Abstract: This article investigates the optimal distributed formation control for heterogeneous air–ground vehicle systems using a data-efficient, off-policy reinforcement learning algorithm.
This repository is the source code for our paper: Federated Learning under Distributed Concept Drift (AISTATS'23). Federated Learning (FL) under distributed concept drift is a largely unexplored area.
Earth observation (EO) constellations capture huge volumes of high-resolution imagery every day, but most of it never reaches the ground in time for model training. Downlink bandwidth is the main ...
In this video, we will study Supervised Learning with Examples. We will also look at types of Supervised Learning and its applications. Supervised learning is a type of Machine Learning which learns ...
Effective task allocation has become a critical challenge for multi-robot systems operating in dynamic environments like search and rescue. Traditional methods, often based on static data and ...
One of Roquan Smith's favorite sayings is "chin up, chest out." It's a reference to taking on challenges head-on, without fear or regrets. In the pool at Loyola College's aquatics center Tuesday ...
1 School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA. 2 Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA. As cloud ...
Artificial intelligence models can secretly transmit dangerous inclinations to one another like a contagion, a recent study found. Subscribe to read this story ad-free Get unlimited access to ad-free ...
The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...
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