John Howat

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8ranked-venue papers

0as first author

0since 2021 · last 2016

—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 7Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science

1 paper

Computational geometry · 56% Algorithms and data structures · 44%

Topics — the 3 heaviest of 3, each with the papers that count most for it

Topic	Weight	Papers	Last	Evidence papers
Computational geometry range searching	0.1	1	2009	Biased range trees · SODA 2009
Algorithms and data structures › data structure design › search structures › search trees range trees	0.1	1	2009	Biased range trees · SODA 2009
Computational geometry › range searching › orthogonal range searching orthogonal range counting	0.0	1	2009	Biased range trees · SODA 2009

Methods — techniques the papers use, named apart from their topics

comparison tree · 0.1biased range tree · 0.1

Year	Publication	Venue	Position
2016	Biased Predecessor Search Prosenjit Bose, Rolf Fagerberg, John Howat, Pat Morin	Algorithmica	3
2014	Biased Predecessor Search Prosenjit Bose, Rolf Fagerberg, John Howat, Pat Morin	LATIN	3
2013	Fast local searches and updates in bounded universes Prosenjit Bose, Karim Douïeb, Vida Dujmovic, John Howat, Pat Morin	Comput. Geom.	4
2012	Layered Working-Set Trees Prosenjit Bose, Karim Douïeb, Vida Dujmovic, John Howat	Algorithmica	4
2012	Biased Range Trees Vida Dujmovic, John Howat, Pat Morin	Algorithmica	2
2010	Layered Working-Set Trees Prosenjit Bose, Karim Douïeb, Vida Dujmovic, John Howat	LATIN	4
2009	Biased range trees abstract A data structure, called a biased range tree, is presented that preprocesses a set S of n points in ℝ2 and a query distribution D for 2-sided orthogonal range counting queries. The expected query time for this data structure, when queries are drawn according to D, matches, to within a constant factor, that of the optimal comparison tree for S and D. The memory and preprocessing requirements of the data structure are O(n log n). Vida Dujmovic, John Howat, Pat Morin	SODA	2
2009	A Distribution-Sensitive Dictionary with Low Space Overhead Prosenjit Bose, John Howat, Pat Morin	WADS	2