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of 31
pro vyhledávání: '"Lavoie, Erick"'
Autor:
Lavoie, Erick
Replicated append-only logs sequentially order messages from the same author such that their ordering can be eventually recovered even with out-of-order and unreliable dissemination of individual messages. They are widely used for implementing replic
Externí odkaz:
http://arxiv.org/abs/2307.08381
Autor:
Lavoie, Erick
Conventional blockchains use consensus algorithms that totally order updates across all accounts, which is stronger than necessary to implement a replicated ledger. This makes updates slower and more expensive than necessary. More recent consensus-fr
Externí odkaz:
http://arxiv.org/abs/2305.16976
Autor:
Lavoie, Erick
***** This design is a duplicate of a Causal Length Set (see notes in the comments). We leave nonetheless the original paper here because the proofs are referred to in another submission.***** The 2P-Set Conflict-Free Replicated Data Type (CRDT) supp
Externí odkaz:
http://arxiv.org/abs/2304.01929
Autor:
de Vos, Martijn, Dhasade, Akash, Kermarrec, Anne-Marie, Lavoie, Erick, Pouwelse, Johan, Sharma, Rishi
Decentralized learning (DL) leverages edge devices for collaborative model training while avoiding coordination by a central server. Due to privacy concerns, DL has become an attractive alternative to centralized learning schemes since training data
Externí odkaz:
http://arxiv.org/abs/2302.13837
One of the key challenges in decentralized and federated learning is to design algorithms that efficiently deal with highly heterogeneous data distributions across agents. In this paper, we revisit the analysis of the popular Decentralized Stochastic
Externí odkaz:
http://arxiv.org/abs/2204.04452
The convergence speed of machine learning models trained with Federated Learning is significantly affected by heterogeneous data partitions, even more so in a fully decentralized setting without a central server. In this paper, we show that the impac
Externí odkaz:
http://arxiv.org/abs/2104.07365
WebRTC enables browsers to exchange data directly but the number of possible concurrent connections to a single source is limited. We overcome the limitation by organizing participants in a fat-tree overlay: when the maximum number of connections of
Externí odkaz:
http://arxiv.org/abs/1904.11402
Autor:
Lavoie, Erick, Hendren, Laurie
We propose personal volunteer computing, a novel paradigm to encourage technical solutions that leverage personal devices, such as smartphones and laptops, for personal applications that require significant computations, such as animation rendering a
Externí odkaz:
http://arxiv.org/abs/1804.01482
The large penetration and continued growth in ownership of personal electronic devices represents a freely available and largely untapped source of computing power. To leverage those, we present Pando, a new volunteer computing tool based on a declar
Externí odkaz:
http://arxiv.org/abs/1803.08426