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https://doi.org/10.2139/ssrn.4676667

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inferredcites →https://doi.org/10.1007/978-3-030-58565-5_6openalex-extracted
PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning
inferredcites →https://doi.org/10.1016/0921-8890(95)00004-yopenalex-extracted
Lifelong robot learning
inferredcites →https://doi.org/10.1016/j.ins.2023.119499openalex-extracted
Personalized federated learning: A Clustered Distributed Co-Meta-Learning approach
inferredcites →https://doi.org/10.1016/j.ins.2023.119725openalex-extracted
FedSULP: A communication-efficient federated learning framework with selective updating and loss penalization
inferredcites →https://doi.org/10.1016/j.ins.2023.119731openalex-extracted
Task-specific parameter decoupling for class incremental learning
inferredcites →https://doi.org/10.1016/j.ins.2023.119784openalex-extracted
rFedFW: Secure and trustable aggregation scheme for Byzantine-robust federated learning in Internet of Things
inferredcites →https://doi.org/10.1016/j.neucom.2021.07.098openalex-extracted
Federated learning on non-IID data: A survey
inferredcites →https://doi.org/10.1016/s0020-0255(02)00170-6openalex-extracted
Incremental class learning approach and its application to handwritten digit recognition
inferredcites →https://doi.org/10.1038/s41467-018-04316-3openalex-extracted
Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science
inferredcites →https://doi.org/10.1073/pnas.1611835114openalex-extracted
Overcoming catastrophic forgetting in neural networks
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-extracted
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.587openalex-extracted
iCaRL: Incremental Classifier and Representation Learning
inferredcites →https://doi.org/10.1109/cvpr.2019.00046openalex-extracted
Large Scale Incremental Learning
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00408openalex-extracted
What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00902openalex-extracted
Continual Learning With Extended Kronecker-Factored Approximate Curvature
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01447openalex-extracted
Unsupervised Model Personalization While Preserving Privacy and Scalability: An Open Problem
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00025openalex-extracted
Training Networks in Null Space of Feature Covariance for Continual Learning
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00164openalex-extracted
On Learning the Geodesic Path for Incremental Learning
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00951openalex-extracted
Layerwise Optimization by Gradient Decomposition for Continual Learning
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00024openalex-extracted
Learning to Prompt for Continual Learning
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00884openalex-extracted
Forward Compatible Few-Shot Class-Incremental Learning
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00907openalex-extracted
DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00992openalex-extracted
Federated Class-Incremental Learning
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01560openalex-extracted
Class-Incremental Learning by Knowledge Distillation with Adaptive Feature Consolidation
inferredcites →https://doi.org/10.1109/cvprw.2009.5206848openalex-extracted
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvprw50498.2020.00118openalex-extracted
Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis
inferredcites →https://doi.org/10.1109/iccv48922.2021.00088openalex-extracted
SS-IL: Separated Softmax for Incremental Learning
inferredcites →https://doi.org/10.1109/iccv48922.2021.00814openalex-extracted
Continual Prototype Evolution: Learning Online from Non-Stationary Data Streams
inferredcites →https://doi.org/10.1109/icde53745.2022.00077openalex-extracted
Federated Learning on Non-IID Data Silos: An Experimental Study
inferredcites →https://doi.org/10.1109/jiot.2021.3079472openalex-extracted
Federated Learning With Unreliable Clients: Performance Analysis and Mechanism Design
inferredcites →https://doi.org/10.1109/jsac.2019.2904348openalex-extracted
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
inferredcites →https://doi.org/10.1109/tcomm.2019.2956472openalex-extracted
Distributed Federated Learning for Ultra-Reliable Low-Latency Vehicular Communications
inferredcites →https://doi.org/10.1109/tcsvt.2023.3262739openalex-extracted
Semantic Knowledge Guided Class-Incremental Learning
inferredcites →https://doi.org/10.1109/tifs.2022.3174394openalex-extracted
PFLF: Privacy-Preserving Federated Learning Framework for Edge Computing
inferredcites →https://doi.org/10.1109/tpami.2023.3334213openalex-extracted
No One Left Behind: Real-World Federated Class-Incremental Learning
inferredcites →https://doi.org/10.1109/tpami.2024.3429383openalex-extracted
Class-Incremental Learning: A Survey
inferredcites →https://doi.org/10.1145/3503161.3548764openalex-extracted
Few-Shot Model Agnostic Federated Learning
inferredcites →https://doi.org/10.1561/0400000042openalex-extracted
The Algorithmic Foundations of Differential Privacy
inferredcites →https://doi.org/10.1561/2200000083openalex-extracted
Advances and Open Problems in Federated Learning
inferredcites →https://doi.org/10.1609/aaai.v35i2.16213openalex-extracted
Few-Shot Class-Incremental Learning via Relation Knowledge Distillation
inferredcites →https://doi.org/10.1609/aaai.v35i9.16960openalex-extracted
Personalized Cross-Silo Federated Learning on Non-IID Data
inferredcites →https://doi.org/10.1609/aaai.v37i9.26330openalex-extracted
FedALA: Adaptive Local Aggregation for Personalized Federated Learning
inferredcites →https://doi.org/10.24963/ijcai.2022/303openalex-extracted
Continual Federated Learning Based on Knowledge Distillation
inferredcites →https://doi.org/10.48550/arxiv.1411.1792openalex-extracted
How transferable are features in deep neural networks?
