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[PDF] Top 20 Neural Network Information Leakage through Hidden Learning

Has 10000 "Neural Network Information Leakage through Hidden Learning" found on our website. Below are the top 20 most common "Neural Network Information Leakage through Hidden Learning".

Neural Network Information Leakage through Hidden Learning

Neural Network Information Leakage through Hidden Learning

... a network for two tasks at the same time, namely the official task which a user expect it to perform, and a secret task which is achieved by feeding the output of the network into a secret network ... Voir le document complet

10

The committee machine: Computational to statistical gaps in learning a two-layers neural network

The committee machine: Computational to statistical gaps in learning a two-layers neural network

... optimal learning error in the above limit of large dimensions for a wide range of ...of hidden neurons, the existence a large hard phase in which learning is information-theoretically ... Voir le document complet

45

2020 — Modeling information flow through deep convolutional neural networks

2020 — Modeling information flow through deep convolutional neural networks

... transfer learning with the new method for feature selection based on information ...and information theory based on Chaddad et ...the neural network as a probabilistic Bayes ... Voir le document complet

180

Deep neural networks for direct, featureless learning through observation: the case of two-dimensional spin models

Deep neural networks for direct, featureless learning through observation: the case of two-dimensional spin models

... our neural network architecture on each of these three ...The neural network was able to classify all but a handful of Ising configurations, on ...the neural network is just ... Voir le document complet

11

Leakage Assessment through Neural Estimation of the Mutual Information

Leakage Assessment through Neural Estimation of the Mutual Information

... the network to perform poorly in this situation, we hypothesized that the information in the first layer, espe- cially the value of s, could be too condensed in the sense that only one neuron is used to ... Voir le document complet

19

Active learning and neural network potentials accelerate molecular screening of ether-based solvate ionic liquids

Active learning and neural network potentials accelerate molecular screening of ether-based solvate ionic liquids

... Through this NN-accelerated virtual screening workflow for ion-ligand complexes, we identified synthetic targets that have Fig. 1 (A) The validation accuracy improves with each round of active learning for ... Voir le document complet

5

Microarchitecture-Aware Virtual Machine Placement under Information Leakage Constraints

Microarchitecture-Aware Virtual Machine Placement under Information Leakage Constraints

... A covert channel is an attack which bypasses the control mechanism using legal means to leak information to unautho- rized neighbors. A covert channel breaks the confidentiality property and thus, the isolation ... Voir le document complet

9

Technical brief: air leakage paths through exterior walls

Technical brief: air leakage paths through exterior walls

... and IRC) indicate that for a given winter season, long and indirect air exfiltration paths can cause three times more accumulation of condensation on the sheathing than short and direct paths. In the envelopes of ... Voir le document complet

4

Evidence of an information leakage between logically independent blocks

Evidence of an information leakage between logically independent blocks

... board. In fact, the implemented countermeasure is designed to be logi- cally independent from the AES ’s calculations. However, registers’ updates and internal calculations induce voltage drops into the cir- cuit’s core ... Voir le document complet

7

Deep Learning with Dense Random Neural Network for Detecting Attacks against IoT-connected Home Environments

Deep Learning with Dense Random Neural Network for Detecting Attacks against IoT-connected Home Environments

... By carefully analyzing the principles of these attacks, it is possible to identify the metrics from which they can be computed. Tab. 1 presents the relevant metrics for detecting some of the attacks described above. ... Voir le document complet

7

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af en Deep Learning in Spiking Neural Networks Deep learning in spiking neural networks

... the learning rule uses the correla- tion between the teacher neuron (desired output) and the input neuron, there is not a direct physical ...the learning is constrained to fall with typical STDP eligibility ... Voir le document complet

24

A Neural Network for Semigroups

A Neural Network for Semigroups

... of neural network that is useful for under- standing semigroup ...convolutional neural networks as they do not adequately measure the structure of ... Voir le document complet

13

Comparing feedforward and recurrent neural network architectures with human behavior in artificial grammar learning

Comparing feedforward and recurrent neural network architectures with human behavior in artificial grammar learning

... artificial neural networks achieved performance close to or better than humans in several domains: tasks that were previously human prerogatives, such as language processing, have witnessed remarkable improvements ... Voir le document complet

16

A Neural Network Demand System

A Neural Network Demand System

... L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignemen[r] ... Voir le document complet

24

Improving neural tagging with lexical information

Improving neural tagging with lexical information

... 3 Integrating lexical information We extend this bi-LSTM architecture with an ad- ditional input layer that contains token-wise fea- tures obtained from a lexicon. The input vector ~l for a given word is an n-hot ... Voir le document complet

8

Analysis of complex neural circuits with nonlinear multidimensional hidden state models

Analysis of complex neural circuits with nonlinear multidimensional hidden state models

... An alternative method of choosing an appropriate σ is by plotting a receiver operating characteristic curve ( Fig. S1E ). Using a simulated model that is of similar size and structure to the dataset of interest, we ... Voir le document complet

7

Differential Privacy: on the trade-off between Utility and Information Leakage

Differential Privacy: on the trade-off between Utility and Information Leakage

... an information-theoretic view of the database query systems, and of its decomposition in terms of the query and of the randomization ...min-entropy leakage, and that the bound is ... Voir le document complet

31

Quantifying Leakage in the Presence of Unreliable Sources of Information

Quantifying Leakage in the Presence of Unreliable Sources of Information

... model information leakage in the typical scenario of protocol attacks, where the adversary has only a limited number of tries to guess the value of the secret ...mutual information is about the same, ... Voir le document complet

51

NEURAL NETWORK AND SEGMENTED LABOUR MARKET

NEURAL NETWORK AND SEGMENTED LABOUR MARKET

... Different variables were used in classifying and interpreting the results. First we used variables describing the individual (age, marital status, number of children, nationality) and professional characteristics ... Voir le document complet

22

Creating a Learning Network

Creating a Learning Network

... PublicationsArchive-ArchivesPublications@nrc-cnrc.gc.ca. If you wish to email the authors directly, please see the first page of the publication for their contact information. ... Voir le document complet

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