1 code implementation • 22 Nov 2022 • Dylan R. Ashley, Vincent Herrmann, Zachary Friggstad, Jürgen Schmidhuber
We then demonstrate how evolutionary algorithms can leverage this to extract a set of narrative templates and how these templates -- in tandem with a novel curve-fitting algorithm we introduce -- can reorder music albums to automatically induce stories in them.
1 code implementation • 3 Nov 2021 • Dylan R. Ashley, Vincent Herrmann, Zachary Friggstad, Kory W. Mathewson, Jürgen Schmidhuber
We look at how machine learning techniques that derive properties of items in a collection of independent media can be used to automatically embed stories into such collections.
no code implementations • 12 Dec 2019 • Zachary Friggstad, Chaitanya Swamy
We also give a better approximation guarantee in the special case of Directed Latency in regret metrics where the goal is to find a path $P$ minimize the average time a node $v$ waits in excess of $c_{rv}$, i. e. $\frac{1}{|V|} \cdot \sum_{v \in V} (c_v(P)-c_{rv})$.
Data Structures and Algorithms
no code implementations • 29 Mar 2016 • Zachary Friggstad, Mohsen Rezapour, Mohammad R. Salavatipour
The most well known and ubiquitous clustering problem encountered in nearly every branch of science is undoubtedly $k$-means: given a set of data points and a parameter $k$, select $k$ centres and partition the data points into $k$ clusters around these centres so that the sum of squares of distances of the points to their cluster centre is minimized.