Heterogeneous Datasets

Heterogeneous datasets, encompassing diverse data types and distributions, pose significant challenges for machine learning, hindering model training and generalization. Current research focuses on developing robust algorithms and model architectures, such as federated learning frameworks (e.g., UniFed, FedCompass), biclustering techniques (e.g., HBIC), and ensemble methods, to effectively analyze these complex datasets. This work is crucial for advancing various fields, including personalized medicine, IoT cybersecurity, and crop yield prediction, where integrating disparate data sources is essential for improved accuracy and actionable insights.

Papers

October 29, 2024

Adaptive Aggregation Weights for Federated Segmentation of Pancreas MRI
Hongyi Pan, Gorkem Durak, Zheyuan Zhang, Yavuz Taktak, Elif Keles, Halil Ertugrul Aktas, Alpay Medetalibeyoglu, Yury Velichko, Concetto Spampinato, Ivo Schoots, Marco J. Bruno, Rajesh N. Keswani, Pallavi Tiwari, Candice Bolan, Tamas Gonda, Michael G. Goggins, Michael B. Wallace, Ziyue Xu, Ulas Bagci
Domain Shift Federated Prompt Cooperation Heterogeneous Datasets Pancreas Segmentation Optimal Aggregation Unified Federated Partially Labeled Segmentation

August 23, 2024

HBIC: A Biclustering Algorithm for Heterogeneous Datasets
Adán José-García, Julie Jacques, Clément Chauvet, Vincent Sobanski, Clarisse Dhaenens
Heterogeneous Datasets

July 29, 2024

UniFed: A Universal Federation of a Mixture of Highly Heterogeneous Medical Image Classification Tasks
Atefe Hassani, Islem Rekik
Mixture Component Heterogeneous Datasets Heterogeneous Medical Image

July 9, 2024

iASiS: Towards Heterogeneous Big Data Analysis for Personalized Medicine
Anastasia Krithara, Fotis Aisopos, Vassiliki Rentoumi, Anastasios Nentidis, Konstantinos Bougatiotis, Maria-Esther Vidal, Ernestina Menasalvas, Alejandro Rodriguez-Gonzalez, Eleftherios G. Samaras, Peter Garrard, Maria Torrente, Mariano Provencio Pulla, Nikos Dimakopoulos, Rui Mauricio, Jordi Rambla De Argila, Gian Gaetano Tartaglia, George Paliouras
Large Scale Medical Heterogeneous Datasets Personalized Medicine Heterogeneous Data Source

June 3, 2024

iKAN: Global Incremental Learning with KAN for Human Activity Recognition Across Heterogeneous Datasets
Mengxi Liu, Sizhen Bian, Bo Zhou, Paul Lukowicz
Incremental Learning Activity Recognition Kolmogorov Arnold Network Wearable Sensor Heterogeneous Datasets Global Deep

May 20, 2024

A graph-structured distance for heterogeneous datasets with meta variables
Edward Hallé-Hannan, Charles Audet, Youssef Diouane, Sébastien Le Digabel, Paul Saves
Nearest Neighbor Graph Based Approach Heterogeneous Datasets Meta Model Graph Distance Inverse Distance Weighting

December 10, 2023

Fake It Till Make It: Federated Learning with Consensus-Oriented Generation
Rui Ye, Yaxin Du, Zhenyang Ni, Siheng Chen, Yanfeng Wang
Data Heterogeneity Fake Speech Heterogeneous Datasets Reference Dataset Complementary Information

September 26, 2023

FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices using a Computing Power Aware Scheduler
Zilinghan Li, Pranshu Chaturvedi, Shilan He, Han Chen, Gagandeep Singh, Volodymyr Kindratenko, E. A. Huerta, Kibaek Kim, Ravi Madduri
Heterogeneous Client Heterogeneous Datasets Cross Silo Federated Learning Asynchronous Algorithm Energy Efficient Scheduling Synchronous Algorithm

August 17, 2023

Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data Spaces
Ahmad-Reza Ehyaei, Kiarash Mohammadi, Amir-Hossein Karimi, Samira Samadi, Golnoosh Farnadi
Native Robustness Adversarial Robustness Adversarial Perturbation Structural Causal Model Sensitive Attribute Individual Fairness Heterogeneous Datasets

