Tiny ImageNet

'Tiny ImageNet' is a dataset that contains 200 classes of images, each with 500 training images, used to evaluate performance in image classification tasks.

Papers using Tiny ImageNet (26)

Separate Aggregation of Split Network for Personalized Federated Learning2026EvoCSFL: Surrogate-Assisted Evolutionary Client Selection for Efficient and Robust Federated Learning2026Adaptive Selection of LoRA Components in Privacy-Preserving Federated Learning2026Enhancing Federated Quadruplet Learning: Stochastic Client Selection and Embedding Stability Analysis2026TSFLora: Token-Compressed Split Fine-Tuning for Wireless Edge Networks2026Probabilistic Federated Learning on Uncertain and Heterogeneous Data with Model Personalization2026Diffusion-Guided Semantic Consistency for Multimodal Heterogeneity2026Rethinking LoRA for Privacy-Preserving Federated Learning in Large Models2026DP-FedAdamW: An Efficient Optimizer for Differentially Private Federated Large Models2026Prompt Estimation from Prototypes for Federated Prompt Tuning of Vision Transformers2025DOPA: Stealthy and Generalizable Backdoor Attacks from a Single Client under Challenging Federated Constraints2025On the Fast Adaptation of Delayed Clients in Decentralized Federated Learning: A Centroid-Aligned Distillation Approach2025Decoupled Contrastive Learning for Federated Learning2025pFedDSH: Enabling Knowledge Transfer in Personalized Federated Learning through Data-free Sub-Hypernetwork2025FedSWA: Improving Generalization in Federated Learning with Highly Heterogeneous Data via Momentum-Based Stochastic Controlled Weight Averaging2025Orthogonal Soft Pruning for Efficient Class Unlearning2025SSFL: Discovering Sparse Unified Subnetworks at Initialization for Efficient Federated Learning2024Local-Global Knowledge Distillation in Heterogeneous Federated Learning with Non-IID Data2021 · 36 citesNo Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier2023 · 3 citesUnlocking the Potential of Federated Learning for Deeper Models2023 · 2 citesTowards Instance-adaptive Inference for Federated Learning2023 · 2 citesOvercoming Catastrophic Forgetting in Federated Class-Incremental Learning via Federated Global Twin Generator2024 · 1 citesDivide-and-Conquer the NAS puzzle in Resource Constrained Federated Learning Systems2023Text-Enhanced Data-free Approach for Federated Class-Incremental Learning2024Data-Free Federated Class Incremental Learning with Diffusion-Based Generative Memory2024PIP: Prototypes-Injected Prompt for Federated Class Incremental Learning2024