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cs.LG2025
Efficient Differentially Private Fine-Tuning of LLMs via Reinforcement Learning
Afshin Khadangi, Amir Sartipi, Igor Tchappi +2
The tension between data privacy and model utility has become the defining bottleneck for the practical deployment of large language models (LLMs) trained on sensitive corpora incl…
cs.LG2025★ 4 cited
Benchmarking Pre-Trained Time Series Models for Electricity Price Forecasting
Timothée Hornek Amir Sartipi, Igor Tchappi, Gilbert Fridgen
Accurate electricity price forecasting (EPF) is crucial for effective decision-making in power trading on the spot market. While recent advances in generative artificial intelligen…