← Keywords

neural network training

309 papers

Explore in graph

Also known as

DNN NNT

Co-occurring keywords

neural network (6616) neural network optimization (1293) stochastic gradient descent (1088) gradient descent (1143) model compression (3283) deep neural network (1801) stochastic optimization (1060) deep learning (2111) batch normalization (222) non-convex optimization (546)

Papers

Maximal Initial Learning Rates in Deep ReLU Networks ICML 2023
The Transient Nature of Emergent In-Context Learning in Transformers NIPS 2023
Supervised Homography Learning with Realistic Dataset Generation ICCV 2023
Better Loss Landscape Visualization for Deep Neural Networks with Trajectory Information ACML 2023
A Computationally Efficient Sparsified Online Newton Method NIPS 2023
BEDLAM: A Synthetic Dataset of Bodies Exhibiting Detailed Lifelike Animated Motion CVPR 2023
Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry NIPS 2023
KOALA: A Kalman Optimization Algorithm with Loss Adaptivity AAAI 2022
Principal Components Bias in Over-parameterized Linear Models, and its Manifestation in Deep Neural Networks JMLR 2022
AI Snap! Blocks for Speech Input and Output, Computer Vision, Word Embeddings, and Neural Net Creation, Training, and Use AAAI 2022
Scaled ReLU Matters for Training Vision Transformers AAAI 2022
Proof of Learning: Towards a Practical Blockchain Consensus Mechanism Using Directed Guiding Gradients (Student Abstract) AAAI 2022
DISTREAL: Distributed Resource-Aware Learning in Heterogeneous Systems AAAI 2022
Chaotic Dynamics are Intrinsic to Neural Network Training with SGD NIPS 2022
MultiplexNet: Towards Fully Satisfied Logical Constraints in Neural Networks AAAI 2022
Learning by Competition of Self-Interested Reinforcement Learning Agents AAAI 2022
A proof of convergence for the gradient descent optimization method with random initializations in the training of neural networks with ReLU activation for piecewise linear target functions JMLR 2022
Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training JMLR 2022
Characterizing Datapoints via Second-Split Forgetting NIPS 2022
Random Sharpness-Aware Minimization NIPS 2022
Secure Quantized Training for Deep Learning ICML 2022
Batch Normalization Preconditioning for Neural Network Training JMLR 2022
SynthMap: a generative model for synthesis of 3D datasets for quantitative MRI parameter mapping of myelin water fraction MIDL 2022
Masked Training of Neural Networks with Partial Gradients AISTATS 2022
Towards Understanding the Condensation of Neural Networks at Initial Training NIPS 2022