$\TeX$ Notes

TikTok Recommendation System Paper

Monolith: Real Time Recommendation System With Collisionless Embedding Table

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Gradient-Based Learning Applied to Document Recognition

Gradient-Based Learning Applied to Document Recognition Paper

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Dropout: A Simple Way to Prevent Neural Networks from Overfitting

Dropout: A Simple Way to Prevent Neural Networks from Overfitting Paper

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Neural Image Caption Generation with Visual Attention

Neural Image Caption Generation with Visual Attention Paper

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YOLOv4: An Incremental Improvement

YOLOv4: An Incremental Improvement Paper

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YOLO9000: Better, Faster, Stronger

YOLO9000: Better, Faster, Stronger Paper

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You Only Look Once: Unified, Real-Time Object Detection

You Only Look Once: Unified, Real-Time Object Detection Paper

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Fully Convolutional Networks for Semantic Segmentation

Fully Convolutional Networks for Semantic Segmentation Paper

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Crowdsourcing in Computer Vision

Crowdsourcing in Computer Vision Paper

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Squeeze-and-Excitation Network

Squeeze-and-Excitation Network Paper

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Xception: Deep Learning with Depthwise Separable Convolutions

Xception: Deep Learning with Depthwise Separable Convolutions Paper

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Deep Residual Learning for Image Recognition

Deep Residual Learning for Image Recognition Paper

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Very Deep Convlutional Networks for Large-Scale Image Recognition

Very Deep Convlutional Networks for Large-Scale Image Recognition Paper

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Going Deeper with Convolutions

Going Deeper with Convolutions Paper

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ImageNet Classification with Deep Convolutional Neural Networks

ImageNet Classification with Deep Convolutional Neural Networks Paper

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neocognitron: A Self-Organizing Neural Network Model for a Mechanism of Pattern Recognition Unaffected by Shift in Position

neocognitron: A Self-Organizing Neural Network Model for a Mechanism of Pattern Recognition Unaffected by Shift in Position Paper

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Receptive Fields and Function Architecture of Monkey Striate Cortex

Receptive Fields and Function Architecture of Monkey Striate Cortex Paper

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Receptive Fields of Single Neurones in The Cat's Striate Cortex

Receptive Fields of Single Neurones in The Cat's Striate Cortex Paper

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Single Unit Activity in Striate Cortex of Unrestrained Cats

Single Unit Activity in Striate Cortex of Unrestrained Cats Paper

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Distributed Representations of Words and Phrases and their Compositionality

Distributed Representations of Words and Phrases and their Compositionality Paper

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Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Paper

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Improving Neural Networks by Preventing Co-Adaptation of Feature Detectors

Improving Neural Networks by Preventing Co-Adaptation of Feature Detectors Paper

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Adam: A Method for Stochastic Optimization

Adam: A Method for Stochastic Optimization Paper

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Adaptive Subgradient Methods for Online Learning and Stochastic Optimization

Adaptive Subgradient Methods for Online Learning and Stochastic Optimization Paper

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Some methods of speeding up the convergence of iteration methods

Some methods of speeding up the convergence of iteration methods Paper

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Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Paper

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Self-Normalizing Neural Networks

Self-Normalizing Neural Networks Paper

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Fast and Accurate Deep Learning by Exponential Linear Units (ELUs)

Fast and Accurate Deep Learning by Exponential Linear Units (ELUs) Paper

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Empirical Evaluation of Rectified Activations in Convolutional Network

Empirical Evaluation of Rectified Activations in Convolutional Network Paper

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Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Paper

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Understanding the Difficulty of Training Deep Feedforward Neural Networks

Understanding the Difficulty of Training Deep Feedforward Neural Networks Paper

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Practical recommendations for gradient-based training of deep architectures

Practical recommendations for gradient-based training of deep architectures Paper

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Using Evolutionary AutoML to Discover Neural Network Architectures

Using Evolutionary AutoML to Discover Neural Network Architectures Paper

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Population Based Training of Neural Networks

Population Based Training of Neural Networks Paper

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Wide & Deep Learning for Recommender Systems

Wide & Deep Learning for Recommender Systems Paper

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A Logical Calculus of Ideas Immanent in Nervous Activity

A Logical Calculus of Ideas Immanent in Nervous Activity Paper

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Web-scale k-means clustering

Web-scale k-means clustering Paper

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Using the Triangle Inequality to Accelerate k-Means

Using the Triangle Inequality to Accelerate k-Means Paper

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Least Square Quantization in PCM

Least Square Quantization in PCM Paper

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Fast Kernel Classifiers with Online and Active Learning

Fast Kernel Classifiers with Online and Active Learning Paper

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Incremental and Decremental SVM Learning

Incremental and Decremental SVM Learning Paper

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Sequential Minimal Optimization: A fast Algorithm for Training Support Vector Machines

Sequential Minimal Optimization: A fast Algorithm for Training Support Vector Machines Paper

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A Dual Coordinate Descent Method for Large-scale Linear SVM

A Dual Coordinate Descent Method for Large-scale Linear SVM Paper

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Nonlinear Dimensionality Reduction by Locally Linear Embedding

Nonlinear Dimensionality Reduction by Locally Linear Embedding Paper

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Kernel Principal Component Analysis

Kernel Principal Component Analysis Paper

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Stacked Generalization

Stacked Generalization Paper

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ARCING THE EDGE

ARCING THE EDGE Paper

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A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting

A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting Paper

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Extremely Randomized Trees

Extremely Randomized Trees Paper

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Random Decision Forests

Random Decision Forests Paper

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The Random Subspace Method for Constructing Decision Forests

The Random Subspace Method for Constructing Decision Forests Paper

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A Mathematical Theory of Communication

A Mathematical Theory of Communication Paper

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A Tutorial Introduction to the Minimum Description Length Principle

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Deep Speech 2: End-to-End Speech Recognition in English and Mandarin

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Neural Turing Machines

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Quantifying the Rise and Fall of Complexity in Closed Systems: The Coffee Automaton

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Variational Lossy Autoencoder

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A Simple NN Module for Relational Reasoning

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Identity Mappings in Deep Residual Networks

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Neural Machine Translation by Jointly Learning to Align and Translate

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Neural Message Passing for Quantum Chemistry

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Multi-Scale Context Aggregation by Dilated Convolutions

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GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism

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Keeping Neural Networks Simple by Minimizing the Description Length of the Weights

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