Federated multi-objective learning
In recent years, multi-objective optimization (MOO) emerges as a foundational problem
underpinning many multi-agent multi-task learning applications. However, existing …
underpinning many multi-agent multi-task learning applications. However, existing …
Rethinking and Optimizing Workload Redistribution in Large-scale Internet Data Centers
Heuristic-based workload redistribution is the most commonly adopted solution to provide
enhanced service performance in large-scale Internet Data Centers (IDCs). However …
enhanced service performance in large-scale Internet Data Centers (IDCs). However …
On the optimal size and composition of customs unions: An evolutionary approach
Customs unions enable countries to freely access each other's markets, which is thought to
increase intra-regional trade and economic growth. However, accession to a customs union …
increase intra-regional trade and economic growth. However, accession to a customs union …
Hierarchical grammar-guided genetic programming techniques for scheduling in heterogeneous networks
Grammar-Guided Genetic Programming is already outperforming humans at creating
efficient transmission schedulers for large heterogeneous communications networks. We …
efficient transmission schedulers for large heterogeneous communications networks. We …
Milpibea: Algorithm for multi-objective features selection in (evolving) software product lines
Abstract Software Product Lines Engineering (SPLE) proposes techniques to model, create
and improve groups of related software systems in a systematic way, with different …
and improve groups of related software systems in a systematic way, with different …
A large neighborhood search approach for the data centre machine reassignment problem
One of the main challenges in data centre operations involves optimally reassigning running
processes to servers in a dynamic setting such that operational performance is improved. In …
processes to servers in a dynamic setting such that operational performance is improved. In …
Incorporating user preferences in multi-objective feature selection in software product lines using multi-criteria decision analysis
Abstract Software Product Lines Engineering has created various tools that assist with the
standardisation in the design and implementation of clusters of equivalent software systems …
standardisation in the design and implementation of clusters of equivalent software systems …
Reparation in evolutionary algorithms for multi-objective feature selection in large software product lines
Abstract Software Product Lines Engineering is the area of software engineering that aims to
systematise the modelling, creation and improvement of groups of interconnected software …
systematise the modelling, creation and improvement of groups of interconnected software …
Complex-Structured Optimization Problems in Distributed Learning
Z Liu - 2024 - search.proquest.com
In recent years, machine learning (ML) has achieved astonishing success in many areas,
including robotics, image recognition, natural language processing, and recommender …
including robotics, image recognition, natural language processing, and recommender …
A Large Neighborhood Search approach for the Machine Reassignment Problem in data centers
One of the main challenges in data centre operations involves optimally reassigning running
processes to servers in a dynamic setting such that operational performance is improved. In …
processes to servers in a dynamic setting such that operational performance is improved. In …