5 citations · 7 across the 14 of their papers we have counts for
6 papers · 1 filter
Offline Stochastic Optimization of Black-Box Objective Functions
Juncheng Dong, Zihao Wu, Hamid Jafarkhani +2
Many challenges in science and engineering, such as drug discovery and communication network design, involve optimizing complex and expensive black-box functions across vast search…
Communication Compression for Distributed Learning without Control Variates
Tomas Ortega, Chun-Yin Huang, Xiaoxiao Li +1
Distributed learning algorithms, such as the ones employed in Federated Learning (FL), require communication compression to reduce the cost of client uploads. The compression metho…
Quantized and Asynchronous Federated Learning
Tomas Ortega, Hamid Jafarkhani
Recent advances in federated learning have shown that asynchronous variants can be faster and more scalable than their synchronous counterparts. However, their design does not incl…
A Reinforcement Learning Approach for Wildfire Tracking with UAV Swarms
Carles Diaz-Vilor, Angel Lozano, Hamid Jafarkhani
Suitably equipped with cameras and sensors, uncrewed aerial vehicles (UAVs) can be instrumental for wildfire prediction, tracking, and monitoring, provided that uninterrupted conne…
Decentralized Optimization in Time-Varying Networks with Arbitrary Delays
Tomas Ortega, Hamid Jafarkhani
We consider a decentralized optimization problem for networks affected by communication delays. Examples of such networks include collaborative machine learning, sensor networks, a…
Decentralized Optimization in Networks with Arbitrary Delays
Tomas Ortega, Hamid Jafarkhani
We consider the problem of decentralized optimization in networks with communication delays. To accommodate delays, we need decentralized optimization algorithms that work on direc…