Zobrazeno 1 - 10
of 28 845
pro vyhledávání: '"P SATISH"'
The holy grail of machine learning is to enable Continual Federated Learning (CFL) to enhance the efficiency, privacy, and scalability of AI systems while learning from streaming data. The primary challenge of a CFL system is to overcome global catas
Externí odkaz:
http://arxiv.org/abs/2411.07959
Autor:
Gotavade, Tejas Satish
This research introduces an innovative artificial intelligence-driven educational concept designed to optimize self-directed learning through personalized course delivery and automated teaching assistance. The system leverages fine-tuned AI models to
Externí odkaz:
http://arxiv.org/abs/2411.07300
Autor:
Desai, Akshar Prabhu, Mallya, Ganesh Satish, Luqman, Mohammad, Ravi, Tejasvi, Kota, Nithya, Yadav, Pranjul
Gen-AI techniques are able to improve understanding of context and nuances in language modeling, translation between languages, handle large volumes of data, provide fast, low-latency responses and can be fine-tuned for various tasks and domains. In
Externí odkaz:
http://arxiv.org/abs/2410.15653
Autor:
Bordin, Matteo, Lacava, Andrea, Polese, Michele, Satish, Sai, Nittoor, Manoj AnanthaSwamy, Sivaraj, Rajarajan, Cuomo, Francesca, Melodia, Tommaso
Next-generation wireless systems, already widely deployed, are expected to become even more prevalent in the future, representing challenges in both environmental and economic terms. This paper focuses on improving the energy efficiency of intelligen
Externí odkaz:
http://arxiv.org/abs/2410.14021
Autor:
Galib, Shaikat, Wang, Shanshan, Xu, Guanshuo, Pfeiffer, Pascal, Chesler, Ryan, Landry, Mark, Ambati, Sri Satish
Smaller vision-language models (VLMs) are becoming increasingly important for privacy-focused, on-device applications due to their ability to run efficiently on consumer hardware for processing enterprise commercial documents and images. These models
Externí odkaz:
http://arxiv.org/abs/2410.13611
Autor:
Paradis, Elise, Grey, Kate, Madison, Quinn, Nam, Daye, Macvean, Andrew, Meimand, Vahid, Zhang, Nan, Ferrari-Church, Ben, Chandra, Satish
How much does AI assistance impact developer productivity? To date, the software engineering literature has provided a range of answers, targeting a diversity of outcomes: from perceived productivity to speed on task and developer throughput. Our ran
Externí odkaz:
http://arxiv.org/abs/2410.12944
Trusted hardware's freshness guarantee ensures that an adversary cannot replay an old value in response to a memory read request. They rely on maintaining a version number for each cache block and ensuring their integrity using a Merkle tree. However
Externí odkaz:
http://arxiv.org/abs/2410.12749
Sparse system identification of nonlinear dynamic systems is still challenging, especially for stiff and high-order differential equations for noisy measurement data. The use of highly correlated functions makes distinguishing between true and false
Externí odkaz:
http://arxiv.org/abs/2410.10023
Tourism Recommender Systems (TRS) have traditionally focused on providing personalized travel suggestions, often prioritizing user preferences without considering broader sustainability goals. Integrating sustainability into TRS has become essential
Externí odkaz:
http://arxiv.org/abs/2409.18003
This paper uses topic modeling and bias measurement techniques to analyze and determine gender bias in English song lyrics. We utilize BERTopic to cluster 537,553 English songs into distinct topics and chart their development over time. Our analysis
Externí odkaz:
http://arxiv.org/abs/2409.15949