Fingerprinting Big Data: The Case of KNN Graph Construction

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Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems". The corresponding scripts can be accessed on GitHub (https://github.com/axgoujon/convex_ridge_regularizers). The data is organized as follows: - ct_data_sets.tar.gz: contains prepr ...

When can a unimodular random planar graph be drawn in the Euclidean or the hyperbolic plane in a way that the distribution of the random drawing is isometry-invariant? This question was answered for one-ended unimodular graphs in Benjamini and Timar, using ...

Extracting value and insights from increasingly heterogeneous data sources involves multiple systems combining and consuming the data. With multi-modal and context-rich data such as strings, text, videos, or images, the problem of standardizing the data mo ...

Principal component analysis (PCA) is an essential algorithm for dimensionality reduction in many data science domains. We address the problem of performing a federated PCA on private data distributed among multiple data providers while ensuring data confi ...

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...

Discovering new materials is essential but challenging, time-consuming, and expensive. In many cases, simulations can be useful for estimating material properties. For many of the most interesting properties, however, simulations are infeasible because of ...

This dataset contains corrected particle number concentration data measured during the year-long MOSAiC expedition from October 2019 to September 2020. Some periods of the measurements were affected by repeated step changes in the particle number concentra ...

The theory underlying robust distributed learning algorithms, designed to resist adversarial machines, matches empirical observations when data is homogeneous. Under data heterogeneity however, which is the norm in practical scenarios, established lower bo ...

Systems and methods for monitoring penile tumescence are provided that overcome the drawbacks of previously known systems by providing a wearable formed of a flexible and elastic tube having a plurality of sensors disposed on or embedded within it, the wea ...

Social media studies often collect data retrospectively to analyze public opinion. Social media data may decay over time and such decay may prevent the collection of the complete dataset. As a result, the collected dataset may differ from the complete data ...

This historical dataset stems from the project of automatic extraction of 72 census records of Lausanne, Switzerland. The complete dataset covers a century of historical demography in Lausanne (1805-1898), which corresponds to 18,831 pages, and nearly 6 mi ...

Fingerprinting Big Data: The Case of KNN Graph Construction

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Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems"

A full characterization of invariant embeddability of unimodular planar graphs

E-Scan: Consuming Contextual Data with Model Plugins

Scalable and Privacy-Preserving Federated Principal Component Analysis

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Toward data-driven materials design: From atoms to pilot plants

Continuous corrected particle number concentration data in 10 sec resolution measured in the Swiss aerosol container using a whole air inlet during MOSAiC 2019/2020

Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity

Tumescense monitoring system for diagnosing erectile dysfunction and methods of use

The Impact of Data Persistence Bias on Social Media Studies

1805-1898 Census Records of Lausanne : a Long Digital Dataset for Demographic History