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cs.LG2026
FedChronos: Federated Fine-Tuning of Time-Series Foundation Models for Privacy-Preserving Commodity Price Forecasting
Amit Sharma, Nitin Auluck, Akramul Azim
Time-series foundation models (TSFMs) such as Chronos have demonstrated strong forecasting capabilities across domains, yet adapting them to institutionally fragmented settings, wh…
cs.LG2025
Agile Reinforcement Learning for Real-Time Task Scheduling in Edge Computing
Amin Avan, Akramul Azim, Qusay Mahmoud
Soft real-time applications are becoming increasingly complex, posing significant challenges for scheduling offloaded tasks in edge computing environments while meeting task timing…
cs.LG2024
Uncertainty measurement for complex event prediction in safety-critical systems
Maria J. P. Peixoto, Akramul Azim
Complex events originate from other primitive events combined according to defined patterns and rules. Instead of using specialists' manual work to compose the model rules, we use…