Zobrazeno 1 - 10
of 29 821
pro vyhledávání: '"Ghazi, A."'
Autor:
van Dreven, Jonne, Cheddad, Abbas, Alawadi, Sadi, Ghazi, Ahmad Nauman, Koussa, Jad Al, Vanhoudt, Dirk
District Heating (DH) systems are essential for energy-efficient urban heating. However, despite the advancements in automated fault detection and diagnosis (FDD), DH still faces challenges in operational faults that impact efficiency. This study int
Externí odkaz:
http://arxiv.org/abs/2408.14499
Autor:
Llambias, Sebastian Nørgaard, Machnio, Julia, Munk, Asbjørn, Ambsdorf, Jakob, Nielsen, Mads, Ghazi, Mostafa Mehdipour
Medical image analysis using deep learning frameworks has advanced healthcare by automating complex tasks, but many existing frameworks lack flexibility, modularity, and user-friendliness. To address these challenges, we introduce Yucca, an open-sour
Externí odkaz:
http://arxiv.org/abs/2407.19888
Generating high-quality synthetic data is crucial for addressing challenges in medical imaging, such as domain adaptation, data scarcity, and privacy concerns. Existing image quality metrics often rely on reference images, are tailored for group comp
Externí odkaz:
http://arxiv.org/abs/2407.14994
Autor:
Mehonic, Adnan, Ielmini, Daniele, Roy, Kaushik, Mutlu, Onur, Kvatinsky, Shahar, Serrano-Gotarredona, Teresa, Linares-Barranco, Bernabe, Spiga, Sabina, Savelev, Sergey, Balanov, Alexander G, Chawla, Nitin, Desoli, Giuseppe, Malavena, Gerardo, Compagnoni, Christian Monzio, Wang, Zhongrui, Yang, J Joshua, Syed, Ghazi Sarwat, Sebastian, Abu, Mikolajick, Thomas, Noheda, Beatriz, Slesazeck, Stefan, Dieny, Bernard, Tuo-Hung, Hou, Varri, Akhil, Bruckerhoff-Pluckelmann, Frank, Pernice, Wolfram, Zhang, Xixiang, Pazos, Sebastian, Lanza, Mario, Wiefels, Stefan, Dittmann, Regina, Ng, Wing H, Buckwell, Mark, Cox, Horatio RJ, Mannion, Daniel J, Kenyon, Anthony J, Lu, Yingming, Yang, Yuchao, Querlioz, Damien, Hutin, Louis, Vianello, Elisa, Chowdhury, Sayeed Shafayet, Mannocci, Piergiulio, Cai, Yimao, Sun, Zhong, Pedretti, Giacomo, Strachan, John Paul, Strukov, Dmitri, Gallo, Manuel Le, Ambrogio, Stefano, Valov, Ilia, Waser, Rainer
The roadmap is organized into several thematic sections, outlining current computing challenges, discussing the neuromorphic computing approach, analyzing mature and currently utilized technologies, providing an overview of emerging technologies, add
Externí odkaz:
http://arxiv.org/abs/2407.02353
We study the differentially private (DP) empirical risk minimization (ERM) problem under the semi-sensitive DP setting where only some features are sensitive. This generalizes the Label DP setting where only the label is sensitive. We give improved u
Externí odkaz:
http://arxiv.org/abs/2406.19040
Autor:
Gharsallah, Ghazi, Kaddoum, Georges
As wireless communication technology progresses towards the sixth generation (6G), high-frequency millimeter-wave (mmWave) communication has emerged as a promising candidate for enabling vehicular networks. It offers high data rates and low-latency c
Externí odkaz:
http://arxiv.org/abs/2407.15023
We study the problem of computing pairwise statistics, i.e., ones of the form $\binom{n}{2}^{-1} \sum_{i \ne j} f(x_i, x_j)$, where $x_i$ denotes the input to the $i$th user, with differential privacy (DP) in the local model. This formulation capture
Externí odkaz:
http://arxiv.org/abs/2406.16305
Autor:
Chua, Lynn, Ghazi, Badih, Huang, Yangsibo, Kamath, Pritish, Kumar, Ravi, Manurangsi, Pasin, Sinha, Amer, Xie, Chulin, Zhang, Chiyuan
Large language models (LLMs) are typically multilingual due to pretraining on diverse multilingual corpora. But can these models relate corresponding concepts across languages, effectively being crosslingual? This study evaluates six state-of-the-art
Externí odkaz:
http://arxiv.org/abs/2406.16135
Autor:
Chua, Lynn, Ghazi, Badih, Huang, Yangsibo, Kamath, Pritish, Kumar, Ravi, Liu, Daogao, Manurangsi, Pasin, Sinha, Amer, Zhang, Chiyuan
Large language models (LLMs) have emerged as powerful tools for tackling complex tasks across diverse domains, but they also raise privacy concerns when fine-tuned on sensitive data due to potential memorization. While differential privacy (DP) offer
Externí odkaz:
http://arxiv.org/abs/2406.14322
Autor:
Khan, Ghazi, Roth, Thomas E.
Superconducting qubits are one of the most mature platforms for quantum computing, but significant performance improvements are still needed. To improve the engineering of these systems, 3D full-wave computational electromagnetics analyses are increa
Externí odkaz:
http://arxiv.org/abs/2406.05473