Results 41 to 50 of about 2,082,460 (297)

Design of Robust Sparse Wideband Beamformers with Circular-Model Mismatches Based on Reweighted 2,1 Optimization

open access: yesRemote Sensing, 2023
Wideband beamformers have been widely studied in wireless communication, remote sensing and so on. Generally speaking, to improve the spatial filtering ability of beamformers, there usually needs more sensors, which implies increased computational ...
Yu Bao   +4 more
doaj   +1 more source

Stochastic Robustness: Towards a Comprehensive Robustness Tool [PDF]

open access: yes, 1990
Stochastic robustness is a simple technique to determine the robustness of linear, time-invariant systems by Monte Carlo methods. Stochastic stability robustness has been described previously.
Ray, Laurie Ryan
core   +1 more source

Evolution under fluctuating environments explains observed robustness in metabolic networks [PDF]

open access: yes, 2010
A high level of robustness against gene deletion is observed in many organisms. However, it is still not clear which biochemical features underline this robustness and how these are acquired during evolution.
Pfeiffer, Thomas, Soyer, Orkun S.
core   +2 more sources

Sirolimus for Extracranial Arteriovenous Malformations: A Scoping Review of the Evidence in Syndromic and Non‐Syndromic Cases

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Arteriovenous malformations (AVMs) are rare, high‐flow, vascular anomalies that can occur either sporadically or as part of a genetic syndrome. AVMs can progress with serious morbidity and even mortality if left unchecked. Sirolimus is an mTOR inhibitor that is effective in low‐flow vascular malformations; however, its role in AVMs is unclear.
Will Swansson   +3 more
wiley   +1 more source

Robust Growth Determinants [PDF]

open access: yesSSRN Electronic Journal, 2011
This paper investigates the robustness of determinants of economic growth in the presence of model uncertainty, parameter heterogeneity and outliers. The robust model averaging approach introduced in the paper uses a flexible and parsimonious mixture modeling that allows for fat-tailed errors compared to the normal benchmark case. Applying robust model
Doppelhofer, Gernot, Weeks, Melvyn
openaire   +5 more sources

Identifying Robust Radiomics Features for Lung Cancer by Using In-Vivo and Phantom Lung Lesions

open access: yesTomography, 2021
We propose a novel framework for determining radiomics feature robustness by considering the effects of both biological and noise signals. This framework is preliminarily tested in a study predicting the epidermal growth factor receptor (EGFR) mutation ...
Lin Lu   +7 more
doaj   +1 more source

Robust e-Voting Composition [PDF]

open access: yes, 2011
This paper is concerned with the presentation of a perspective on robustness in e-voting systems. It is argued that the effective design of an e-voting system and its viability can be enhanced by a two-pronged approach to robustness. First, it requires a
Anane, Rachid, Cooke, Richard
core   +1 more source

Intravitreal GD2‐Specific Chimeric Antigen Receptor T‐Cell Therapy for Refractory Retinoblastoma

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Effective treatments for advanced, treatment‐resistant retinoblastoma (RB) remain limited. GD2‐specific chimeric antigen receptor (CAR) T cells show potent antitumor activity with minimal toxicity but have not previously been evaluated in RB.
Subongkoch Subhadhirasakul   +13 more
wiley   +1 more source

Robust Forecast Comparison [PDF]

open access: yesSSRN Electronic Journal, 2015
Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence of the use of misspecified models in multiple model comparisons, relative forecast rankings are loss function dependent. In order to address this issue, a novel criterion for forecast evaluation that utilizes the entire distribution of forecast errors ...
JIN, Sainan   +2 more
openaire   +6 more sources

Robust Proxy: Improving Adversarial Robustness by Robust Proxy Learning

open access: yesIEEE Transactions on Information Forensics and Security, 2023
Recently, it has been widely known that deep neural networks are highly vulnerable and easily broken by adversarial attacks. To mitigate the adversarial vulnerability, many defense algorithms have been proposed. Recently, to improve adversarial robustness, many works try to enhance feature representation by imposing more direct supervision on the ...
Hong Joo Lee, Yong Man Ro
openaire   +2 more sources

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