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Found 6 papers, 2 papers with code
Nonparametric End-to-End Probabilistic Forecasting of Distributed Generation Outputs Considering Missing Data Imputation
In this paper, we introduce a nonparametric end-to-end method for probabilistic forecasting of distributed renewable generation outputs while including missing data imputation.
Universal Debiased Editing on Foundation Models for Fair Medical Image Classification
UDE is capable of mitigating bias both within the FM API embedding and the images themselves.
FedSoup: Improving Generalization and Personalization in Federated Learning via Selective Model Interpolation
In this paper, we propose a novel federated model soup method (i. e., selective interpolation of model parameters) to optimize the trade-off between local and global performance.
Forgettable Federated Linear Learning with Certified Data Removal
To this end, we propose the Forgettable Federated Linear Learning (2F2L) framework featured with novel training and data removal strategies.
VITA: A Multi-Source Vicinal Transfer Augmentation Method for Out-of-Distribution Generalization
The tangent transfer creates initial augmented samples for improving corruption robustness.
Benchmarks for Corruption Invariant Person Re-identification
When deploying person re-identification (ReID) model in safety-critical applications, it is pivotal to understanding the robustness of the model against a diverse array of image corruptions.
Ranked #1 on
Cross-Modal Person Re-Identification
on RegDB-C
(mINP (Visible to Thermal) metric)
Cross-Modal Person Re-Identification
Generalizable Person Re-identification
