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relu activation

93 papers

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Also known as

RELU

Co-occurring keywords

neural network (6616) gradient descent (1144) learning theory (519) relu network (143) neural network optimization (1293) deep neural network (1803) rectified linear unit (24) neural network training (309) single neuron (11) generalization bound (652)

Papers

Branch and Bound for Piecewise Linear Neural Network Verification JMLR 2020
Efficient Verification of ReLU-Based Neural Networks via Dependency Analysis AAAI 2020
Neural Networks are Convex Regularizers: Exact Polynomial-time Convex Optimization Formulations for Two-layer Networks ICML 2020
Linear predictor on linearly-generated data with missing values: non consistency and solutions AISTATS 2020
Network size and size of the weights in memorization with two-layers neural networks NIPS 2020
Learning Over-Parametrized Two-Layer Neural Networks beyond NTK COLT 2020
CryptoNAS: Private Inference on a ReLU Budget NIPS 2020
Neural Path Features and Neural Path Kernel : Understanding the role of gates in deep learning NIPS 2020
On the Tightness of Semidefinite Relaxations for Certifying Robustness to Adversarial Examples NIPS 2020
Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent ICML 2020
Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality NIPS 2020
Transformation of ReLU-based recurrent neural networks from discrete-time to continuous-time ICML 2020
Agnostic Learning of a Single Neuron with Gradient Descent NIPS 2020
On the Number of Linear Regions of Convolutional Neural Networks ICML 2020
Deep Neural Networks Learn Non-Smooth Functions Effectively AISTATS 2019
Learning One-hidden-layer ReLU Networks via Gradient Descent AISTATS 2019
Approximate Feature Collisions in Neural Nets NIPS 2019
How do infinite width bounded norm networks look in function space? COLT 2019
Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals NIPS 2019
Learning Two Layer Rectified Neural Networks in Polynomial Time COLT 2019
How degenerate is the parametrization of neural networks with the ReLU activation function? NIPS 2019
On the Convergence Rate of Training Recurrent Neural Networks NIPS 2019
Computing Linear Restrictions of Neural Networks NIPS 2019
Random deep neural networks are biased towards simple functions NIPS 2019
SHE: A Fast and Accurate Deep Neural Network for Encrypted Data NIPS 2019