Results 11 to 20 of about 14,976,458 (288)

Transitional Leakage in Theory and Practice

Transactions on Cryptographic Hardware and Embedded Systems, 2022
Accelerated by the increased interconnection of highly accessible devices, the demand for effective and efficient protection of hardware designs against Side-Channel Analysis (SCA) is ever rising, causing its topical relevance to remain immense in both,
Nicolai Müller, David Knichel, Pascal Sasdrich, Amir Moradi   +3 more
doaj   +1 more source

Engineering and Probing Non-Abelian Chiral Spin Liquids Using Periodically Driven Ultracold Atoms

PRX Quantum, 2023
We propose a scheme to implement Kitaev’s honeycomb model with cold atoms, based on a periodic (Floquet) drive, in view of realizing and probing non-Abelian chiral spin liquids using quantum simulators.
Bo-Ye Sun, Nathan Goldman, Monika Aidelsburger, Marin Bukov   +3 more
doaj   +1 more source

Self-Supervised Latent Representations of Network Flows and Application to Darknet Traffic Classification

IEEE Access, 2023
Characterizing network flows is essential for security operators to enhance their awareness about cyber-threats targeting their networks. The automation of network flow characterization with machine learning has received much attention in recent years ...
Mehdi Zakroum, Jerome Francois, Mounir Ghogho, Isabelle Chrisment   +3 more
doaj   +1 more source

Probing Out-of-Distribution Robustness of Language Models with Parameter-Efficient Transfer Learning

Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023), 2023
As the size of the pre-trained language model (PLM) continues to increase, numerous parameter-efficient transfer learning methods have been proposed recently to compensate for the tremendous cost of fine-tuning. Despite the impressive results achieved by large pre-trained language models (PLMs) and various parameter-efficient transfer learning (PETL ...
Hyunsoo Cho, Choonghyun Park, Junyeop Kim, Hyuhng Joon Kim, Kang Min Yoo, Sang-goo Lee   +5 more
openaire   +2 more sources

Composable Gadgets with Reused Fresh Masks

Transactions on Cryptographic Hardware and Embedded Systems, 2022
Albeit its many benefits, masking cryptographic hardware designs has proven to be a non-trivial and error-prone task, even for experienced engineers.
David Knichel, Amir Moradi
doaj   +1 more source

In-Context Probing: Toward Building Robust Classifiers via Probing Large Language Models

, 2023
Large language models are able to learn new tasks in context, where they are provided with instructions and a few annotated examples. However, the effectiveness of in-context learning is dependent on the provided context, and the performance on a downstream task can vary considerably, depending on the instruction.
Amini, Afra, Ciaramita, Massimiliano
openaire   +2 more sources

Submodular stochastic probing on matroids [PDF]

, 2014
In a stochastic probing problem we are given a universe E, where each element e in E is active independently with probability p in [0,1], and only a probe of e can tell us whether it is active or not. On this universe we execute a process that one by one
Sviridenko, Maxim, Marek Adamczyk, Maxim Sviridenko, Adamczyk, Marek, Justin Ward, Ward, Justin   +5 more
core   +1 more source

Model Identification and Robust Nonlinear Model Predictive Control of a Twin Rotor MIMO System [PDF]

, 2009
PhDThis thesis presents an investigation into a number of model predictive control (MPC) paradigms for a nonlinear aerodynamics test rig, a twin rotor multi-input multi-output system (TRMS).
Rahideh, Akbar
core   +4 more sources

Robust statistical modeling improves sensitivity of high-throughput RNA structure probing experiments [PDF]

Nature Methods, 2016
Structure probing coupled with high-throughput sequencing could revolutionize our understanding of the role of RNA structure in regulation of gene expression. Despite recent technological advances, intrinsic noise and high sequence coverage requirements greatly limit the applicability of these techniques.
Selega, A., Sirocchi, C., Iosub, I., Granneman, S., Sanguinetti, G.   +4 more
openaire   +4 more sources

ShortcutProbe: Probing Prediction Shortcuts for Learning Robust Models

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence
Deep learning models often achieve high performance by inadvertently learning spurious correlations between targets and non-essential features. For example, an image classifier may identify an object via its background that spuriously correlates with it.
Guangtao Zheng, Wenqian Ye, Aidong Zhang 0001   +2 more
openaire   +2 more sources