2 citations · 4 across the 7 of their papers we have counts for
7 papers
Early Prediction of Student Performance Using Bayesian Updating with Informative Priors Across Cohorts
Jakob Schwerter, Amer Krivosija, Tim Novak +2
Early identification of at risk students in higher education depends on predictive models that maintain accuracy across successive cohorts -- a requirement that single-cohort model…
Improved Learning via k-DTW: A Novel Dissimilarity Measure for Curves
Amer Krivošija, Alexander Munteanu, André Nusser +1
This paper introduces -Dynamic Time Warping (-DTW), a novel dissimilarity measure for polygonal curves. -DTW has stronger metric properties than Dynamic Time Warping (DTW)…
Scalable Learning of Item Response Theory Models
Susanne Frick, Amer Krivošija, Alexander Munteanu
Item Response Theory (IRT) models aim to assess latent abilities of examinees along with latent difficulty characteristics of test items from categorical data that indicate…
Computing the Fréchet distance of trees and graphs of bounded tree width
Maike Buchin, Amer Krivošija, Alexander Neuhaus
We give algorithms to compute the Fréchet distance of trees and graphs with bounded tree width. Our algorithms run in time for trees of bounded degree, and $O(n^2\sqrt{n \…
On the complexity of the middle curve problem
Maike Buchin, Nicole Funk, Amer Krivošija
For a set of curves, Ahn et al. introduced the notion of a middle curve and gave algorithms computing these with run time exponential in the number of curves. Here we study the com…
Probabilistic smallest enclosing ball in high dimensions via subgradient sampling
Amer Krivošija, Alexander Munteanu
We study a variant of the median problem for a collection of point sets in high dimensions. This generalizes the geometric median as well as the (probabilistic) smallest enclosing…
Clustering time series under the Fréchet distance
Anne Driemel, Amer Krivošija, Christian Sohler
The Fréchet distance is a popular distance measure for curves. We study the problem of clustering time series under the Fréchet distance. In particular, we give -a…