Joint Optimization

Joint optimization in machine learning and related fields focuses on simultaneously optimizing multiple, often competing, objectives within a single system. Current research emphasizes the use of deep reinforcement learning, multi-agent systems, and various optimization algorithms (e.g., gradient-based methods, dynamic programming) to address this challenge across diverse applications, including resource allocation in communication networks, robotics control, and model training efficiency. These advancements are significant because they enable the development of more efficient, robust, and effective systems by considering the interconnectedness of different components and optimizing their performance holistically.

Papers

December 7, 2023

November 28, 2023

Optimization Theory Based Deep Reinforcement Learning for Resource Allocation in Ultra-Reliable Wireless Networked Control Systems
Hamida Qumber Ali, Amirhassan Babazadeh Darabi, Sinem Coleri
Deep Reinforcement Learning Resource Allocation Joint Optimization Wireless Networked Control System

November 22, 2023

A Joint Gradient and Loss Based Clustered Federated Learning Design
Licheng Lin, Mingzhe Chen, Zhaohui Yang, Yusen Wu, Yuchen Liu
Interest Loss Joint Optimization Local Model Clustered Federated Learning FL Algorithm Efficient Clustering

November 3, 2023

Client Orchestration and Cost-Efficient Joint Optimization for NOMA-Enabled Hierarchical Federated Learning
Bibo Wu, Fang Fang, Xianbin Wang, Donghong Cai, Shu Fu, Zhiguo Ding
Joint Optimization Hierarchical Federated Learning Non Orthogonal Multiple Access Convergence Orchestration Edge Server Scheduling

October 16, 2023

Joint Optimization of Traffic Signal Control and Vehicle Routing in Signalized Road Networks using Multi-Agent Deep Reinforcement Learning
Xianyue Peng, Hang Gao, Gengyue Han, Hao Wang, Michael Zhang
Multi Agent Multi Agent Deep Reinforcement Learning Traffic Signal Control Joint Optimization Vehicle Routing Signal Control

September 19, 2023

Hybrid State Space-based Learning for Sequential Data Prediction with Joint Optimization
Mustafa E. Aydın, Arda Fazla, Suleyman S. Kozat
LeArning Abstract Time Series Recurrent Neural Network Joint Optimization Nonlinear Prediction Sequential Prediction State Space Representation

August 21, 2023

Efficient Joint Optimization of Layer-Adaptive Weight Pruning in Deep Neural Networks
Kaixin Xu, Zhe Wang, Xue Geng, Jie Lin, Min Wu, Xiaoli Li, Weisi Lin
Deep Neural Network Joint Optimization Pruning Ratio Layer Adaptive Weight Pruning

August 7, 2023

TIJO: Trigger Inversion with Joint Optimization for Defending Multimodal Backdoored Models
Indranil Sur, Karan Sikka, Matthew Walmer, Kaushik Koneripalli, Anirban Roy, Xiao Lin, Ajay Divakaran, Susmit Jha
Backdoor Defense Backdoor Trigger Joint Optimization Multimodal Backdoor Trigger Inversion

June 9, 2023

Acoustic Scene Clustering Using Joint Optimization of Deep Embedding Learning and Clustering Iteration
Yanxiong Li, Mingle Liu, Wucheng Wang, Yuhan Zhang, Qianhua He
Loss Function Feature Embeddings Joint Optimization Acoustic Scene Classification Acoustic Scene Audio Feature Iterative Clustering

June 1, 2023

BOtied: Multi-objective Bayesian optimization with tied multivariate ranks
Ji Won Park, Nataša Tagasovska, Michael Maser, Stephen Ra, Kyunghyun Cho
Pareto Optimal Joint Optimization Multi Objective Bayesian Optimization Bot Account Joint Distribution

