@unpublished{11630, abstract = {The second mission of NASA’s Kepler satellite, K2, has collected hundreds of thousands of lightcurves for stars close to the ecliptic plane. This new sample could increase the number of known pulsating stars and then improve our understanding of those stars. For the moment only a few stars have been properly classified and published. In this work, we present a method to automaticly classify K2 pulsating stars using a Machine Learning technique called Random Forest. The objective is to sort out the stars in four classes: red giant (RG), main-sequence Solar-like stars (SL), classical pulsators (PULS) and Other. To do this we use the effective temperatures and the luminosities of the stars as well as the FliPer features, that measures the amount of power contained in the power spectral density. The classifier now retrieves the right classification for more than 80% of the stars.}, author = {Saux, A. Le and Bugnet, Lisa Annabelle and Mathur, S. and Breton, S. N. and Garcia, R. A.}, booktitle = {arXiv}, keywords = {asteroseismology - methods, data analysis - thecniques, machine learning - stars, oscillations}, title = {{Automatic classification of K2 pulsating stars using machine learning techniques}}, doi = {10.48550/arXiv.1906.09611}, year = {2019}, } @inproceedings{11826, abstract = {The diameter, radius and eccentricities are natural graph parameters. While these problems have been studied extensively, there are no known dynamic algorithms for them beyond the ones that follow from trivial recomputation after each update or from solving dynamic All-Pairs Shortest Paths (APSP), which is very computationally intensive. This is the situation for dynamic approximation algorithms as well, and even if only edge insertions or edge deletions need to be supported. This paper provides a comprehensive study of the dynamic approximation of Diameter, Radius and Eccentricities, providing both conditional lower bounds, and new algorithms whose bounds are optimal under popular hypotheses in fine-grained complexity. Some of the highlights include: - Under popular hardness hypotheses, there can be no significantly better fully dynamic approximation algorithms than recomputing the answer after each update, or maintaining full APSP. - Nearly optimal partially dynamic (incremental/decremental) algorithms can be achieved via efficient reductions to (incremental/decremental) maintenance of Single-Source Shortest Paths. For instance, a nearly (3/2+epsilon)-approximation to Diameter in directed or undirected n-vertex, m-edge graphs can be maintained decrementally in total time m^{1+o(1)}sqrt{n}/epsilon^2. This nearly matches the static 3/2-approximation algorithm for the problem that is known to be conditionally optimal.}, author = {Ancona, Bertie and Henzinger, Monika H and Roditty, Liam and Williams, Virginia Vassilevska and Wein, Nicole}, booktitle = {46th International Colloquium on Automata, Languages, and Programming}, isbn = {978-3-95977-109-2}, issn = {1868-8969}, location = {Patras, Greece}, publisher = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik}, title = {{Algorithms and hardness for diameter in dynamic graphs}}, doi = {10.4230/LIPICS.ICALP.2019.13}, volume = {132}, year = {2019}, } @inproceedings{11850, abstract = {Modern networked systems are increasingly reconfigurable, enabling demand-aware infrastructures whose resources can be adjusted according to the workload they currently serve. Such dynamic adjustments can be exploited to improve network utilization and hence performance, by moving frequently interacting communication partners closer, e.g., collocating them in the same server or datacenter. However, dynamically changing the embedding of workloads is algorithmically challenging: communication patterns are often not known ahead of time, but must be learned. During the learning process, overheads related to unnecessary moves (i.e., re-embeddings) should be minimized. This paper studies a fundamental model which captures the tradeoff between the benefits and costs of dynamically collocating communication partners on l servers, in an online manner. Our main contribution is a distributed online algorithm which is asymptotically almost optimal, i.e., almost matches the lower bound (also derived in this paper) on the competitive ratio of any (distributed or centralized) online algorithm.}, author = {Henzinger, Monika H and Neumann, Stefan and Schmid, Stefan}, booktitle = {SIGMETRICS'19: International Conference on Measurement and Modeling of Computer Systems}, isbn = {978-1-4503-6678-6}, location = {Phoenix, AZ, United States}, pages = {43–44}, publisher = {Association for Computing Machinery}, title = {{Efficient distributed workload (re-)embedding}}, doi = {10.1145/3309697.3331503}, year = {2019}, } @inbook{11847, abstract = {This paper serves as a user guide to the Vienna graph clustering framework. We review our general memetic algorithm, VieClus, to tackle the graph clustering problem. A key component of our contribution are natural recombine operators that employ ensemble clusterings as well as multi-level techniques. Lastly, we combine these techniques with a scalable communication protocol, producing a system that is able to compute high-quality solutions in a short amount of time. After giving a description of the algorithms employed, we establish the connection of the graph clustering problem to protein–protein interaction networks and moreover give a description on how the software can be used, what file formats are expected, and how this can be used to find functional groups in protein–protein interaction networks.}, author = {Biedermann, Sonja and Henzinger, Monika H and Schulz, Christian and Schuster, Bernhard}, booktitle = {Protein-Protein Interaction Networks}, editor = {Canzar, Stefan and Rojas Ringeling, Francisca}, isbn = {9781493998722}, issn = {1940-6029}, pages = {215–231}, publisher = {Springer Nature}, title = {{Vienna Graph Clustering}}, doi = {10.1007/978-1-4939-9873-9_16}, volume = {2074}, year = {2019}, } @inproceedings{11853, abstract = {We present a deterministic dynamic algorithm for maintaining a (1+ε)f-approximate minimum cost set cover with O(f log(Cn)/ε^2) amortized update time, when the input set system is undergoing element insertions and deletions. Here, n denotes the number of elements, each element appears in at most f sets, and the cost of each set lies in the range [1/C, 1]. Our result, together with that of Gupta~et~al.~[STOC'17], implies that there is a deterministic algorithm for this problem with O(f log(Cn)) amortized update time and O(min(log n, f)) -approximation ratio, which nearly matches the polynomial-time hardness of approximation for minimum set cover in the static setting. Our update time is only O(log (Cn)) away from a trivial lower bound. Prior to our work, the previous best approximation ratio guaranteed by deterministic algorithms was O(f^2), which was due to Bhattacharya~et~al.~[ICALP`15]. In contrast, the only result that guaranteed O(f) -approximation was obtained very recently by Abboud~et~al.~[STOC`19], who designed a dynamic algorithm with (1+ε)f-approximation ratio and O(f^2 log n/ε) amortized update time. Besides the extra O(f) factor in the update time compared to our and Gupta~et~al.'s results, the Abboud~et~al.~algorithm is randomized, and works only when the adversary is oblivious and the sets are unweighted (each set has the same cost). We achieve our result via the primal-dual approach, by maintaining a fractional packing solution as a dual certificate. This approach was pursued previously by Bhattacharya~et~al.~and Gupta~et~al., but not in the recent paper by Abboud~et~al. Unlike previous primal-dual algorithms that try to satisfy some local constraints for individual sets at all time, our algorithm basically waits until the dual solution changes significantly globally, and fixes the solution only where the fix is needed.}, author = {Bhattacharya, Sayan and Henzinger, Monika H and Nanongkai, Danupon}, booktitle = {60th Annual Symposium on Foundations of Computer Science}, isbn = {978-1-7281-4953-0}, issn = {2575-8454}, location = {Baltimore, MD, United States}, pages = {406--423}, publisher = {Institute of Electrical and Electronics Engineers}, title = {{A new deterministic algorithm for dynamic set cover}}, doi = {10.1109/focs.2019.00033}, year = {2019}, }