inferredcites →https://doi.org/10.48550/arxiv.1503.02531openalex-extracted
Distilling the Knowledge in a Neural Network
inferredcites →https://doi.org/10.48550/arxiv.1602.05629openalex-extracted
Communication-Efficient Learning of Deep Networks from Decentralized Data
inferredcites →https://doi.org/10.48550/arxiv.1711.05136openalex-extracted
Deep Rewiring: Training very sparse deep networks
inferredcites →https://doi.org/10.48550/arxiv.1803.03635openalex-extracted
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1804.05271openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.1806.00582openalex-extracted
Federated Learning with Non-IID Data
inferredcites →https://doi.org/10.48550/arxiv.1902.01996openalex-extracted
Are All Layers Created Equal?
inferredcites →https://doi.org/10.48550/arxiv.1902.05967openalex-extracted
Parameter Efficient Training of Deep Convolutional Neural Networks by Dynamic Sparse Reparameterization
inferredcites →https://doi.org/10.48550/arxiv.1905.12784openalex-extracted
Intrinsic dimension of data representations in deep neural networks
inferredcites →https://doi.org/10.48550/arxiv.1906.04329openalex-extracted
Federated Learning for Emoji Prediction in a Mobile Keyboard
inferredcites →https://doi.org/10.48550/arxiv.1907.04840openalex-extracted
Sparse Networks from Scratch: Faster Training without Losing Performance
inferredcites →https://doi.org/10.48550/arxiv.1909.01520openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.1911.11134openalex-extracted
Rigging the Lottery: Making All Tickets Winners
inferredcites →https://doi.org/10.48550/arxiv.2002.10619openalex-extracted
Three Approaches for Personalization with Applications to Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.2003.03196openalex-extracted
Federated Continual Learning with Weighted Inter-client Transfer
inferredcites →https://doi.org/10.48550/arxiv.2003.13461openalex-extracted
Adaptive Personalized Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.2004.07507openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2004.11500openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2006.10455openalex-extracted
What Do Neural Networks Learn When Trained With Random Labels?
inferredcites →https://doi.org/10.48550/arxiv.2012.04221openalex-extracted
Ditto: Fair and Robust Federated Learning Through Personalization
inferredcites →https://doi.org/10.48550/arxiv.2102.02079openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2102.02887openalex-extracted
Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training
inferredcites →https://doi.org/10.48550/arxiv.2102.07078openalex-extracted
Exploiting Shared Representations for Personalized Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.2103.01737openalex-extracted
Distilling Causal Effect of Data in Class-Incremental Learning
inferredcites →https://doi.org/10.48550/arxiv.2103.07113openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2103.16788openalex-extracted
DER: Dynamically Expandable Representation for Class Incremental Learning
inferredcites →https://doi.org/10.48550/arxiv.2105.07561openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2203.06953openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2204.00895openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2205.13218openalex-extracted
A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning
inferredcites →https://doi.org/10.48550/arxiv.2206.00187openalex-extracted
DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training
inferredcites →https://doi.org/10.48550/arxiv.2302.13001openalex-extracted
Better Generative Replay for Continual Federated Learning
inferredcites →https://doi.org/10.57702/zp44cu3gopenalex-extracted
Learning Multiple Layers of Features from Tiny Images
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