Rudolf Fleischer
Heinrich Heine University Düsseldorf, Computer Science Department, Department Member
ABSTRACT
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Research Interests:
Page 1. Ludolf Fleischer Bernard Moret Erik Meineche Schmidt (Eds.) Experimental Alaorithmics From Algorithm Design to Robust and Efficient Software rt. PreflowPush: Graph I^^ BI HLPreNuwPush: View1 1 lllll. I ll Page 2. Page 3. ...
... This is in line with Faltin's [14] SALA (Struc-tured Active Learning of Algorithms) approach toteaching algorithms which lets students assemble complicated algorithms from simpler components in an interactive learning... more
... This is in line with Faltin's [14] SALA (Struc-tured Active Learning of Algorithms) approach toteaching algorithms which lets students assemble complicated algorithms from simpler components in an interactive learning environment. 3 Good Teaching Animations ...
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While discrepancy theory is normally only studied in the context of 2-colorings, we explore the problem of k-coloring, for k ≥ 2, a set of vertices to minimize imbalance among a family of subsets of vertices. The imbalance is the maximum,... more
While discrepancy theory is normally only studied in the context of 2-colorings, we explore the problem of k-coloring, for k ≥ 2, a set of vertices to minimize imbalance among a family of subsets of vertices. The imbalance is the maximum, over all subsets in the family, of the largest difference between the size of any two color classes in
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Research Interests:
... (2) The computation of the convex hull of intersections of line segments. (3) The computation of the convex hull of intersections of circles. ... 4.2 Convex Hulls of Segment Intersections In this experiment, we computed the convex... more
... (2) The computation of the convex hull of intersections of line segments. (3) The computation of the convex hull of intersections of circles. ... 4.2 Convex Hulls of Segment Intersections In this experiment, we computed the convex hull of the intersection points of line segments. ...
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... of images and the picture taking device, that can be exploited to guide the upscaling process. ... space of original images mapped to the same target image is growing very fast with increasing ... rithm itself is probably not really... more
... of images and the picture taking device, that can be exploited to guide the upscaling process. ... space of original images mapped to the same target image is growing very fast with increasing ... rithm itself is probably not really new, some people might call it a vectorization technique ...
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... also would like to thank the organizing committee, most notably Gerhard Trippen, for their tremendous work in making ISAAC 2004 a ... Organization IX Referees Pankaj Agarwal Heekap Ahn Amihood Amir Nikhil Bansal Marcin Bienkowski... more
... also would like to thank the organizing committee, most notably Gerhard Trippen, for their tremendous work in making ISAAC 2004 a ... Organization IX Referees Pankaj Agarwal Heekap Ahn Amihood Amir Nikhil Bansal Marcin Bienkowski Johannes Blomer Carsten Boke Franz. ...
The standard dynamic programming solution to finding k- medians on a line with n nodes requires O(kn ) time. Dynamic programming speed-up techniques, e.g., use of the quadrangle inequality or properties of totally monotone matrices, can... more
The standard dynamic programming solution to finding k- medians on a line with n nodes requires O(kn ) time. Dynamic programming speed-up techniques, e.g., use of the quadrangle inequality or properties of totally monotone matrices, can reduce this to O(kn) time but these techniques are inherently static. The major result of this paper is to show that we can maintain the dynamic programming speedup in an online setting where points are added from left to right on a line.
We consider a problem coming from practical applications: finding a minimum spanning tree with both edge weights and inner node (non-leaf node) weights. This problem is NP-complete even in the metric space. We present two polynomial time... more
We consider a problem coming from practical applications: finding a minimum spanning tree with both edge weights and inner node (non-leaf node) weights. This problem is NP-complete even in the metric space. We present two polynomial time algorithms which achieve approximation factors of 2.35 ln n and 2(Hn − 1), respectively, where n is the number of nodes in the graph and Hn is the n-th Harmonic number. This nearly matches the lower bound: no polynomial-time approximation algorithm can achieve an approximation factor of (1−)Hn, for any > 0. For metric case where the edge weights are symmetric and satisfy the triangle inequality, it also proves to be an NP-hard problem and we give a 3.52 approximation algorithm and an improved factor 3.106 one and also show that an approximation factor of 1.463 is impossible unless N P ⊆ DT IM E[n O(loglogn) ]. We also give an approximation algorithm with factor ∆ − 1, where ∆ is the maximum degree of the graph.
How e#ciently can we search an unknown environment for a goal in unknown position? How much would it help if the environment were known? We answer these questions for simple polygons and for general graphs, by providing online search... more
How e#ciently can we search an unknown environment for a goal in unknown position? How much would it help if the environment were known? We answer these questions for simple polygons and for general graphs, by providing online search strategies that are as good as the best o#ine search algorithms, up to a constant factor. For other settings we prove that no such online algorithms exist.
... This is in line with Faltin's [14] SALA (Struc-tured Active Learning of Algorithms) approach toteaching algorithms which lets students assemble complicated algorithms from simpler components in an interactive learning... more
... This is in line with Faltin's [14] SALA (Struc-tured Active Learning of Algorithms) approach toteaching algorithms which lets students assemble complicated algorithms from simpler components in an interactive learning environment. 3 Good Teaching Animations ...
Research Interests:
Research Interests:
ABSTRACT We conduct an experimental evaluation of all major online graph traversal algorithms. This includes many simple natural algorithms as well as more sophisticated strategies. The observations we made watching the animated... more
ABSTRACT We conduct an experimental evaluation of all major online graph traversal algorithms. This includes many simple natural algorithms as well as more sophisticated strategies. The observations we made watching the animated algorithms explore the graphs in the interactive experiments motivated us to introduce some variants of the original algorithms. Since the theoretical bounds for deterministic online algorithms are rather bad and no better bounds for randomized algorithms are known, our work helps to provide a better insight into the practical performance of these algorithms on various graph families. It is to observe that all the tested algorithm have a performance very close to the optimum offline algorithm in a huge family of random graphs. Only few very specific lower bound examples cause bad results.
: Interval orders are partial orders defined by having interval representations. It is well known that a transitively oriented digraph G is an interval order iff its (undirected) complement is chordal. We investigate parallel algorithms... more
: Interval orders are partial orders defined by having interval representations. It is well known that a transitively oriented digraph G is an interval order iff its (undirected) complement is chordal. We investigate parallel algorithms for the following scheduling problem: Given a system consisting of a set T of n tasks (each requiring unit execution time) and an interval order ! over T , and given m identical parallel processors, construct an optimal (i.e., minimal length) schedule for (T; !). Our algorithm is based on a subroutine for computing so-called scheduling distances, i.e., the minimal number of time steps needed to schedule all those tasks succeeding some given task t and preceding some other task t 0 . For a given interval order with n tasks, these scheduling distances can be computed using n 3 processors and O(log 2 n) time on a CREW-PRAM. We then give an incremental version of the scheduling distance algorithm, which can be used to compute the empty slots in an ...