Distributed Algorithms

By Dan Alistarh, R. Guerraoui. 2014

864 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Computer Networks and Communications

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In Computational Theory and Mathematics

In Computer Networks and Communications

Citations in the corpus

Defending non-Bayesian learning against adversarial attacks (2016, positive): “to have complete knowledge of system, including the network topology, underlying running algorithm, the states or even the entire history. The faulty agents may collaborate with each other adaptively [12]. Note that |F|≤fand |N|≥n−fsince at most fagents may fail. (As noted earlier, although we assum”
Global consensus for discrete-time multi-agent systems with input saturation constraints (2014, background): “…including consensus computation (Tsitsiklis, 1984; Jadbabaie, Lin, and Morse, 2003; Olfati- Saber and Murray, 2004; Bai, Arcak, and Wen, 2011), synchronization (Wu and Chua, 1995), distributed processing (Lynch, 1996), and network flow control (Low, Paganini, and Doyle, 2002; Wen and Arcak, 2004).”
Constructing consensus controllers for networks with identical general linear agents (2010, background): “We note that the consensus problem actually has a long history in the computer science community [12].”
Consensus Computation in Unreliable Networks: A System Theoretic Approach (2010, background): “ous point, or the formation pattern for a team of autonomous vehicles; e.g., see [1], [2], [3]. Several algorithms achieving consensus have been proposed and studied in the computer science community [4]. In this work, we consider linear iterations, where, at each time instant, each node updates its”
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning (2018, methodology): “As mentioned, the adversary is assumed to have complete knowledge of the algorithm used and the data stored on all machines, and the Byzantine machines may collude [ 48] and adapt to the output of the master and normal worker machines.”
Leader-Based Optimal Coordination Control for the Consensus Problem of Multiagent Differential Games via Fuzzy Adaptive Dynamic Programming (2015, background): “) have received considerable attention, such as [7], [8] and [9]. In the early days, consensus problems originated from computer science and formed the foundation of the ﬁeld of distributed computing [10]. Subsequently, these problems were developed to management science and statistics [11]. Now, re”
When Neurons Fail - Technical Report (2016, background): “, to handle the synchronicity of message passing between the subsets of the network [20].”
Efficient Exploration via State Marginal Matching (2019, methodology): “experiments, we leave the latent prior p(z) as ﬁxed and uniform. Note that the updates for each zcan be conducted in parallel. A distributed implementation would emulate broadcast-collect algorithms [Lynch, 1996], with each worker updating the policy independently, and periodically aggregating resul”