Application of the Modified Fixed-Lag Smoother in TAGI-LSTM

In this seminar, I presented the application of the modified fixed-lag smoother in TAGI-LSTM, enabling the model to learn without traditional epochs.

This approach allows TAGI-LSTM to transition from offline to online learning, making it more adaptable to real-time data. I also discussed challenges such as optimizing the fixed-lag window size and addressing potential overfitting.

Source: CIV-ML’s Seminars