale networked control systems pdf

Daniel E. Quevedo, Arunselvan Ramaswamy, Adrian Redder, 2019, IFAC-PapersOnLine.