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pro vyhledávání: '"Impagliazzo A"'
While graphs and abstract data structures can be large and complex, practical instances are often regular or highly structured. If the instance has sufficient structure, we might hope to compress the object into a more succinct representation. An eff
Externí odkaz:
http://arxiv.org/abs/2407.19102
The replicability crisis is a major issue across nearly all areas of empirical science, calling for the formal study of replicability in statistics. Motivated in this context, [Impagliazzo, Lei, Pitassi, and Sorrell STOC 2022] introduced the notion o
Externí odkaz:
http://arxiv.org/abs/2406.02628
Autor:
Bun, Mark, Gaboardi, Marco, Hopkins, Max, Impagliazzo, Russell, Lei, Rex, Pitassi, Toniann, Sivakumar, Satchit, Sorrell, Jessica
The notion of replicable algorithms was introduced in Impagliazzo et al. [STOC '22] to describe randomized algorithms that are stable under the resampling of their inputs. More precisely, a replicable algorithm gives the same output with high probabi
Externí odkaz:
http://arxiv.org/abs/2303.12921
Autor:
Carlo Impagliazzo, Muriel Cabianca, Maria Laura Clemente, Giuliana Siddi Moreau, Matteo Vocale, Lidia Leoni
Publikováno v:
IoT, Vol 5, Iss 1, Pp 35-57 (2024)
This paper describes the development activity that has been carried out for a living laboratory for the city of Cagliari aimed at functioning as a learning center for local SMEs willing to improve their skills in IoT and create applications that will
Externí odkaz:
https://doaj.org/article/fb3b3abe4f2a492d92e2db3884e7a609
We introduce the notion of a reproducible algorithm in the context of learning. A reproducible learning algorithm is resilient to variations in its samples -- with high probability, it returns the exact same output when run on two samples from the sa
Externí odkaz:
http://arxiv.org/abs/2201.08430
Autor:
Elena Bertelli, Michele Vizzi, Chiara Marzi, Sandro Pastacaldi, Alberto Cinelli, Martina Legato, Ron Ruzga, Federico Bardazzi, Vittoria Valoriani, Francesco Loverre, Francesco Impagliazzo, Diletta Cozzi, Samuele Nardoni, Davide Facchiano, Sergio Serni, Lorenzo Masieri, Andrea Minervini, Simone Agostini, Vittorio Miele
Publikováno v:
Diagnostics, Vol 14, Iss 15, p 1608 (2024)
Background: Biparametric MRI (bpMRI) has an important role in the diagnosis of prostate cancer (PCa), by reducing the cost and duration of the procedure and adverse reactions. We assess the additional benefit of the ADC map in detecting prostate canc
Externí odkaz:
https://doaj.org/article/6ee2ec2b09dc4d16a7db89396793bfca
Autor:
Diakonikolas, Ilias, Impagliazzo, Russell, Kane, Daniel, Lei, Rex, Sorrell, Jessica, Tzamos, Christos
We study the problem of boosting the accuracy of a weak learner in the (distribution-independent) PAC model with Massart noise. In the Massart noise model, the label of each example $x$ is independently misclassified with probability $\eta(x) \leq \e
Externí odkaz:
http://arxiv.org/abs/2106.07779
Autor:
Fleming, Noah, Göös, Mika, Impagliazzo, Russell, Pitassi, Toniann, Robere, Robert, Tan, Li-Yang, Wigderson, Avi
The Stabbing Planes proof system was introduced to model the reasoning carried out in practical mixed integer programming solvers. As a proof system, it is powerful enough to simulate Cutting Planes and to refute the Tseitin formulas -- certain unsat
Externí odkaz:
http://arxiv.org/abs/2102.05019
Autor:
Impagliazzo, Russell, McGuire, Sam
Computational pseudorandomness studies the extent to which a random variable $\bf{Z}$ looks like the uniform distribution according to a class of tests $\cal{F}$. Computational entropy generalizes computational pseudorandomness by studying the extent
Externí odkaz:
http://arxiv.org/abs/2011.06166
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