August 14, 2023

CEmb-SAM: Segment Anything Model with Condition Embedding for Joint Learning from Heterogeneous Datasets
Dongik Shin, Beomsuk Kim, Seungjun Baek
Segment Anything Model Joint Learning Medical Image Segmentation Task Robust Segmentation Heterogeneous Datasets Ultrasound Image Segmentation

August 9, 2023

Efficient Bayesian Optimization with Deep Kernel Learning and Transformer Pre-trained on Multiple Heterogeneous Datasets
Wenlong Lyu, Shoubo Hu, Jie Chuai, Zhitang Chen
Transformer Based Gaussian Process Bayesian Optimization Surrogate Model Black Box Optimization Heterogeneous Datasets Black Box Optimization Problem Deep Kernel Learning

July 20, 2023

Ensemble Learning based Anomaly Detection for IoT Cybersecurity via Bayesian Hyperparameters Sensitivity Analysis
Tin Lai, Farnaz Farid, Abubakar Bello, Fariza Sabrina
Anomaly Detection Ensemble Learning Internet of Thing Heterogeneous Datasets

July 18, 2023

Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning
Zachary Charles, Nicole Mitchell, Krishna Pillutla, Michael Reneer, Zachary Garrett
Heterogeneous Datasets Aggregated Data Federated Training Federated Large Language Model Federated Foundation Model Group Learning

June 20, 2023

June 19, 2023

BioREx: Improving Biomedical Relation Extraction by Leveraging Heterogeneous Datasets
Po-Ting Lai, Chih-Hsuan Wei, Ling Luo, Qingyu Chen, Zhiyong Lu
Biomedical Natural Language Processing Heterogeneous Datasets Biomedical Relation Extraction

June 12, 2023

Generating Synthetic Datasets by Interpolating along Generalized Geodesics
Jiaojiao Fan, David Alvarez-Melis
Synthetic Data Generation Generalized Geodesic Heterogeneous Datasets Multi Dataset Dataset Synthesis

June 8, 2023

ScaleDet: A Scalable Multi-Dataset Object Detector
Yanbei Chen, Manchen Wang, Abhay Mittal, Zhenlin Xu, Paolo Favaro, Joseph Tighe, Davide Modolo
3D Object Detection Label Space Heterogeneous Datasets Multi Dataset

May 24, 2023

Personalized Dictionary Learning for Heterogeneous Datasets
Geyu Liang, Naichen Shi, Raed Al Kontar, Salar Fattahi
Sparse Representation Dictionary Learning Heterogeneous Datasets Weak Learner

May 2, 2023

HTPS: Heterogeneous Transferring Prediction System for Healthcare Datasets
Jia-Hao Syu, Jerry Chun-Wei Lin, Marcin Fojcik, Rafał Cupek
Task Transferability Heterogeneous Data Healthcare Datasets Heterogeneous Datasets Heterogeneous Transfer Learning

Heterogeneous Datasets

Papers

Adaptive Aggregation Weights for Federated Segmentation of Pancreas MRI

HBIC: A Biclustering Algorithm for Heterogeneous Datasets

UniFed: A Universal Federation of a Mixture of Highly Heterogeneous Medical Image Classification Tasks

iASiS: Towards Heterogeneous Big Data Analysis for Personalized Medicine

iKAN: Global Incremental Learning with KAN for Human Activity Recognition Across Heterogeneous Datasets

A graph-structured distance for heterogeneous datasets with meta variables

Fake It Till Make It: Federated Learning with Consensus-Oriented Generation

FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices using a Computing Power Aware Scheduler

Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data Spaces

CEmb-SAM: Segment Anything Model with Condition Embedding for Joint Learning from Heterogeneous Datasets

Efficient Bayesian Optimization with Deep Kernel Learning and Transformer Pre-trained on Multiple Heterogeneous Datasets

Ensemble Learning based Anomaly Detection for IoT Cybersecurity via Bayesian Hyperparameters Sensitivity Analysis

Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning

Winter Wheat Crop Yield Prediction on Multiple Heterogeneous Datasets using Machine Learning

A Deep Learning Model for Heterogeneous Dataset Analysis -- Application to Winter Wheat Crop Yield Prediction

BioREx: Improving Biomedical Relation Extraction by Leveraging Heterogeneous Datasets

Generating Synthetic Datasets by Interpolating along Generalized Geodesics

ScaleDet: A Scalable Multi-Dataset Object Detector

Personalized Dictionary Learning for Heterogeneous Datasets

HTPS: Heterogeneous Transferring Prediction System for Healthcare Datasets