J
John Iacono
Researcher at Université libre de Bruxelles
Publications - 174
Citations - 2286
John Iacono is an academic researcher from Université libre de Bruxelles. The author has contributed to research in topics: Data structure & Amortized analysis. The author has an hindex of 24, co-authored 170 publications receiving 2130 citations. Previous affiliations of John Iacono include New York University & Aarhus University.
Papers
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Journal ArticleDOI
Key-Independent Optimality
TL;DR: It is shown that any data structure that is key-independently optimal is expected to execute any access sequence where the key values are assigned arbitrarily to unordered data as fast as any offline binary search tree algorithm, within a multiplicative constant.
Proceedings ArticleDOI
Retroactive data structures
TL;DR: In this article, the authors introduce a new data structuring paradigm in which operations can be performed on a data structure not only in the present but also in the past, called retroactive data structures, the historical sequence of operations performed on the data structure is not fixed.
Proceedings ArticleDOI
Cache-oblivious dynamic dictionaries with update/query tradeoffs
Gerth Stølting Brodal,Erik D. Demaine,Jeremy T. Fineman,John Iacono,Stefan Langerman,J. Ian Munro +5 more
TL;DR: The xDict attains the optimal tradeoff between insertions and queries, even in the broader external-memory model, for the range where inserts cost between ε with 0 < ε < 1.
Proceedings ArticleDOI
The cost of cache-oblivious searching
Michael A. Bender,Gerth Stølting Brodal,Rolf Fagerberg,Dongdong Ge,Simai He,Haodong Hu,John Iacono,Alejandro López-Ortiz +7 more
TL;DR: It is shown that for a multilevel memory hierarchy, a simple cache-oblivious structure almost replicates the performance of an optimal parameterized k-level DAM structure, and it is demonstrated that as k grows, the search costs of the optimal k- level DAM search structure and the optimal cache-OBlivious search structure rapidly converge.
Book ChapterDOI
In Pursuit of the Dynamic Optimality Conjecture
TL;DR: In this article, the authors survey the progress that has been made in the almost thirty years since the conjecture was first formulated, and present a binary search tree algorithm that is dynamically optimal.