Collaborative Learning

Collaborative learning focuses on improving machine learning model performance by leveraging data and computational resources from multiple sources, enhancing efficiency and privacy. Current research emphasizes developing algorithms that optimize communication and resource allocation among collaborating agents, including bilevel optimization and spectral estimators, while addressing challenges like negative transfer and data heterogeneity across diverse datasets. This approach is significant for improving model accuracy and generalization in various applications, from medical image segmentation to personalized recommendations, and is increasingly relevant in the context of data privacy regulations and resource-constrained environments.

Papers

March 21, 2023

HRDFuse: Monocular 360{\deg}Depth Estimation by Collaboratively Learning Holistic-with-Regional Depth Distributions
Hao Ai, Zidong cao, Yan-pei Cao, Ying Shan, Lin Wang
Convolutional Neural Network Depth Estimation Monocular Depth Estimation Depth Map Collaborative Learning Depth Prediction Depth Distribution

March 13, 2023

Model Extraction Attacks on Split Federated Learning
Jingtao Li, Adnan Siraj Rakin, Xing Chen, Li Yang, Zhezhi He, Deliang Fan, Chaitali Chakrabarti
Collaborative Learning Model Extraction Attack Split Federated Learning Intellectual Property Protection

March 3, 2023

Collaborative Learning with a Drone Orchestrator
Mahdi Boloursaz Mashhadi, Mahnoosh Mahdavimoghadam, Rahim Tafazolli, Walid Saad
Single Drone Collaborative Learning Rogue Drone Wireless Intelligence

February 11, 2023

Cross-center Early Sepsis Recognition by Medical Knowledge Guided Collaborative Learning for Data-scarce Hospitals
Ruiqing Ding, Fangjie Rong, Xiao Han, Leye Wang
Collaborative Learning Data Scarce Understanding Cross Sepsis Diagnosis

January 26, 2023

Communication-Efficient Collaborative Regret Minimization in Multi-Armed Bandits
Nikolai Karpov, Qin Zhang
Multi Armed Bandit Regret Minimization Collaborative Learning Multi Agent Multi Armed Bandit

January 20, 2023

Split Ways: Privacy-Preserving Training of Encrypted Data Using Split Learning
Tanveer Khan, Khoa Nguyen, Antonis Michalas
Training Data Homomorphic Encryption Split Learning PRIvacy Leakage Collaborative Learning Split and Fit Training Data Privacy

December 13, 2022

Privacy-Preserving Collaborative Learning through Feature Extraction
Alireza Sarmadi, Hao Fu, Prashanth Krishnamurthy, Siddharth Garg, Farshad Khorrami
Membership Inference Attack Feature Extraction PRIvacy Leakage Collaborative Learning Feature Extractor Entity Extraction

November 30, 2022

Conservative-Progressive Collaborative Learning for Semi-supervised Semantic Segmentation
Siqi Fan, Fenghua Zhu, Zunlei Feng, Yisheng Lv, Mingli Song, Fei-Yue Wang
Semantic Segmentation Semi Supervised Learning Collaborative Learning Semi Supervised Semantic Segmentation Pseudo Supervision

November 20, 2022

Scalable Collaborative Learning via Representation Sharing
Frédéric Berdoz, Abhishek Singh, Martin Jaggi, Ramesh Raskar
Knowledge Distillation Split Learning Collaborative Learning Joint Representation Privacy Preserving Machine Learning Online Knowledge Distillation

October 11, 2022

Exploring Interactions and Regulations in Collaborative Learning: An Interdisciplinary Multimodal Dataset
Yante Li, Yang Liu, KhÁnh Nguyen, Henglin Shi, Eija Vuorenmaa, Sanna Jarvela, Guoying Zhao
Multimodal Dataset Collaborative Learning Interaction Strategy Affective Computing Social Medium Regulation

October 4, 2022

Split Federated Learning on Micro-controllers: A Keyword Spotting Showcase
Jingtao Li, Runcong Kuang
Keyword Spotting Collaborative Learning Private Learning 32 Bit Microcontrollers Split Federated Learning Mandarin Speech Splitfed Learning

September 22, 2022

Robust Collaborative Learning with Linear Gradient Overhead
Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Lê Nguyên Hoang, Rafael Pinot, John Stephan
Native Robustness Stochastic Gradient Descent Collaborative Learning Gradient Computation Collaborative Adversarial Fast Gradient

August 8, 2022

SelfCoLearn: Self-supervised collaborative learning for accelerating dynamic MR imaging
Juan Zou, Cheng Li, Sen Jia, Ruoyou Wu, Tingrui Pei, Hairong Zheng, Shanshan Wang
Self Supervised Collaborative Learning Fast Magnetic Resonance Imaging Dynamic Magnetic Resonance Ex Vivo Dynamic Magnetic Resonance Imaging

July 20, 2022

Continual Variational Autoencoder Learning via Online Cooperative Memorization
Fei Ye, Adrian G. Bors
Continual LEArning Variational Autoencoders Collaborative Learning Long Term Memory Variational Continual Learning

July 16, 2022

June 1, 2022

Collaborative Learning of Discrete Distributions under Heterogeneity and Communication Constraints
Xinmeng Huang, Donghwan Lee, Edgar Dobriban, Hamed Hassani
Collaborative Learning Communication Efficient Unobserved Heterogeneity Discrete Distribution Communication Constraint Heterogeneous User

May 31, 2022

Near-Optimal Collaborative Learning in Bandits
Clémence Réda, Sattar Vakili, Emilie Kaufmann
Regret Minimization Collaborative Learning Optimal Arm Multi Agent Multi Armed Bandit Near Optimal Algorithm Collaborative Bandit

May 22, 2022

Incentivizing Federated Learning
Shuyu Kong, You Li, Hai Zhou
Federated Learning Model Performance Collaborative Learning Incentive Mechanism

May 20, 2022

Constructive Interpretability with CoLabel: Corroborative Integration, Complementary Features, and Collaborative Learning
Abhijit Suprem, Sanjyot Vaidya, Suma Cherkadi, Purva Singh, Joao Eduardo Ferreira, Calton Pu
Inherent Interpretability Unified Framework Interpretable Model Collaborative Learning Interpretable Feature Interpretability Analysis Data Re Annotation