5 citations · 12 across the 11 of their papers we have counts for
15 papers
Time Series Decomposition using the Fréchet Distance
Anne Driemel, Jan Höckendorff, Ioannis Psarros +1
In this paper, we introduce a new data analysis problem that aims to decompose a set of univariate time series into a small set of base curves of length at most such that t…
A near-linear time approximation scheme for -median clustering under discrete Fréchet distance
Anne Driemel, Jan Höckendorff, Ioannis Psarros +1
A time series of complexity is a sequence of real valued measurements. The discrete Fréchet distance is a distance measure between two time series and …
Data-driven soiling detection in PV modules
Alexandros Kalimeris, Ioannis Psarros, Giorgos Giannopoulos +3
Soiling is the accumulation of dirt in solar panels which leads to a decreasing trend in solar energy yield and may be the cause of vast revenue losses. The effect of soiling can b…
Random projections for curves in high dimensions
Ioannis Psarros, Dennis Rohde
Modern time series analysis requires the ability to handle datasets that are inherently high-dimensional; examples include applications in climatology, where measurements from nume…
Approximating Length-Restricted Means under Dynamic Time Warping
Maike Buchin, Anne Driemel, Koen van Greevenbroek +2
We study variants of the mean problem under the -Dynamic Time Warping (-DTW) distance, a popular and robust distance measure for sequential data. In our setting we are given…
Tight Bounds for Approximate Near Neighbor Searching for Time Series under the Fréchet Distance
Karl Bringmann, Anne Driemel, André Nusser +1
We study the -approximate near neighbor problem under the continuous Fréchet distance: Given a set of polygonal curves with vertices, a radius , and a parameter $k…
-ANN for time series under the Fréchet distance
Anne Driemel, Ioannis Psarros
We study approximate-near-neighbor data structures for time series under the continuous Fréchet distance. For an attainable approximation factor and a query radius , an ap…
Sublinear data structures for short Fréchet queries
Anne Driemel, Ioannis Psarros, Melanie Schmidt
We study metric data structures for curves in doubling spaces, such as trajectories of moving objects in Euclidean , where the distance between two curves is measured…
The VC Dimension of Metric Balls under Fréchet and Hausdorff Distances
Anne Driemel, André Nusser, Jeff M. Phillips +1
The Vapnik-Chervonenkis dimension provides a notion of complexity for systems of sets. If the VC dimension is small, then knowing this can drastically simplify fundamental computat…
Near neighbor preserving dimension reduction for doubling subsets of
Ioannis Z. Emiris, Vasilis Margonis, Ioannis Psarros
Randomized dimensionality reduction has been recognized as one of the fundamental techniques in handling high-dimensional data. Starting with the celebrated Johnson-Lindenstrauss L…
Products of Euclidean metrics and applications to proximity questions among curves
Ioannis Z. Emiris, Ioannis Psarros
The problem of Approximate Nearest Neighbor (ANN) search is fundamental in computer science and has benefited from significant progress in the past couple of decades. However, most…
Practical linear-space Approximate Near Neighbors in high dimension
Georgia Avarikioti, Ioannis Z. Emiris, Ioannis Psarros +1
The -approximate Near Neighbor problem in high dimensional spaces has been mainly addressed by Locality Sensitive Hashing (LSH), which offers polynomial dependence on the dimens…
High-dimensional approximate -nets
Georgia Avarikioti, Ioannis Z. Emiris, Loukas Kavouras +1
The construction of -nets offers a powerful tool in computational and metric geometry. We focus on high-dimensional spaces and present a new randomized algorithm which efficient…
Randomized embeddings with slack, and high-dimensional Approximate Nearest Neighbor
Evangelos Anagnostopoulos, Ioannis Z. Emiris, Ioannis Psarros
The approximate nearest neighbor problem (-ANN) in high dimensional Euclidean space has been mainly addressed by Locality Sensitive Hashing (LSH), which has polynomial dependenc…
Counting Euclidean embeddings of rigid graphs
Ioannis Z. Emiris, Ioannis Psarros
A graph is called (generically) rigid in if, for any choice of sufficiently generic edge lengths, it can be embedded in in a finite number of distinct…