Zobrazeno 1 - 10
of 14 359
pro vyhledávání: '"A, Kazmi"'
Autor:
Smith, Trevor I., Kazmi, Mohammad A., Sarles III, Richard R., Sbrana, Joshua A., Soper, Cody W., Bendjilali, Nasrine
Previous work has shown that item response theory may be used to rank incorrect response options to multiple-choice items on commonly used assessments. This work has shown that, when the correct response to each item is specified, a nominal response
Externí odkaz:
http://arxiv.org/abs/2410.05231
Autor:
Asif, Muneeba, Kazmi, Mohammad Kumail, Rahman, Mohammad Ashiqur, Hasan, Syed Rafay, Homsi, Soamar
As edge computing and the Internet of Things (IoT) expand, horizontal collaboration (HC) emerges as a distributed data processing solution for resource-constrained devices. In particular, a convolutional neural network (CNN) model can be deployed on
Externí odkaz:
http://arxiv.org/abs/2409.17279
In this article, we consider p and hp least-squares spectral element methods for one-dimensional elliptic boundary layer problems. We derive stability estimates and design a numerical scheme based on minimizing the residuals in the sense of least squ
Externí odkaz:
http://arxiv.org/abs/2409.14426
A digital currency is money in a digital form. In this model, maintaining integrity of the supply is a core concern, therefore protections against double-spending are often at the heart of a secure digital money scheme. Quantum money exploits the qua
Externí odkaz:
http://arxiv.org/abs/2408.04563
Autor:
Hegre, Håvard, Vesco, Paola, Colaresi, Michael, Vestby, Jonas, Timlick, Alexa, Kazmi, Noorain Syed, Becker, Friederike, Binetti, Marco, Bodentien, Tobias, Bohne, Tobias, Brandt, Patrick T., Chadefaux, Thomas, Drauz, Simon, Dworschak, Christoph, D'Orazio, Vito, Fritz, Cornelius, Frank, Hannah, Gleditsch, Kristian Skrede, Häffner, Sonja, Hofer, Martin, Klebe, Finn L., Macis, Luca, Malaga, Alexandra, Mehrl, Marius, Metternich, Nils W., Mittermaier, Daniel, Muchlinski, David, Mueller, Hannes, Oswald, Christian, Pisano, Paola, Randahl, David, Rauh, Christopher, Rüter, Lotta, Schincariol, Thomas, Seimon, Benjamin, Siletti, Elena, Tagliapietra, Marco, Thornhill, Chandler, Vegelius, Johan, Walterskirchen, Julian
This draft article outlines a prediction challenge where the target is to forecast the number of fatalities in armed conflicts, in the form of the UCDP `best' estimates, aggregated to the VIEWS units of analysis. It presents the format of the contrib
Externí odkaz:
http://arxiv.org/abs/2407.11045
Deep learning models have gained increasing prominence in recent years in the field of solar pho-tovoltaic (PV) forecasting. One drawback of these models is that they require a lot of high-quality data to perform well. This is often infeasible in pra
Externí odkaz:
http://arxiv.org/abs/2405.14472
Publikováno v:
Energy Build. 2024;312: 114216
Advances in machine learning and increased computational power have driven progress in energy-related research. However, limited access to private energy data from buildings hinders traditional regression models relying on historical data. While gene
Externí odkaz:
http://arxiv.org/abs/2404.00525
Autor:
Weyn, Jonathan A., Kumar, Divya, Berman, Jeremy, Kazmi, Najeeb, Klocek, Sylwester, Luferenko, Pete, Thambiratnam, Kit
We present an operations-ready multi-model ensemble weather forecasting system which uses hybrid data-driven weather prediction models coupled with the European Centre for Medium-range Weather Forecasts (ECMWF) ocean model to predict global weather a
Externí odkaz:
http://arxiv.org/abs/2403.15598
Autor:
Kazmi, Mishaal, Lautraite, Hadrien, Akbari, Alireza, Tang, Qiaoyue, Soroco, Mauricio, Wang, Tao, Gambs, Sébastien, Lécuyer, Mathias
We present PANORAMIA, a privacy leakage measurement framework for machine learning models that relies on membership inference attacks using generated data as non-members. By relying on generated non-member data, PANORAMIA eliminates the common depend
Externí odkaz:
http://arxiv.org/abs/2402.09477
Autor:
Raussi, Petra, Kamsamrong, Jirapa, Paspatis, Alexandros, Heussen, Kai, Zerihun, Tesfaye Amare, Widl, Edmund, Andrén, Filip Pröstl, Kazmi, Jawad H, Strasser, Thomas I., Castro, Felipe, Pellegrino, Luigi
Smart energy systems comprise multiple domains like power, thermal, control, information, and communication technology, which increases the complexity of research and development studies. This expansion also requires larger and ever so complex experi
Externí odkaz:
http://arxiv.org/abs/2310.06451