Dropout

الإسقاط العشوائي للعصبونات

تقنية كبح للإفراط تعطل عشوائياً نسبة من العصبونات في كل خطوة تدريب لإجبار الشبكة على عدم الاعتماد على مسارات محددة.

Dropout

Also translated asالتعطيل المؤقت لمسارات المعالجة، آلية كبح الإفراط بالتحييد الدوري، الإسقاط الترشيحي

First appears in this corpus in: The Monte Carlo Method (1949)

Appears in these papers

ImageNet Classification with Deep Convolutional Neural Networks2012 in the sky ✦
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift2015 in the sky ✦
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer2019 in the sky ✦
Neural Networks and the Bias/Variance Dilemma1992 in the sky ✦
Reducing the Dimensionality of Data with Neural Networks2006 in the sky ✦
Deep Learning2015 in the sky ✦
Deep Learning2015 in the sky ✦
Training Data-Efficient Image Transformers & Distillation Through Attention2021 in the sky ✦
Deep Interest Network for Click-Through Rate Prediction2018 in the sky ✦
Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World2017 in the sky ✦
Dropout: A Simple Way to Prevent Neural Networks from Overfitting2014 in the sky ✦
Dropout: A Simple Way to Prevent Neural Networks from Overfitting2014 in the sky ✦
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks2019 in the sky ✦
Fast R-CNN2015 in the sky ✦
Explaining and Harnessing Adversarial Examples2015 in the sky ✦
Fusion-in-Decoder: Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering2021 in the sky ✦
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness2022 in the sky ✦
Generative Adversarial Networks2014 in the sky ✦
Graph Attention Networks2018 in the sky ✦
Gaussian Error Linear Units (GELUs)2016 in the sky ✦
Gaussian Error Linear Units (GELUs)2016 in the sky ✦
Going Deeper with Convolutions2014 in the sky ✦
Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets2022 in the sky ✦
LIMA: Less Is More for Alignment2023 in the sky ✦
LIMA: Less Is More for Alignment2023 in the sky ✦
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks2019 in the sky ✦
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism2019 in the sky ✦
mixup: Beyond Empirical Risk Minimization2018 in the sky ✦
mixup: Beyond Empirical Risk Minimization2018 in the sky ✦
The Monte Carlo Method1949 in the sky ✦
Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer2022 in the sky ✦
N-BEATS: Neural Basis Expansion Analysis for Interpretable Time Series Forecasting2019 in the sky ✦
No Free Lunch Theorems for Optimization1997 in the sky ✦
OPT: Open Pre-Trained Transformer Language Models2022 in the sky ✦
A Time Series Is Worth 64 Words: Long-Term Forecasting with Transformers2023 in the sky ✦
A Time Series Is Worth 64 Words: Long-Term Forecasting with Transformers2023 in the sky ✦
Image-to-Image Translation with Conditional Adversarial Networks2017 in the sky ✦
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation2017 in the sky ✦
Proximal Policy Optimization Algorithms2017 in the sky ✦
Ridge Regression: Biased Estimation for Nonorthogonal Problems1970 in the sky ✦
RoBERTa: A Robustly Optimized BERT Pretraining Approach2019 in the sky ✦
Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity2022 in the sky ✦
Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity2022 in the sky ✦
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions2018 in the sky ✦
Universal Language Model Fine-Tuning for Text Classification2018 in the sky ✦
VQA: Visual Question Answering2015 in the sky ✦