Easwar Subramanian

Orcid: 0000-0002-9120-6164

According to our database1, Easwar Subramanian authored at least 19 papers between 2007 and 2024.

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

Timeline

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Bibliography

2024
Optimizing Prosumer Policies in Periodic Double Auctions Inspired by Equilibrium Analysis (Extended Version).
CoRR, 2024

Optimizing Prosumer Policies in Periodic Double Auctions Inspired by Equilibrium Analysis.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

A Novel Bidding Strategy for PDAs Using MCTS in Continuous Action Spaces.
Proceedings of the Engineering Multi-Agent Systems - 12th International Workshop, 2024

2023
Multi-armed Bandit Based Tariff Generation Strategy for Multi-agent Smart Grid Systems.
Proceedings of the Engineering Multi-Agent Systems - 11th International Workshop, 2023

A Nash Equilibrium Solution for Periodic Double Auctions.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022
Electricity Consumption Forecasting for Out-of-distribution Time-of-Use Tariffs.
CoRR, 2022

VidyutVanika21: An Autonomous Intelligent Broker for Smart-grids.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Multi-unit Double Auctions: Equilibrium Analysis and Bidding Strategy using DDPG in Smart-grids.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2020
Bidding Strategy for Two-Sided Electricity Markets: A Reinforcement Learning based Framework.
Proceedings of the BuildSys '20: The 7th ACM International Conference on Systems for Energy-Efficient Buildings, 2020

Bidding in Smart Grid PDAs: Theory, Analysis and Strategy.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Bidding in Smart Grid PDAs: Theory, Analysis and Strategy (Extended Version).
CoRR, 2019

Sparse Recurrent Mixture Density Networks for Forecasting High Variability Time Series with Confidence Estimates.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Deep Learning, 2019

lEarn: A Reinforcement Learning Based Bidding Strategy for Generators in Single sided Energy Markets.
Proceedings of the Tenth ACM International Conference on Future Energy Systems, 2019

Load Forecasting in Energy Markets: An Approach Using Sparse Neural Networks.
Proceedings of the Tenth ACM International Conference on Future Energy Systems, 2019

VidyutVanika: A Reinforcement Learning Based Broker Agent for a Power Trading Competition.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2015
Discrete-Time Quadratic-Optimal Hedging Strategies for European Contingent Claims.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2015

On Accelerating Concurrent PCA Computations for Financial Risk Applications.
Proceedings of the 22nd IEEE International Conference on High Performance Computing, 2015

2014
Explicit solutions of discrete-time quadratic optimal hedging strategies for European contingent claims.
Proceedings of the IEEE Conference on Computational Intelligence for Financial Engineering & Economics, 2014

2007
Motion detection, noise reduction, texture suppression, and contour enhancement by spatiotemporal Gabor filters with surround inhibition.
Biol. Cybern., 2007


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