Training Recurrent Neural Networks

GPTKB entity

Statements (48)
Predicate Object
gptkbp:instanceOf Machine Learning Task
gptkbp:appliesTo Recurrent Neural Networks
gptkbp:canBe Gated Recurrent Unit
Long Short-Term Memory
gptkbp:canBeAcceleratedBy GPU Computation
TPU Computation
gptkbp:canBeOptimizedWith gptkb:RMSprop
gptkb:Adam_Optimizer
SGD
gptkbp:canBeParallelizedBy gptkb:Truncated_Backpropagation_Through_Time
gptkbp:challenge Exploding Gradient Problem
Vanishing Gradient Problem
https://www.w3.org/2000/01/rdf-schema#label Training Recurrent Neural Networks
gptkbp:implementedIn gptkb:TensorFlow
gptkb:Keras
gptkb:MXNet
gptkb:Theano
gptkb:PyTorch
gptkbp:improves gptkb:Dropout
Batch Normalization
Curriculum Learning
Data Augmentation
Early Stopping
Gradient Clipping
Layer Normalization
Learning Rate Scheduling
Regularization
Scheduled Sampling
Sequence Padding
Teacher Forcing
Weight Initialization
gptkbp:involves Backpropagation Through Time
Gradient Descent
gptkbp:monitors Accuracy
Perplexity
Training Loss
Validation Loss
gptkbp:requires Sequential Data
gptkbp:suffersFrom Overfitting
gptkbp:usedIn gptkb:Machine_Translation
gptkb:Natural_Language_Processing
gptkb:Speech_Recognition
Video Analysis
Music Generation
Text Generation
Time Series Prediction
gptkbp:bfsParent gptkb:Ilya_Sutskever
gptkbp:bfsLayer 5