Zobrazeno 1 - 10
of 176
pro vyhledávání: '"Crovella, Mark"'
Learning from Label Proportions (LLP) is an established machine learning problem with numerous real-world applications. In this setting, data items are grouped into bags, and the goal is to learn individual item labels, knowing only the features of t
Externí odkaz:
http://arxiv.org/abs/2310.19065
Publikováno v:
In Cell Reports Methods 25 March 2024 4(3)
Seemingly overnight, the Internet has gone from an academic experiment to a worldwide information matrix. Along the way, computer scientists have come to realize that understanding the performance of the Internet is a remarkably challenging and subtl
Externí odkaz:
https://ul.qucosa.de/id/qucosa%3A32406
https://ul.qucosa.de/api/qucosa%3A32406/attachment/ATT-0/
https://ul.qucosa.de/api/qucosa%3A32406/attachment/ATT-0/
Autor:
Law, Jeffrey N., Akers, Kyle, Tasnina, Nure, Della Santina, Catherine M., Deutsch, Shay, Kshirsagar, Meghana, Klein-Seetharaman, Judith, Crovella, Mark, Rajagopalan, Padmavathy, Kasif, Simon, Murali, T. M.
Background: Network propagation has been widely used for nearly 20 years to predict gene functions and phenotypes. Despite the popularity of this approach, little attention has been paid to the question of provenance tracing in this context, e.g., de
Externí odkaz:
http://arxiv.org/abs/2006.01968
Fairness concerns about algorithmic decision-making systems have been mainly focused on the outputs (e.g., the accuracy of a classifier across individuals or groups). However, one may additionally be concerned with fairness in the inputs. In this pap
Externí odkaz:
http://arxiv.org/abs/2005.09209
The increasing role of recommender systems in many aspects of society makes it essential to consider how such systems may impact social good. Various modifications to recommendation algorithms have been proposed to improve their performance for speci
Externí odkaz:
http://arxiv.org/abs/1812.01504
In many applications, e.g., recommender systems and traffic monitoring, the data comes in the form of a matrix that is only partially observed and low rank. A fundamental data-analysis task for these datasets is matrix completion, where the goal is t
Externí odkaz:
http://arxiv.org/abs/1705.00399
Matrix completion is a problem that arises in many data-analysis settings where the input consists of a partially-observed matrix (e.g., recommender systems, traffic matrix analysis etc.). Classical approaches to matrix completion assume that the inp
Externí odkaz:
http://arxiv.org/abs/1705.00375
Autor:
Salamatian, Loqman, Anderson, Scott, Mathews, Joshua, Barford, Paul, Willinger, Walter, Crovella, Mark
Publikováno v:
Communications of the ACM; Aug2023, Vol. 66 Issue 8, p95-103, 9p, 1 Color Photograph, 3 Graphs
In this work we focus on modeling a little studied type of traffic, namely the network traffic generated from endhosts. We introduce a parsimonious parametric model of the marginal distribution for connection arrivals. We employ mixture models based
Externí odkaz:
http://arxiv.org/abs/1212.2744