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Classification of personal text messages has many useful applications in surveillance, e-commerce, and mental health care, to name a few. Giving applications access to personal texts can easily lead t...
We continue the study of statistical/computational tradeoffs in learning robust classifiers, following the recent work of Bubeck, Lee, Price and Razenshteyn who showed examples of classification tasks...
Fairness in classification has become an increasingly relevant and controversial issue as computers replace humans in many of today’s classification tasks. In particular, a subject of much recent deba...
Thanks to the ease of access and low expenses, it is now popular for people to store data in cloud servers. To protect sensitive data from being leaked to the outside, people usually encrypt the data ...
Privacy-preserving data analysis in the context of federated databases distributed across multiple parties has the potential to produce richer and more accurate models than what each party can learn w...
S-boxes, typically the only nonlinear part of a block cipher, are the heart of symmetric cryptographic primitives. They significantly impact the cryptographic strength and the implementation character...
The advent of Machine Learning as a Service (MLaaS) makes it possible to outsource a visual object recognition task to an external (e.g. cloud) provider. However, out- sourcing such an image classific...
In image processing, algorithms for object classification are typically based around machine learning. From the algorithm developer's perspective, these can involve a considerable amount of effort and...
Our analysis identifies two families of intractability assumptions, the qq-Generalized Diffie-Hellman Exponent assumptions and the qq-Simple Fractional assumptions that imply all other target assumpti...
Neural Networks (NN) are today increasingly used in Machine Learning where they have become deeper and deeper to accurately model or classify high-level abstractions of data. Their development however...
Machine learning classification is used in numerous settings nowadays, such as medical or genomics predictions, spam detection, face recognition, and financial predictions. Due to privacy concerns, i...
Two parties, P1 and P2, wish to jointly compute some function f(x, y) where P1 only knows x, whereas P2 only knows y. Furthermore, and most importantly, the parties wish to reveal only what the out...
In this paper, we present a new classification of 4-bit optimal S-boxes. All optimal 4-bit Sboxes can be classified into 183 different categories, among which we specify 3 platinum categories. Under...
The GHS attack is known to solve discrete logarithm problems (DLP) in the Jacobian of a curve C_0 defined over the d degree extension field k_d of k:=GF(q) by mapping it to the DLP in the Jacobian of ...
The GHS attack is known as a method to map the discrete logarithm problem(DLP) in the Jacobian of a curve C_{0} defined over the d degree extension k_{d} of a finite field k to the DLP in the Jacobian...

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