text:   Guarantees",5,"['Our new paper is out! We investigate the impacts of Compression on #FederatedLearning and present FedCOMGATE, which improves SOTA. We provide sharp guarantees under different settings in FL with Compression. <LINK>\n@Farzinhaddadpou @AryanMokhtari @mehrdadmahdavi <LINK>', 'We show that even without compression, our algorithm matches the SOTA results with no extra control variable. We provide guarantees for general nonconvex, PL/strongly convex, and general convex objective functions, as well as, homogeneous and heterogenous data distributions.', 'We accompanied our theoretical results with extensive experimental results. We investigate both Quantization and Sparsification as the compression method in our algorithm.\n#Quantization #Sparsification #Compression https://t.co/OYVzNyFprN', 'We will have a major code release in the coming weeks for our Distributed Learning and Federated Learning setups, including FedCOMGATE and many more. Stay tuned. For getting updates you can follow my GitHub handle: https://t.co/9Tei2W1QXt\n#MachineLearning #DistributedOptimization', '@aminkarbasi @AryanMokhtari @Farzinhaddadpou @mehrdadmahdavi Thanks 🙏']",20,07,1101