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Found 14 papers, 1 papers with code
CRYPTO-MINE: Cryptanalysis via Mutual Information Neural Estimation
The use of Mutual Information (MI) as a measure to evaluate the efficiency of cryptosystems has an extensive history.
Generalized Rainbow Differential Privacy
In this framework, datasets are nodes in a graph, and two neighboring datasets are connected by an edge.
Blockage Prediction in Directional mmWave Links Using Liquid Time Constant Network
We propose to use a liquid time constant (LTC) network to predict the future blockage status of a millimeter wave (mmWave) link using only the received signal power as the input to the system.
PEOPL: Characterizing Privately Encoded Open Datasets with Public Labels
Allowing organizations to share their data for training of machine learning (ML) models without unintended information leakage is an open problem in practice.
Rainbow Differential Privacy
We extend a previous framework for designing differentially private (DP) mechanisms via randomized graph colorings that was restricted to binary functions, corresponding to colorings in a graph, to multi-valued functions.
Syfer: Neural Obfuscation for Private Data Release
We quantify privacy as the number of attacker guesses required to re-identify a single image (guesswork).
Stream Distributed Coded Computing
The contribution of this paper is to devise a novel framework for joint scheduling-coding, in a setting where the workers and the arrival of stream computational jobs are based on stochastic models.
Information Theory Information Theory
Robust Improvement of the Age of Information by Adaptive Packet Coding
We consider a wireless communication network with an adaptive scheme to select the number of packets to be admitted and encoded for each transmission, and characterize the information timeliness.
Information Theory Information Theory H.1.1, E.4
Multi-Level Group Testing with Application to One-Shot Pooled COVID-19 Tests
A key requirement in containing contagious diseases, such as the Coronavirus disease 2019 (COVID-19) pandemic, is the ability to efficiently carry out mass diagnosis over large populations.
Noise Recycling
The estimate is recycled to reduce the Signal to Noise Ratio (SNR) of an orthogonal channel that is experiencing correlated noise and so improve the accuracy of its decoding.
Information Theory Information Theory
Same-Cluster Querying for Overlapping Clusters
In this paper, we look at the more practical scenario of overlapping clusters, and provide upper bounds (with algorithms) on the sufficient number of queries.
A Characterization of Guesswork on Swiftly Tilting Curves
We show that the tilt operation on a memoryless string-source parametrizes an exponential family of memoryless string-sources, which we refer to as the tilted family.
Information Theory Information Theory
Privacy with Estimation Guarantees
Here, an analyst is allowed to reconstruct (in a mean-squared error sense) certain functions of the data (utility), while other private functions should not be reconstructed with distortion below a certain threshold (privacy).
Maximum Likelihood Latent Space Embedding of Logistic Random Dot Product Graphs
A latent space model of particular interest is the Random Dot Product Graph (RDPG), which can be fit using an efficient spectral method; however, this method is based on a heuristic that can fail, even in simple cases.
