Zobrazeno 1 - 10
of 15 706
pro vyhledávání: '"Sima, P"'
Conformal prediction (CP) is a distribution-free framework for achieving probabilistic guarantees on black-box models. CP is generally applied to a model post-training. Recent research efforts, on the other hand, have focused on optimizing CP efficie
Externí odkaz:
http://arxiv.org/abs/2411.01696
Data deduplication, one of the key features of modern Big Data storage devices, is the process of removing replicas of data chunks stored by different users. Despite the importance of deduplication, several drawbacks of the method, such as storage ro
Externí odkaz:
http://arxiv.org/abs/2411.01407
Autor:
Emonet, Vincent, Bolleman, Jerven, Duvaud, Severine, de Farias, Tarcisio Mendes, Sima, Ana Claudia
We introduce a Retrieval-Augmented Generation (RAG) system for translating user questions into accurate federated SPARQL queries over bioinformatics knowledge graphs (KGs) leveraging Large Language Models (LLMs). To enhance accuracy and reduce halluc
Externí odkaz:
http://arxiv.org/abs/2410.06062
Autor:
Bolleman, Jerven, Emonet, Vincent, Altenhoff, Adrian, Bairoch, Amos, Blatter, Marie-Claude, Bridge, Alan, Duvaud, Severine, Gasteiger, Elisabeth, Kuznetsov, Dmitry, Moretti, Sebastien, Michel, Pierre-Andre, Morgat, Anne, Pagni, Marco, Redaschi, Nicole, Zahn-Zabal, Monique, de Farias, Tarcisio Mendes, Sima, Ana Claudia
Background. In the last decades, several life science resources have structured data using the same framework and made these accessible using the same query language to facilitate interoperability. Knowledge graphs have seen increased adoption in bio
Externí odkaz:
http://arxiv.org/abs/2410.06010
End-effector based assistive robots face persistent challenges in generating smooth and robust trajectories when controlled by human's noisy and unreliable biosignals such as muscle activities and brainwaves. The produced endpoint trajectories are of
Externí odkaz:
http://arxiv.org/abs/2410.03486
Autor:
Bahrani, Sima, Oliveira, Romerson D., Parra-Ullauri, Juan Marcelo, Wang, Rui, Simeonidou, Dimitra
Distributed quantum computing (DQC) has emerged as a promising approach to overcome the scalability limitations of monolithic quantum processors in terms of computing capability. However, realising the full potential of DQC requires effective resourc
Externí odkaz:
http://arxiv.org/abs/2409.12675
Autor:
Ding, Kairui, Chen, Boyuan, Su, Yuchen, Gao, Huan-ang, Jin, Bu, Sima, Chonghao, Zhang, Wuqiang, Li, Xiaohui, Barsch, Paul, Li, Hongyang, Zhao, Hao
End-to-end architectures in autonomous driving (AD) face a significant challenge in interpretability, impeding human-AI trust. Human-friendly natural language has been explored for tasks such as driving explanation and 3D captioning. However, previou
Externí odkaz:
http://arxiv.org/abs/2409.06702
Rank aggregation combines multiple ranked lists into a consensus ranking. In fields like biomedical data sharing, rankings may be distributed and require privacy. This motivates the need for federated rank aggregation protocols, which support distrib
Externí odkaz:
http://arxiv.org/abs/2409.00848
Autor:
Fortulan, Raphael, Li, Suwei, Reece, Michael John, Serhiienko, Illia, Mori, Takao, Yamini, Sima Aminorroya
There is evidence that magnetism can potentially increase the thermopower of materials, most likely due to magnon scattering, suggesting the incorporation of intrinsic magnetic semiconductors in non-magnetic thermoelectric materials. Here, samples of
Externí odkaz:
http://arxiv.org/abs/2408.15704
Reward shaping is effective in addressing the sparse-reward challenge in reinforcement learning by providing immediate feedback through auxiliary informative rewards. Based on the reward shaping strategy, we propose a novel multi-task reinforcement l
Externí odkaz:
http://arxiv.org/abs/2408.10858