A Broad Study on the Transferability of Visual Representations with Contrastive Learning [PDF]
IEEE International Conference on Computer Vision, 2021 Tremendous progress has been made in visual representation learning, notably with the recent success of self-supervised contrastive learning methods.
Ashraful Islam +5 more
semanticscholar +1 more source
Boosting the Transferability of Adversarial Attacks with Global Momentum Initialization [PDF]
Expert systems with applications, 2022 Deep Neural Networks (DNNs) are vulnerable to adversarial examples, which are crafted by adding human-imperceptible perturbations to the benign inputs. Simultaneously, adversarial examples exhibit transferability across models, enabling practical black ...
Jiafeng Wang +6 more
semanticscholar +1 more source
Real space first-principles derived semiempirical pseudopotentials applied to tunneling magnetoresistance [PDF]
, 2008 In this letter we present a real space density functional theory (DFT) localized basis set semi-empirical pseudopotential (SEP) approach. The method is applied to iron and magnesium oxide, where bulk SEP and local spin density approximation (LSDA) band ...
Arfken G. B. +6 more
core +6 more sources
LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity [PDF]
European Conference on Computer Vision, 2022 We propose transferability from Large Geometric Vicinity (LGV), a new technique to increase the transferability of black-box adversarial attacks. LGV starts from a pretrained surrogate model and collects multiple weight sets from a few additional ...
Martin Gubri +4 more
semanticscholar +1 more source
Evolving Architectures With Gradient Misalignment Toward Low Adversarial Transferability
IEEE Access, 2021 Deep neural network image classifiers are known to be susceptible, not only to adversarial examples created for them, but also to those created for others.
Kevin Richard G. Operiano +3 more
doaj +1 more source
Toward Understanding and Boosting Adversarial Transferability From a Distribution Perspective [PDF]
IEEE Transactions on Image Processing, 2022 Transferable adversarial attacks against Deep neural networks (DNNs) have received broad attention in recent years. An adversarial example can be crafted by a surrogate model and then attack the unknown target model successfully, which brings a severe ...
Yao Zhu +8 more
semanticscholar +1 more source
Charting the Journey of Young Leaders: A New Model of Transferability of Skills
Merits, 2023 Globally, adolescents and young adults are calling for action from governments on global humanitarian crises, taking on leadership roles that have contributed to redefining leadership in terms of behavior and action rather than qualities and status ...
Despoina Karagianni +2 more
doaj +1 more source
On Transferability of Prompt Tuning for Natural Language Processing [PDF]
North American Chapter of the Association for Computational Linguistics, 2021 Prompt tuning (PT) is a promising parameter-efficient method to utilize extremely large pre-trained language models (PLMs), which can achieve comparable performance to full-parameter fine-tuning by only tuning a few soft prompts.
Yusheng Su +12 more
semanticscholar +1 more source
ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs [PDF]
Knowledge Discovery and Data MiningWith the development of foundation models such as large language models, zero-shot transfer learning has become increasingly significant. This is highlighted by the generative capabilities of NLP models like GPT-4, and the retrieval-based approaches of ...
Yuhan Li +4 more
semanticscholar +1 more source
A Novel MSFED Feature for the Intelligent Fault Diagnosis of Rotating Machines
Machines, 2022 The vibration energy distribution pattern usually changes with the rotating machine’s health state and is a good indicator for intelligent fault diagnosis (IFD).
Qi Zhou, Xuyan Zhang, Chaoqun Wu
doaj +1 more source