Sep 2, 2019 · What is the difference between the following LocalCluster configurations for dask.distributed? Client(n_workers=4, processes=False, threads_per_worker=1) versus …
In the burgeoning domain of distributed quantum computing, achieving consensus amidst adversarial settings remains a pivotal challenge. We introduce an enhancement to the Quantum Byzantine Agreement (QBA) protocol, uniquely incorporating advanced err...
We establish optimal Statistical Query (SQ) lower bounds for robustly learning certain families of discrete high-dimensional distributions. In particular, we show that no efficient SQ algorithm with access to an $ε$-corrupted binary product distribu...
Deep learning has been used in a wide range of areas and made a huge breakthrough. With the ever-increasing model size and train-ing data volume, distributed deep learning emerges which utilizes a cluster to train a model in parallel. Unfortunately,...
We study the robustness of deep reinforcement learning algorithms against distribution shifts within contextual multi-stage stochastic combinatorial optimization problems from the operations research domain. In this context, risk-sensitive algorithms...
I present an analytic method for estimating the errors in fitting a distribution. A well-known theorem from statistics gives the minimum variance bound (MVB) for the uncertainty in estimating a set of parameters $ł_i$, when a distribution function...
While many resource-constrained networks, such as Internet of Things (IoT) and Internet of Vehicles (IoV), are inherently distributed, the majority still rely on central servers for fast authentication and data sharing. Blockchain-based solutions off...
Distributed quantum computation is a practical method for large-scale quantum computation on quantum processors with limited size. It can be realized by direct quantum channels in flying qubits. Moreover, the pre-established quantum entanglements can...
Sep 15, 2022 · Shein is planning to build three large distribution centers in the U.S. to help speed deliveries to customers in three to four days. The privately-held fast-fashion site currently ships …
distributions, the purely discrete scaled Poisson distribution, and the class of compound Poisson–gamma distributions that have positive mass at zero, but
Suppose that the expected number of phone calls that are handled by a switchboard in each second is 5.35. Assume that the distribution of the number of phone calls per second follows the Poisson distr...
Statistical modeling projects including regression analysis of safety performance using linear, interaction and polynomial models, and a simulation-based study of Poisson distribution approximation to the Normal distribution with hypothesis testing and visualization. (⭐ 0)
In this repo there are graphs and some computations that help understand what has to be done in order to have a better normal approximation to some discrete distributions such as Binomial and Poisson distributions (⭐ 0)
This paper presents an analysis of the architectural design of two distributed open source systems (OSS) developed in Java: Distributed Modular Audio Recognition Framework (DMARF) and General Intensional Programming System (GIPSY). The research start...
Out-of-training-distribution (OOD) scenarios are a common challenge of learning agents at deployment, typically leading to arbitrary deductions and poorly-informed decisions. In principle, detection of and adaptation to OOD scenes can mitigate their...
Recent advances have resulted in queue-based algorithms for medium access control which operate in a distributed fashion, and yet achieve the optimal throughput performance of centralized scheduling algorithms. However, fundamental performance bounds...
Video block compressive sensing has been studied for use in resource constrained scenarios, such as wireless sensor networks, but the approach still suffers from low performance and long reconstruction time. Inspired by classical distributed video co...