Explore more Categories
Artificial Intelligence involves the science and engineering of developing intelligent machines
The manufacturing world is at a cusp of a new revolution that will redefine conventional business models
IoT will have a major impact on businesses and consumers in the future
The world is creating 2.5 exabytes of data daily
Our research seeks to connect-the-dots across multiple trends
Personal Robots are Set to Be a $19 Billion Market
Strategic Analysis of BREXIT and its Implications to Industries, Economies and Societies
Time for a Digital Revolution in the Women’s Health Market
iFrost is a digital platform for interactive and dynamic reporting of data.
The TOEs are a great source of information which gives corporates critical information on companies to action for their strategic investments either as an open source platform or to collaborate and to develop successful products
Leveraging Open Source Tools to Accelerate Technology Development across Organizations and Regions
* Required Fields
Pay by invoice
Traditional machine learning (ML) models are centralized and involve vast amounts of data. However, both the urgency to guarantee data privacy and to abide by strict regulations imposed across regions have contributed to the emergence of a new and powerful alternative technique, federated learning. Instead of acquiring data from a central server or cloud, federated learning allows localized model training. The technique ensures privacy preservation, and better global models are trained without exchanging raw data that holds private and sensitive information. Attracted to this powerful privacy-protecting technique, a growing number of market participants, academics, and end-use industries are adopting federated learning at an unprecedented rate.Federated learning is a distributed ML architecture that enables a global model to be trained using decentralized data. It is intended to utilize data from across an organization accurately and effectively. To help companies gain valuable insights about this emerging technique, this report offers an overview of the federated learning industry, market dynamics, key market players, research directions, key application areas, and recent developments. The following chapters are included:- Overview of federated learning- Market forecast, drivers, and challenges- Key research directions for federated learning- IP landscape analysis- Key enablers and recent technology developments - Companies to action, including Edgify, Owkin, Fetch.ai, Sherpa Europe, and WeBank- Growth opportunities
Hyperscaler Demand Drives the North American Data Center Colocation Services Market
Acquisitions, Vertical Focus, and New Technologies Drive Highly Competitive North American Mobile Field Service Management (FSM) Market
Growth Opportunities in the Global Webinars and Virtual Events Market
IoT Start-Up Tracker: Smart Home
IoT Start-up Tracker: Digital Manufacturing
Singapore Data Center Colocation Services Growth Opportunities
Global Video Analytics Growth Opportunities
Indian Data Center Colocation Services Growth Opportunities
Next Wave of Deep Learning Models & Applications (RNN, CNN, and GaN)
AI in the Public Sector Growth Opportunities
composite materials market
fuel cell market
wearable electronics market
heavy commercial vehicles market
solar cell market
dietary supplements market
augmented reality market
plastic recycling market
Don't have an account? Create One!
Enter your Email Address here to receive a link to change password.
If you are an existing frost.com user, please register using the same email for seamless access
Already have an account? Login!
Use your Linkedin account to login or register within our store.You're just one click away.