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Gabriel Arpino
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2020 – today
- 2024
- [i6]Gabriel Arpino, Xiaoqi Liu, Ramji Venkataramanan:
Inferring Change Points in High-Dimensional Linear Regression via Approximate Message Passing. CoRR abs/2404.07864 (2024) - 2023
- [c4]Gabriel Arpino, Ramji Venkataramanan:
Statistical-Computational Tradeoffs in Mixed Sparse Linear Regression. COLT 2023: 921-986 - [i5]Gabriel Arpino, Ramji Venkataramanan:
Statistical-Computational Tradeoffs in Mixed Sparse Linear Regression. CoRR abs/2303.02118 (2023) - [i4]Gabriel Arpino, Daniil Dmitriev, Nicolò Grometto:
Greedy Heuristics and Linear Relaxations for the Random Hitting Set Problem. CoRR abs/2305.05565 (2023) - 2022
- [i3]Freya Behrens, Gabriel Arpino, Yaroslav Kivva, Lenka Zdeborová:
(Dis)assortative Partitions on Random Regular Graphs. CoRR abs/2202.10379 (2022) - 2021
- [c3]Gintare Karolina Dziugaite, Kyle Hsu, Waseem Gharbieh, Gabriel Arpino, Daniel M. Roy:
On the role of data in PAC-Bayes. AISTATS 2021: 604-612 - [c2]Gabriel Arpino, Nicolò Grometto, Afonso S. Bandeira:
Group Testing in the High Dilution Regime. ISIT 2021: 1955-1960 - [i2]Gabriel Arpino, Nicolò Grometto, Afonso S. Bandeira:
Group Testing in the High Dilution Regime. CoRR abs/2102.01200 (2021)
2010 – 2019
- 2018
- [c1]Gabriel Arpino, Kyle Morris, Sasanka Nagavalli, Katia P. Sycara:
Using Information Invariants to Compare Swarm Algorithms and General Multi-Robot Algorithms. ICRA 2018: 7682-7687 - [i1]Gabriel Arpino, Kyle Morris, Sasanka Nagavalli, Katia P. Sycara:
Using Information Invariants to Compare Swarm Algorithms and General Multi-Robot Algorithms: A Technical Report. CoRR abs/1802.08995 (2018)
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last updated on 2024-05-31 02:30 CEST by the dblp team
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