conftrace_

neural network optimization

1293 papers

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Co-occurring keywords

model compression (3302) neural network (6616) convolutional neural network (4226) gradient descent (1144) stochastic gradient descent (1091) efficient computing (781) deep neural network (1803) large language model (13587) knowledge distillation (3725) representation learning (6206)

Papers

A PDE-based Explanation of Extreme Numerical Sensitivities and Edge of Stability in Training Neural Networks JMLR 2024
Algorithmic progress in language models NIPS 2024
PikeLPN: Mitigating Overlooked Inefficiencies of Low-Precision Neural Networks CVPR 2024
Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability AISTATS 2024
AutoAugment Is What You Need: Enhancing Rule-based Augmentation Methods in Low-resource Regimes EACL 2024
Bridging the Empirical-Theoretical Gap in Neural Network Formal Language Learning Using Minimum Description Length ACL 2024
Parameter Symmetry and Noise Equilibrium of Stochastic Gradient Descent NIPS 2024
Streamlining Speech Enhancement DNNs: an Automated Pruning Method Based on Dependency Graph with Advanced Regularized Loss Strategies INTERSPEECH 2024
Scalable Optimization in the Modular Norm NIPS 2024
The effect of Leaky ReLUs on the training and generalization of overparameterized networks AISTATS 2024
MCNet: Rethinking the Core Ingredients for Accurate and Efficient Homography Estimation CVPR 2024
On the Limitations of Fractal Dimension as a Measure of Generalization NIPS 2024
Light-PEFT: Lightening Parameter-Efficient Fine-Tuning via Early Pruning ACL 2024
Unveiling The Matthew Effect Across Channels: Assessing Layer Width Sufficiency via Weight Norm Variance NIPS 2024
BOLD: Boolean Logic Deep Learning NIPS 2024
Rethinking 3D Convolution in $\ell_p$-norm Space NIPS 2024
UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems NIPS 2024
Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization NIPS 2024
A Layer-Wise Natural Gradient Optimizer for Training Deep Neural Networks NIPS 2024
Unraveling the Gradient Descent Dynamics of Transformers NIPS 2024
SDGMNet: Statistic-Based Dynamic Gradient Modulation for Local Descriptor Learning AAAI 2024
Data Driven Threshold and Potential Initialization for Spiking Neural Networks AISTATS 2024
Investigation into Training Dynamics of Learned Optimizers (Student Abstract) AAAI 2024
What do Graph Neural Networks learn? Insights from Tropical Geometry NIPS 2024
MicroAdam: Accurate Adaptive Optimization with Low Space Overhead and Provable Convergence NIPS 2024