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Found 4 papers, 1 papers with code
Achieving Online Regression Performance of LSTMs with Simple RNNs
Recurrent Neural Networks (RNNs) are widely used for online regression due to their ability to generalize nonlinear temporal dependencies.
RNN-based Online Learning: An Efficient First-Order Optimization Algorithm with a Convergence Guarantee
We investigate online nonlinear regression with continually running recurrent neural network networks (RNNs), i. e., RNN-based online learning.
Minimax Optimal Algorithms for Adversarial Bandit Problem with Multiple Plays
To construct our algorithm, we introduce a new expert advice algorithm for the multiple-play setting.
An Efficient and Effective Second-Order Training Algorithm for LSTM-based Adaptive Learning
We study adaptive (or online) nonlinear regression with Long-Short-Term-Memory (LSTM) based networks, i. e., LSTM-based adaptive learning.
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