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This work studies the learning process over social networks under partial and random information sharing. In traditional social learning models, agents exchange full belief information with each other while trying to infer the true state of nature. We stud ...
Modern digital connectivity has necessitated the creation of robust methods for securely storing and transferring data. At the heart of all security infrastructure is the random number generator (RNG). While random numbers find use in a variety of applicat ...
Harnessing quantum randomness for the generation of random numbers is an important concept crucial for information security and many other computer-related applications. Quantum random number generators (QRNGs) are evolving from bulky, slow, and expensive ...
True random number generators (TRNGs) allow the generation of true random bit sequences, guaranteeing the unpredictability and perfect balancing of the generated values. TRNGs can be realised from the sampling of quantum phenomena, for instance, the detect ...
This work presents a technique to produce random bits by exploiting single-photon time of arrival. Two quantum random number generator (QRNG) devices based on the field programmable gate array (FPGA) technology are presented: Randy, which uses one discrete ...
In this work, we tackle the problem of minimising the Conditional-Value-at-Risk (CVaR) of output quantities of complex differential models with random input data, using gradient-based approaches in combination with the Multi-Level Monte Carlo (MLMC) method ...
This paper examines the minimization of the cost for an expected random production output, given an assembly of finished goods from two random inputs, matched in two categories. We describe the optimal input portfolio, first using the standard normal appro ...
We consider one-dimensional excited random walks (ERWs) with i.i.d. Markovian cookie stacks in the non-boundary recurrent regime. We prove that under diffusive scaling such an ERW converges in the standard Skorokhod topology to a multiple of Brownian motio ...
It is commonly held that asynchronous consensus is much more complex, difficult, and costly than partially-synchronous algorithms, especially without using common coins. This paper challenges that conventional wisdom with que sera consensus QSC, an approac ...
An animals' ability to learn how to make decisions based on sensory evidence is often well described by Reinforcement Learning (RL) frameworks. These frameworks, however, typically apply to event-based representations and lack the explicit and fine-grained ...
