Leaky ReLU

GPTKB entity

Properties (57)
Predicate Object
gptkbp:instanceOf activation function
gptkbp:adaptation changing alpha
gptkbp:aimsTo model performance
gptkbp:benefits training deep networks
gptkbp:environmentalProtection dying ReLU problem
gptkbp:has_a alpha
gptkbp:hasPrograms can be tuned for better results
can be used in adversarial training tasks
can be used in batch learning tasks
can be used in classification tasks
can be used in clustering tasks
can be used in deep reinforcement learning tasks
can be used in few-shot learning tasks
can be used in incremental learning tasks
can be used in meta-learning tasks
can be used in multi-task learning tasks
can be used in online learning tasks
can be used in regression tasks
can be used in reinforcement learning tasks
can be used in supervised learning tasks
can be used in transfer learning tasks
can be used in unsupervised learning tasks
can be used in zero-shot learning tasks
can be visualized as a line with a slope
introduces non-linearity
https://www.w3.org/2000/01/rdf-schema#label Leaky ReLU
gptkbp:includes gradient flow
gptkbp:is_a non-linear_activation_function
gptkbp:is_a_document_that allows a small, non-zero gradient when x < 0
gptkbp:is_a_popular_spot_for hidden layers
activation in GANs
standard ReLU in some cases
gptkbp:is_committed_to overfitting
gptkbp:is_evaluated_by efficient
gptkbp:is_expected_to saturate compared to sigmoid
gptkbp:is_popular_among ReLU
gptkbp:is_recognized_for gptkb:PyTorch
gptkb:Keras
TensorFlow
all real numbers
f(x) = x if x > 0, else f(x) = alpha * x
gptkbp:is_used_in deep learning
neural networks
reinforcement learning
transfer learning
time series forecasting
convolutional neural networks
image classification tasks
speech recognition systems
generative adversarial networks
autoencoders
natural language processing tasks
fully connected networks
gptkbp:modifications the_ReLU_function
gptkbp:relatedTo Parametric ReLU
gptkbp:sensors the choice of alpha
gptkbp:variant ReLU