Summary of Ccva-fl: Cross-client Variations Adaptive Federated Learning For Medical Imaging, by Sunny Gupta and Amit Sethi
CCVA-FL: Cross-Client Variations Adaptive Federated Learning for Medical Imagingby Sunny Gupta, Amit SethiFirst submitted to…
Summary of Dynamic Dimension Wrapping (ddw) Algorithm: a Novel Approach For Efficient Cross-dimensional Search in Dynamic Multidimensional Spaces, by Dongnan Jin et al.
Dynamic Dimension Wrapping (DDW) Algorithm: A Novel Approach for Efficient Cross-Dimensional Search in Dynamic Multidimensional…
Summary of Dataset Dictionary Learning in a Wasserstein Space For Federated Domain Adaptation, by Eduardo Fernandes Montesuma et al.
Dataset Dictionary Learning in a Wasserstein Space for Federated Domain Adaptationby Eduardo Fernandes Montesuma, Fabiola…
Summary of Neural Compression Of Atmospheric States, by Piotr Mirowski et al.
Neural Compression of Atmospheric Statesby Piotr Mirowski, David Warde-Farley, Mihaela Rosca, Matthew Koichi Grimes, Yana…
Summary of R-sfllm: Jamming Resilient Framework For Split Federated Learning with Large Language Models, by Aladin Djuhera et al.
R-SFLLM: Jamming Resilient Framework for Split Federated Learning with Large Language Modelsby Aladin Djuhera, Vlad…
Summary of Skada-bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation on Diverse Modalities, by Yanis Lalou et al.
SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalitiesby Yanis Lalou, Théo…
Summary of Theoretical Insights Into Cyclegan: Analyzing Approximation and Estimation Errors in Unpaired Data Generation, by Luwei Sun et al.
Theoretical Insights into CycleGAN: Analyzing Approximation and Estimation Errors in Unpaired Data Generationby Luwei Sun,…
Summary of Global Atmospheric Data Assimilation with Multi-modal Masked Autoencoders, by Thomas J. Vandal et al.
Global atmospheric data assimilation with multi-modal masked autoencodersby Thomas J. Vandal, Kate Duffy, Daniel McDuff,…
Summary of Exploring Quantization For Efficient Pre-training Of Transformer Language Models, by Kamran Chitsaz et al.
Exploring Quantization for Efficient Pre-Training of Transformer Language Modelsby Kamran Chitsaz, Quentin Fournier, Gonçalo Mordido,…
Summary of Nitro-d: Native Integer-only Training Of Deep Convolutional Neural Networks, by Alberto Pirillo et al.
NITRO-D: Native Integer-only Training of Deep Convolutional Neural Networksby Alberto Pirillo, Luca Colombo, Manuel RoveriFirst…