Internet of things applications, security challenges, attacks, intrusion detection, and future visions: A systematic review
Internet of Things (IoT) technology is prospering and entering every part of our lives, be it
education, home, vehicles, or healthcare. With the increase in the number of connected …
education, home, vehicles, or healthcare. With the increase in the number of connected …
Behavioral systems theory in data-driven analysis, signal processing, and control
I Markovsky, F Dörfler - Annual Reviews in Control, 2021 - Elsevier
The behavioral approach to systems theory, put forward 40 years ago by Jan C. Willems,
takes a representation-free perspective of a dynamical system as a set of trajectories. Till …
takes a representation-free perspective of a dynamical system as a set of trajectories. Till …
Towards out-of-distribution generalization: A survey
Traditional machine learning paradigms are based on the assumption that both training and
test data follow the same statistical pattern, which is mathematically referred to as …
test data follow the same statistical pattern, which is mathematically referred to as …
Manipulating machine learning: Poisoning attacks and countermeasures for regression learning
As machine learning becomes widely used for automated decisions, attackers have strong
incentives to manipulate the results and models generated by machine learning algorithms …
incentives to manipulate the results and models generated by machine learning algorithms …
Bridging direct and indirect data-driven control formulations via regularizations and relaxations
In this article, we discuss connections between sequential system identification and control
for linear time-invariant systems, often termed indirect data-driven control, as well as a …
for linear time-invariant systems, often termed indirect data-driven control, as well as a …
Rademacher complexity for adversarially robust generalization
Many machine learning models are vulnerable to adversarial attacks; for example, adding
adversarial perturbations that are imperceptible to humans can often make machine …
adversarial perturbations that are imperceptible to humans can often make machine …
Learning with pseudo-ensembles
P Bachman, O Alsharif… - Advances in neural …, 2014 - proceedings.neurips.cc
We formalize the notion of a pseudo-ensemble, a (possibly infinite) collection of child
models spawned from a parent model by perturbing it according to some noise process. Eg …
models spawned from a parent model by perturbing it according to some noise process. Eg …
Robust Wasserstein profile inference and applications to machine learning
We show that several machine learning estimators, including square-root least absolute
shrinkage and selection and regularized logistic regression, can be represented as …
shrinkage and selection and regularized logistic regression, can be represented as …
Intergenerational mobility in Africa
A Alesina, S Hohmann, S Michalopoulos… - …, 2021 - Wiley Online Library
We examine intergenerational mobility (IM) in educational attainment in Africa since
independence using census data. First, we map IM across 27 countries and more than 2800 …
independence using census data. First, we map IM across 27 countries and more than 2800 …
Statistics of robust optimization: A generalized empirical likelihood approach
We study statistical inference and distributionally robust solution methods for stochastic
optimization problems, focusing on confidence intervals for optimal values and solutions that …
optimization problems, focusing on confidence intervals for optimal values and solutions that …