3 papers
cs.LG2026
Uncertainty-Driven Replay Memory for Reinforcement Learning
Sheeraja Rajakrishnan, Alexander G. Ororbia, Travis Desell +1
Uncertainty estimation provides promising capabilities for reinforcement learning (RL) agents. Notably, estimating uncertainty can reduce the training time and enable agents to obt…
quant-ph2026
GSC-QEMit: A Telemetry-Driven Hierarchical Forecast-and-Bandit Framework for Adaptive Quantum Error Mitigation
Steven Szachara, Sheeraja Rajakrishnan, Dylan Jay Van Allen +3
Quantum error mitigation (QEM) is essential for extracting reliable results from near-term quantum devices, yet practical deployments must balance mitigation strength against runti…
cs.LG2025
Directly Learning Stock Trading Strategies Through Profit Guided Loss Functions
Devroop Kar, Zimeng Lyu, Sheeraja Rajakrishnan +4
Stock trading has always been a challenging task due to the highly volatile nature of the stock market. Making sound trading decisions to generate profit is particularly difficult…