Snehanshu Saha

LALR: Theoretical and Experimental validation of Lipschitz Adaptive\n Learning Rate in Regression and Neural Networks

2020 · arXiv (Cornell University)

We propose a theoretical framework for an adaptive learning rate policy for\nthe Mean Absolute Error loss function and Quantile loss function and evaluate\nits effectiveness for regression tasks. The framework is based on the theory of\nLipschitz …

Quantile LSTM: A Robust LSTM for Anomaly Detection In Time Series Data

2023 · arXiv (Cornell University)

Anomalies refer to the departure of systems and devices from their normal behaviour in standard operating conditions. An anomaly in an industrial device can indicate an upcoming failure, often in the temporal direction. In this …