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Found 5 papers, 2 papers with code
On the Multidimensional Random Subset Sum Problem
random variables $X_1, ..., X_n$, we wish to approximate any point $z \in [-1, 1]$ as the sum of a suitable subset $X_{i_1(z)}, ..., X_{i_s(z)}$ of them, up to error $\varepsilon$.
Planning with Biological Neurons and Synapses
We revisit the planning problem in the blocks world, and we implement a known heuristic for this task.
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.
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.
Finding a Bounded-Degree Expander Inside a Dense One
It follows from the Marcus-Spielman-Srivastava proof of the Kadison-Singer conjecture that if $G=(V, E)$ is a $\Delta$-regular dense expander then there is an edge-induced subgraph $H=(V, E_H)$ of $G$ of constant maximum degree which is also an expander.
Distributed, Parallel, and Cluster Computing