May 30, 2023

Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in Segmentation
Zeju Li, Konstantinos Kamnitsas, Qi Dou, Chen Qin, Ben Glocker
Data Augmentation Segmentation Based Approach Joint Optimization Test Time Augmentation Data Augmentation Strategy

May 16, 2023

Optimizing pre-scheduled, intermittently-observed MDPs
Patrick Zhong, Federico Rossi, Dylan A. Shell
Optimal Policy Multi Objective Optimization Problem Joint Optimization Robotics Problem Implicit Coordination

April 18, 2023

Joint Age-based Client Selection and Resource Allocation for Communication-Efficient Federated Learning over NOMA Networks
Bibo Wu, Fang Fang, Xianbin Wang
Resource Allocation Client Selection Joint Optimization Joint Framework Non Orthogonal Multiple Access

April 9, 2023

SLowcal-SGD: Slow Query Points Improve Local-SGD for Stochastic Convex Optimization
Kfir Y. Levy
Stochastic Gradient Descent Joint Optimization Stochastic Convex Optimization Local SGD Local Update Efficient Query Minibatch Stochastic

March 28, 2023

March 2, 2023

Model-based Constrained MDP for Budget Allocation in Sequential Incentive Marketing
Shuai Xiao, Le Guo, Zaifan Jiang, Lei Lv, Yuanbo Chen, Jun Zhu, Shuang Yang
Constrained Markov Decision Process Joint Optimization Budget Allocation Dual Optimization

January 26, 2023

Joint Training of Deep Ensembles Fails Due to Learner Collusion
Alan Jeffares, Tennison Liu, Jonathan Crabbé, Mihaela van der Schaar
Deep Ensemble Joint Optimization Joint Training Numerical Case Study Yield Collusion

November 17, 2022

Audio Anti-spoofing Using a Simple Attention Module and Joint Optimization Based on Additive Angular Margin Loss and Meta-learning
Zhenyu Wang, John H. L. Hansen
Meta Learning Speech Synthesis Speaker Verification Voice Conversion Audio Driven Attention Module Convolution Layer Joint Optimization Attention Weight Angular Margin Loss

Joint Optimization

Papers

NeuJeans: Private Neural Network Inference with Joint Optimization of Convolution and Bootstrapping

Resource Allocation for Semantic Communication under Physical-layer Security

Optimization Theory Based Deep Reinforcement Learning for Resource Allocation in Ultra-Reliable Wireless Networked Control Systems

A Joint Gradient and Loss Based Clustered Federated Learning Design

Client Orchestration and Cost-Efficient Joint Optimization for NOMA-Enabled Hierarchical Federated Learning

Joint Optimization of Traffic Signal Control and Vehicle Routing in Signalized Road Networks using Multi-Agent Deep Reinforcement Learning

Hybrid State Space-based Learning for Sequential Data Prediction with Joint Optimization

Efficient Joint Optimization of Layer-Adaptive Weight Pruning in Deep Neural Networks

TIJO: Trigger Inversion with Joint Optimization for Defending Multimodal Backdoored Models

Acoustic Scene Clustering Using Joint Optimization of Deep Embedding Learning and Clustering Iteration

BOtied: Multi-objective Bayesian optimization with tied multivariate ranks

Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in Segmentation

Optimizing pre-scheduled, intermittently-observed MDPs

Joint Age-based Client Selection and Resource Allocation for Communication-Efficient Federated Learning over NOMA Networks

SLowcal-SGD: Slow Query Points Improve Local-SGD for Stochastic Convex Optimization

Joint optimization of a $\beta$-VAE for ECG task-specific feature extraction

Modeling and Joint Optimization of Security, Latency, and Computational Cost in Blockchain-based Healthcare Systems

Model-based Constrained MDP for Budget Allocation in Sequential Incentive Marketing

Joint Training of Deep Ensembles Fails Due to Learner Collusion

Audio Anti-spoofing Using a Simple Attention Module and Joint Optimization Based on Additive Angular Margin Loss and Meta-learning