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Numerous process integration techniques were proved to be highly effective for identifying and estimating potential energy savings in the industry. However, they require high time and effort to collect and analyse process data. As a result, they do not con ...
Analyzing and processing data that are siloed and dispersed among multiple distrustful stakeholders is difficult and can even become impossible when the data are sensitive or confidential. Current data-protection and privacy regulations highly restrict the ...
We describe a series of algorithms that efficiently implement Gaussian model-X knockoffs to control the false discovery rate on large-scale feature selection problems. Identifying the knockoff distribution requires solving a large-scale semidefinite progra ...
The exponential growth of wearable healthcare devices market is fostered by the internetof-things (IoT) era. Connected smart biosensors enable a decentralized healthcare thatdoes not constrain the user to be in a medical facility to get a real-time insight ...
In this paper, we resolve the complexity problem of spectral graph sparcification in dynamic streams up to polylogarithmic factors. Using a linear sketch we design a streaming algorithm that uses (O) over tilde (n) space, and with high probability, recover ...
Transformers have been proven a successful model for a variety of tasks in sequence modeling. However, computing the attention matrix, which is their key component, has quadratic complexity with respect to the sequence length, thus making them prohibitivel ...
We propose radiofrequency filters using solitons generated from Si3N4 microresonators. By leveraging inherent diverse solitons states, we show filter tunability achieved without the need for external pulse shaping, establishing an essential step towards re ...
Feistel Networks (FN) are now being used massively to encrypt credit card numbers through format-preserving encryption. In our work, we focus on FN with two branches, entirely unknown round functions, modular additions (or other group operations), and when ...
A novel manifold learning approach is presented to incorporate computationally efficient obstacle avoidance constraints in optimal control algorithms. The method presented provides a significant computational benefit by reducing the number of constraints r ...
We consider the problem of estimating the value of MAX-CUT in a graph in the streaming model of computation. At one extreme, there is a trivial 2-approximation for this problem that uses only O(log n) space, namely, count the number of edges and output hal ...