Abstract: Federated Learning (FL) is a collaborative machine learning (ML) framework that combines on-device training and server-based aggregation to train a common ML model among distributed agents.

Abstract: Deep neural networks(DNNs) have been demonstrated to be vulnerable to meticulously crafted adversarial examples. Transfer-based attacks do not require ...

Delivering high-fidelity investment data across th... Financial data aggregation is foundational to modern wealth management. It enables advisors to deliver holistic advice by collecting, normalizing, ...

Community driven content discussing all aspects of software development from DevOps to design patterns. Here are the most important concepts developers must know when they size Java arrays and deal ...

Some people may have received a letter in recent weeks, offering the option to opt out of energy provided by the company selected by the Northwest Ohio Aggregation Coalition. If you got one of these ...

You might be thinking, “We already have retail choice and consumer protections when it comes to electricity in Connecticut. Why do we need something else?” Yes, individuals can choose that their ...

HTMX is a newer technology that takes plain old HTML and gives it extra powers like Ajax and DOM swaps. It’s included in my personal list of good ideas because it eliminates a whole realm of ...

Introduced with the Java 17 release, pattern matching enhances the instanceof operator so Java developers can better check and object's type and extract its components, and more efficiently deal with ...