Zobrazeno 1 - 10
of 534
pro vyhledávání: '"Kaleem, Muhammad"'
Autor:
Zhang, Weize, Elmahgiubi, Mohammed, Rezaee, Kasra, Khamidehi, Behzad, Mirkhani, Hamidreza, Arasteh, Fazel, Li, Chunlin, Kaleem, Muhammad Ahsan, Corral-Soto, Eduardo R., Sharma, Dhruv, Cao, Tongtong
In this paper we present the architecture of the Kyber-E2E submission to the map track of CARLA Leaderboard 2.0 Autonomous Driving (AD) challenge 2023, which achieved first place. We employed a modular architecture for our solution consists of five m
Externí odkaz:
http://arxiv.org/abs/2405.01394
This paper investigates adaptive streaming codes over a three-node relayed network. In this setting, a source transmits a sequence of message packets through a relay under a delay constraint of $T$ time slots per packet. The source-to-relay and relay
Externí odkaz:
http://arxiv.org/abs/2401.15056
Autor:
Wang, Wenhao, Kaleem, Muhammad Ahmad, Dziedzic, Adam, Backes, Michael, Papernot, Nicolas, Boenisch, Franziska
Self-supervised learning (SSL) has recently received significant attention due to its ability to train high-performance encoders purely on unlabeled data-often scraped from the internet. This data can still be sensitive and empirical evidence suggest
Externí odkaz:
http://arxiv.org/abs/2401.12233
Autor:
Franzese, Olive, Dziedzic, Adam, Choquette-Choo, Christopher A., Thomas, Mark R., Kaleem, Muhammad Ahmad, Rabanser, Stephan, Fang, Congyu, Jha, Somesh, Papernot, Nicolas, Wang, Xiao
Collaborative machine learning (ML) is widely used to enable institutions to learn better models from distributed data. While collaborative approaches to learning intuitively protect user data, they remain vulnerable to either the server, the clients
Externí odkaz:
http://arxiv.org/abs/2310.16678
Autor:
Dziedzic, Adam, Choquette-Choo, Christopher A, Dullerud, Natalie, Suriyakumar, Vinith Menon, Shamsabadi, Ali Shahin, Kaleem, Muhammad Ahmad, Jha, Somesh, Papernot, Nicolas, Wang, Xiao
Private multi-winner voting is the task of revealing $k$-hot binary vectors satisfying a bounded differential privacy (DP) guarantee. This task has been understudied in machine learning literature despite its prevalence in many domains such as health
Externí odkaz:
http://arxiv.org/abs/2211.15410
Autor:
Dziedzic, Adam, Duan, Haonan, Kaleem, Muhammad Ahmad, Dhawan, Nikita, Guan, Jonas, Cattan, Yannis, Boenisch, Franziska, Papernot, Nicolas
Self-supervised models are increasingly prevalent in machine learning (ML) since they reduce the need for expensively labeled data. Because of their versatility in downstream applications, they are increasingly used as a service exposed via public AP
Externí odkaz:
http://arxiv.org/abs/2209.09024
Self-Supervised Learning (SSL) is an increasingly popular ML paradigm that trains models to transform complex inputs into representations without relying on explicit labels. These representations encode similarity structures that enable efficient lea
Externí odkaz:
http://arxiv.org/abs/2205.07890
Autor:
Kaleem, Muhammad
La biohydrogénation (BH) ruminale des acides gras polyinsaturés (AGPI) est à l’origine de la production d’AG trans pouvant se retrouver dans les productions de ruminants, dont le lait. Parmi ceux-ci, les isomères t11 auraient des effets bén
Externí odkaz:
http://oatao.univ-toulouse.fr/10706/1/Kaleem.pdf
Publikováno v:
In Land Use Policy September 2024 144
Autor:
Safdar, Muhammad, Kaleem, Muhammad, Duarte, Phelipe Magalhães, Tazerji, Sina Salajegheh, Ozaslan, Mehmet, Hassanpour, Shahin, Rath, Jayadev, Priyadarsini, Swagatika, Rizwan, Muhammad Arif
Publikováno v:
In Ecological Genetics and Genomics September 2024 32