Patrick K. Nicholson
Bell Labs
62 Papers
348 Citations
Patrick K. Nicholson is an academic researcher from Bell Labs. The author has contributed to research in topics: Data structure & Succinct data structure. The author has an hindex of 14, co-authored 62 publications. Previous affiliations of Patrick K. Nicholson include Max Planck Society & Alcatel-Lucent.
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Papers
Cartel: A System for Collaborative Transfer Learning at the Edge
Harshit Daga,Patrick K. Nicholson,Ada Gavrilovska,Diego Lugones +3 more
- 20 Nov 2019
TL;DR: Cartel is proposed, a system for collaborative learning in edge clouds that creates a model-sharing environment in which tailored models at each edge can quickly adapt to changes, and can be as robust and accurate as centralized models.
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On Reconfiguring 5G Network Slices
TL;DR: Matryoshka, the divide-and-conquer approach for finding a sequence of feasible configurations that can be used to reconfigure 5G network slices, is presented and it is observed that it yields close-to-optimal reconfiguration sequences 10X faster than existing approaches.
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Monitorless: Predicting Performance Degradation in Cloud Applications with Machine Learning
Johannes Grohmann,Patrick K. Nicholson,Jesus Omana Iglesias,Samuel Kounev,Diego Lugones +4 more
- 09 Dec 2019
TL;DR: A monitorless model to streamline application deployment by delegating performance management is discussed and it is shown that training a machine learning model with platform-level data, collected from the execution of representative containerized services, allows inferring application KPI degradation.
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Weighted Ancestors in Suffix Trees
Paweł Gawrychowski,Moshe Lewenstein,Patrick K. Nicholson +2 more
- 08 Sep 2014
TL;DR: It is shown that a suffix tree built for a text w[1..n] can be preprocessed using O(n) extra space, so that queries can be answered in O(1) time, which improves the running times of several applications.
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Finding frequent elements in compressed 2D arrays and strings
Travis Gagie,Meng He,J. Ian Munro,Patrick K. Nicholson +3 more
- 17 Oct 2011
TL;DR: An O(n min(log(1/α), H +1) log n) bit data structure for strings that, in O(1 /β) time, can return the O( 1/β) elements that have relative frequency at least β in a given range, without false positives, for β ≥ α.
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