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Exploring lottery ticket hypothesis in media recommender systems

https://doi.org/10.1002/int.22827
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/int.22302openalex-snapshot
One‐dimensional convolutional neural networks for high‐resolution range profile recognition via adaptively feature recalibrating and automatically channel pruning
inferredcites →https://doi.org/10.1002/int.22320openalex-snapshot
Trust‐aware generative adversarial network with recurrent neural network for recommender systems
inferredcites →https://doi.org/10.1002/int.22412openalex-snapshot
An attention‐based category‐aware GRU model for the next POI recommendation
inferredcites →https://doi.org/10.1007/s10462-018-9654-yopenalex-snapshot
A review on deep learning for recommender systems: challenges and remedies
inferredcites →https://doi.org/10.1016/j.knosys.2020.106622openalex-snapshot
AutoML: A survey of the state-of-the-art
inferredcites →https://doi.org/10.1038/s41592-019-0686-2openalex-snapshot
SciPy 1.0: fundamental algorithms for scientific computing in Python
inferredcites →https://doi.org/10.1109/isca45697.2020.00084openalex-snapshot
DeepRecSys: A System for Optimizing End-To-End At-Scale Neural Recommendation Inference
inferredcites →https://doi.org/10.1109/msp.2017.2765695openalex-snapshot
Model Compression and Acceleration for Deep Neural Networks: The Principles, Progress, and Challenges
inferredcites →https://doi.org/10.1145/2959100.2959190openalex-snapshot
Deep Neural Networks for YouTube Recommendations
inferredcites →https://doi.org/10.1145/3038912.3052569openalex-snapshot
Neural Collaborative Filtering
inferredcites →https://doi.org/10.1145/3158369openalex-snapshot
Facial Expression Analysis under Partial Occlusion
inferredcites →https://doi.org/10.1145/3331184.3331267openalex-snapshot
Neural Graph Collaborative Filtering
inferredcites →https://doi.org/10.1145/3383313.3412227openalex-snapshot
Model Size Reduction Using Frequency Based Double Hashing for Recommender Systems
inferredcites →https://doi.org/10.1145/3394486.3403288openalex-snapshot
Neural Input Search for Large Scale Recommendation Models
inferredcites →https://doi.org/10.1145/3397271.3401063openalex-snapshot
LightGCN
inferredcites →https://doi.org/10.1145/3397271.3401125openalex-snapshot
A Generic Network Compression Framework for Sequential Recommender Systems
inferredcites →https://doi.org/10.1145/3397271.3401436openalex-snapshot
Automated Embedding Size Search in Deep Recommender Systems
inferredcites →https://doi.org/10.1145/3409963.3410498openalex-snapshot
Saec
inferredcites →https://doi.org/10.17863/cam.64134openalex-snapshot
SciPy 1.0: fundamental algorithms for scientific computing in Python
inferredcites →https://doi.org/10.18653/v1/2020.acl-main.360openalex-snapshot
Successfully Applying the Stabilized Lottery Ticket Hypothesis to the Transformer Architecture
inferredcites →https://doi.org/10.18653/v1/2020.findings-emnlp.372openalex-snapshot
TinyBERT: Distilling BERT for Natural Language Understanding
inferredcites →https://doi.org/10.48550/arxiv.1205.2618openalex-snapshot
BPR: Bayesian Personalized Ranking from Implicit Feedback
inferredcites →https://doi.org/10.48550/arxiv.1502.02551openalex-snapshot
Deep Learning with Limited Numerical Precision
inferredcites →https://doi.org/10.48550/arxiv.1803.03635openalex-snapshot
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1903.00103openalex-snapshot
Saec: Similarity-Aware Embedding Compression in Recommendation Systems
inferredcites →https://doi.org/10.48550/arxiv.1906.02768openalex-snapshot
Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP
inferredcites →https://doi.org/10.48550/arxiv.1906.02773openalex-snapshot
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers
inferredcites →https://doi.org/10.48550/arxiv.2002.02126openalex-snapshot
LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
inferredcites →https://doi.org/10.48550/arxiv.2003.02389openalex-snapshot
Comparing Rewinding and Fine-tuning in Neural Network Pruning
inferredcites →https://doi.org/10.48550/arxiv.2101.07577openalex-snapshot
Learnable Embedding Sizes for Recommender Systems

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1016/j.jksuci.2024.102142openalex-snapshot
Face forgery video detection based on expression key sequences
inferred← citeshttps://doi.org/10.1016/j.sasc.2025.200294openalex-snapshot
Online English teaching resource recommendation method design based on LightGCN CSCM
inferred← citeshttps://doi.org/10.1109/tnnls.2022.3217403openalex-snapshot
Power Law in Deep Neural Networks: Sparse Network Generation and Continual Learning With Preferential Attachment
inferred← citeshttps://doi.org/10.1109/tpami.2026.3664091openalex-snapshot
Out-of-Distribution-Resistant Evaluations for Explanations of Graph Neural Networks
inferred← citeshttps://doi.org/10.1145/3589334.3645549openalex-snapshot
Invariant Graph Learning for Causal Effect Estimation
inferred← citeshttps://doi.org/10.1145/3589334.3645576openalex-snapshot
Unleashing the Power of Knowledge Graph for Recommendation via Invariant Learning
inferred← citeshttps://doi.org/10.1145/3616855.3635780openalex-snapshot
Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation
inferred← citeshttps://doi.org/10.1145/3690624.3709203openalex-snapshot
A Unified Invariant Learning Framework for Graph Classification
inferred← citeshttps://doi.org/10.1145/3706062openalex-snapshot
A Simple Data Augmentation for Graph Classification: A Perspective of Equivariance and Invariance
inferred← citeshttps://doi.org/10.1177/18758967251376788openalex-snapshot
Joint Gradual Pruning and Knowledge Distillation for Identifying Graph Lottery Tickets
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