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Proving the Lottery Ticket Hypothesis for Convolutional Neural Networks
The lottery ticket hypothesis states that a randomly-initialized neural network contains a small subnetwork such that, when trained in isolation, can compete with the performance of the original network.
On Computing Pareto Optimal Paths in Weighted Time-Dependent Networks
Our algorithm can be used to solve several different minimum cost path problems in weighted point-availability time-dependent networks with a vast variety of cost definitions, and it can be easily modified in order to deal with the single destination Pareto problem.
Data Structures and Algorithms Networking and Internet Architecture
A Comparative Study of Neural Network Compression
There has recently been an increasing desire to evaluate neural networks locally on computationally-limited devices in order to exploit their recent effectiveness for several applications; such effectiveness has nevertheless come together with a considerable increase in the size of modern neural networks, which constitute a major downside in several of the aforementioned computationally-limited settings.
