Zobrazeno 1 - 5
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pro vyhledávání: '"Yaldiz, Duygu Nur"'
Autor:
Mushtaq, Erum, Yaldiz, Duygu Nur, Bakman, Yavuz Faruk, Ding, Jie, Tao, Chenyang, Dimitriadis, Dimitrios, Avestimehr, Salman
Continual self-supervised learning (CSSL) learns a series of tasks sequentially on the unlabeled data. Two main challenges of continual learning are catastrophic forgetting and task confusion. While CSSL problem has been studied to address the catast
Externí odkaz:
http://arxiv.org/abs/2407.12188
Autor:
Yaldiz, Duygu Nur, Bakman, Yavuz Faruk, Buyukates, Baturalp, Tao, Chenyang, Ramakrishna, Anil, Dimitriadis, Dimitrios, Zhao, Jieyu, Avestimehr, Salman
Uncertainty estimation (UE) of generative large language models (LLMs) is crucial for evaluating the reliability of generated sequences. A significant subset of UE methods utilize token probabilities to assess uncertainty, aggregating multiple token
Externí odkaz:
http://arxiv.org/abs/2406.11278
Autor:
Bakman, Yavuz Faruk, Yaldiz, Duygu Nur, Buyukates, Baturalp, Tao, Chenyang, Dimitriadis, Dimitrios, Avestimehr, Salman
Generative Large Language Models (LLMs) are widely utilized for their excellence in various tasks. However, their tendency to produce inaccurate or misleading outputs poses a potential risk, particularly in high-stakes environments. Therefore, estima
Externí odkaz:
http://arxiv.org/abs/2402.11756
Federated Learning (FL) has gained significant attraction due to its ability to enable privacy-preserving training over decentralized data. Current literature in FL mostly focuses on single-task learning. However, over time, new tasks may appear in t
Externí odkaz:
http://arxiv.org/abs/2309.01289
Publikováno v:
ICLR 2023 Workshop on Backdoor Attacks and Defenses in Machine Learning
Given the distributed nature, detecting and defending against the backdoor attack under federated learning (FL) systems is challenging. In this paper, we observe that the cosine similarity of the last layer's weight between the global model and each
Externí odkaz:
http://arxiv.org/abs/2304.00160