Redder, Adrian, Arunselvan Ramaswamy, and Holger Karl. “Age of Information Process under Strongly Mixing Communication -- Moment Bound, Mixing Rate and Strong Law.” In Proceedings of the 58th Allerton Conference on Communication, Control, and Computing, 2022.
LibreCat: /record/32811

Redder, Adrian, Arunselvan Ramaswamy, and Holger Karl. “Multi-Agent Policy Gradient Algorithms for Cyber-Physical Systems with Lossy Communication.”https://doi.org/10.5220/0010845400003116__In Proceedings of the 14th International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and Technology Publications, 2022.https://doi.org/10.5220/0010845400003116 .
LibreCat: /record/30793
DOI: 10.5220/0010845400003116

Redder, Adrian, Arunselvan Ramaswamy, and Holger Karl. “Distributed Gradient-Based Optimization in the Presence of Dependent  Aperiodic Communication.” ArXiv:2201.11343, 2022.
LibreCat: /record/30790
arXiv: 2201.11343

Redder, Adrian, Arunselvan Ramaswamy, and Holger Karl. “Asymptotic Convergence of Deep Multi-Agent Actor-Critic Algorithms.” ArXiv:2201.00570, 2022.
LibreCat: /record/30791
arXiv: 2201.00570

Redder, Adrian, Arunselvan Ramaswamy, and Holger Karl. “Practical Network Conditions for the Convergence of Distributed Optimization.” IFAC-PapersOnLine 55, no. 13 (2022): 133–138.
LibreCat: /record/32854

Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Analyzing Approximate Value Iteration Algorithms.” Mathematics of Operations Research (to Appear), 2021.
LibreCat: /record/24142

Drees, Jan Peter, Pritha Gupta, Eyke Hüllermeier, Tibor Jager, Alexander Konze, Claudia Priesterjahn, Arunselvan Ramaswamy, and Juraj Somorovsky. “Automated Detection of Side Channels in Cryptographic Protocols: DROWN the ROBOTs!” 14th ACM Workshop on Artificial Intelligence and Security, 2021.
LibreCat: /record/24143

Ramaswamy, Arunselvan, and Eyke Hüllermeier. “Deep Q-Learning: Theoretical Insights from an Asymptotic Analysis.” IEEE Transactions on Artificial Intelligence (to Appear), 2021.
LibreCat: /record/24148

Afifi, Haitham, Arunselvan Ramaswamy, and Holger Karl. “Reinforcement Learning for Autonomous Vehicle Movements in Wireless Sensor Networks.” In 2021 IEEE International Conference on Communications (ICC): IoT and Sensor Networks Symposium (IEEE ICC’21 - IoTSN Symposium). Montreal, Canada, 2021.
LibreCat: /record/21478

Afifi, Haitham, Arunselvan Ramaswamy, and Holger Karl. “A Reinforcement Learning QoI/QoS-Aware Approach in Acoustic Sensor Networks.” In 2021 IEEE 18th Annual Consumer Communications \'26; Networking Conference (CCNC) (CCNC 2021), 2021.
LibreCat: /record/21479

Ramaswamy, Arunselvan, Adrian Redder, and Daniel E. Quevedo. “Distributed Optimization over Time-Varying Networks with Stochastic Information Delays.”https://doi.org/10.1109/TAC.2021.3108492__IEEE Transactions on Automatic Control, 2021, 1–1.https://doi.org/10.1109/TAC.2021.3108492 .
LibreCat: /record/24140
DOI: 10.1109/TAC.2021.3108492

Ramaswamy, Arunselvan. “DSPG: Decentralized Simultaneous Perturbations Gradient Descent Scheme.” In 2020 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), 54–62, 2020.
LibreCat: /record/24145

Heid, Stefan Helmut, Arunselvan Ramaswamy, and Eyke Hüllermeier. “Constrained Multi-Agent Optimization with Unbounded Information Delay.” In Proceedings-30. Workshop Computational Intelligence: Berlin, 26.-27. November 2020, 26:247, 2020.
LibreCat: /record/24146

Ramaswamy, Arunselvan, Shalabh Bhatnagar, and Daniel E Quevedo. “Asynchronous Stochastic Approximations with Asymptotically Biased Errors and Deep Multi-Agent Learning.” IEEE Transactions on Automatic Control, 2020.
LibreCat: /record/24147

König, Jonas, Simon Malberg, Martin Martens, Sebastian Niehaus, Artus Krohn-Grimberghe, and Arunselvan Ramaswamy. “Multi-Stage Reinforcement Learning for Object Detection.” In Science and Information Conference, 178–91, 2019.
LibreCat: /record/24141

Leong, Alex S., Arunselvan Ramaswamy, Daniel E. Quevedo, Holger Karl, and Ling Shi. “Deep Reinforcement Learning for Wireless Sensor Scheduling in Cyber–Physical Systems.”https://doi.org/10.1016/j.automatica.2019.108759__Automatica, 2019.https://doi.org/10.1016/j.automatica.2019.108759 .
LibreCat: /record/15741
DOI: 10.1016/j.automatica.2019.108759

Redder, Adrian, Arunselvan Ramaswamy, and Daniel Quevedo. “Deep Reinforcement Learning for Scheduling in Large-Scale Networked Control Systems.” In Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems, 2019.
LibreCat: /record/13443

Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Stability of Stochastic Approximations with ‘Controlled Markov’ Noise and Temporal Difference Learning.” IEEE Transactions on Automatic Control 64, no. 6 (2018): 2614–20.
LibreCat: /record/24150

Demirel, Burak, Arunselvan Ramaswamy, Daniel E Quevedo, and Holger Karl. “Deepcas: A Deep Reinforcement Learning Algorithm for Control-Aware Scheduling.” IEEE Control Systems Letters 2, no. 4 (2018): 737–42.
LibreCat: /record/24151

Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Analysis of Gradient Descent Methods with Nondiminishing Bounded Errors.” IEEE Transactions on Automatic Control 63, no. 5 (2017): 1465–71.
LibreCat: /record/24152