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In this thesis, we explore techniques for addressing the communication bottleneck in data-parallel distributed training of deep learning models. We investigate algorithms that either reduce the size of the messages that are exchanged between workers, or th ...
decrement have been proposed, such as weakened acquisition of the motor skill. While the processes at play during the initial acquisition phase have been well-characterized in young adults, they were only scarcely investigated in older adults. The goal of ...
Uncovering structural regularities and architectural topologies of cortical circuitry is vital for understanding neural computations. Recently, an experimentally constrained algorithm generated a dense network reconstruction of a similar to 0.3-mm(3) volum ...
Two channels are said to be equivalent if they are degraded from each other. The space of equivalent channels with input alphabet X and output alphabet Y can be naturally endowed with the quotient of the Euclidean topology by the equivalence relation. We s ...
We consider the problem of finding the minimum number of transmissions in an ad-hoc network for all-to-all broadcasting using network coding. This work generalizes previous results for canonical topologies such as the circle and the wrap around grid to the ...
We introduce Endoscopic Low Coherence Interferometry to obtain topology of upper airways through commonly used rigid endoscopes. Quantitative dimensioning of upper airways pathologies is crucial to provide maximum health recovery chances, for example in or ...