Improving the Learning Speed of 2-Layer Neural Networks by Choosing Initial Values of the Adaptive W

Improving the Learning Speed of 2-Layer Neural Networks by Choosing Initial Values of the Adaptive W

NeuralNetworksinterval-basedmlpnovelseminaltheoreticalinitalization
Generative Modeling by Estimating Gradients of the Data Distribution

Generative Modeling by Estimating Gradients of the Data Distribution

AutoEncoderseminal2019denoisingNIPSwowscorematchingLangevindynamicstheoretical
Double Descent in Adversarial Training: An Implicit Label Noise Perspective

Double Descent in Adversarial Training: An Implicit Label Noise Perspective

RobustLearning2022adversarialICLROptimizationseminaltheoreticalwowoverfitting
AutoRec: Autoencoders Meet Collaborative Filtering

AutoRec: Autoencoders Meet Collaborative Filtering

AutoEncoderRecommenderSystems2015emmmheuristicseminalWWWCF
Deep Crossing: Web-Scale Modeling without Manually Crafted Combinatorial Features

Deep Crossing: Web-Scale Modeling without Manually Crafted Combinatorial Features

RecommenderSystems2016empiricalnovelseminalSIGKDDCTR
How Powerful is Graph Convolution for Recommendation?

How Powerful is Graph Convolution for Recommendation?

RepresentationLearniRecommenderSystems2021graphseminalwowtheoreticalCIKM
Fairness among New Items in Cold Start Recommender Systems

Fairness among New Items in Cold Start Recommender Systems

RobustLearningRecommenderSystems2021fairnessheuristicnovelseminalSIGIRcoldstart
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction

DeepFM: A Factorization-Machine based Neural Network for CTR Prediction

RecommenderSystems2017CTRFMheuristicIJCAInovelseminal
Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networ

Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networ

RecommenderSystems2017attentionFMheuristicIJCAInovelseminal

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