Zobrazeno 1 - 10
of 11 053
pro vyhledávání: '"Raghu, P."'
Autor:
Koeplinger, David, Gandhi, Darshan, Nandkar, Pushkar, Sheeley, Nathan, Musaddiq, Matheen, Zhang, Leon, Goodbar, Reid, Shaffer, Matthew, Wang, Han, Wang, Angela, Wang, Mingran, Prabhakar, Raghu
Token generation speed is critical to power the next wave of AI inference applications. GPUs significantly underperform during token generation due to synchronization overheads at kernel boundaries, utilizing only 21% of their peak memory bandwidth.
Externí odkaz:
http://arxiv.org/abs/2410.23668
The importance of Reinforcement Learning from Human Feedback (RLHF) in aligning large language models (LLMs) with human values cannot be overstated. RLHF is a three-stage process that includes supervised fine-tuning (SFT), reward learning, and policy
Externí odkaz:
http://arxiv.org/abs/2410.15610
Medical task-oriented dialogue systems can assist doctors by collecting patient medical history, aiding in diagnosis, or guiding treatment selection, thereby reducing doctor burnout and expanding access to medical services. However, doctor-patient di
Externí odkaz:
http://arxiv.org/abs/2410.14204
Autor:
Lewin, Sylvia K., Yu, Josephine J., Frank, Corey E., Graf, David, Chen, Patrick, Ran, Sheng, Eo, Yun Suk, Paglione, Johnpierre, Raghu, S., Butch, Nicholas P.
We experimentally determine the bounds of the magnetic-field-induced superconducting and magnetic phases near the crystalline $b$ axis of uranium ditelluride (UTe$_2$). By measuring the magnetoresistance as a function of rotation angle and field stre
Externí odkaz:
http://arxiv.org/abs/2410.05137
Software Development Waste (SDW) is defined as any resource-consuming activity that does not add value to the client or the organization developing the software. SDW impacts the overall efficiency and productivity of a software project as the scale a
Externí odkaz:
http://arxiv.org/abs/2409.19107
Autor:
Becktepe, Jannis, Dierkes, Julian, Benjamins, Carolin, Mohan, Aditya, Salinas, David, Rajan, Raghu, Hutter, Frank, Hoos, Holger, Lindauer, Marius, Eimer, Theresa
Publikováno v:
17th European Workshop on Reinforcement Learning 2024
Hyperparameters are a critical factor in reliably training well-performing reinforcement learning (RL) agents. Unfortunately, developing and evaluating automated approaches for tuning such hyperparameters is both costly and time-consuming. As a resul
Externí odkaz:
http://arxiv.org/abs/2409.18827
The strange metal is a mysterious non-Fermi liquid which shows linear-in-$T$ resistivity behavior at finite temperatures, and, as found in recent experiment, vanishingly small shot noise in the linear-in-$T$ regime. Here, we investigate the shot nois
Externí odkaz:
http://arxiv.org/abs/2409.16398
Pattern recognition-based myoelectric control is traditionally trained with static or ramp contractions, but this fails to capture the dynamic nature of real-world movements. This study investigated the benefits of training classifiers with continuou
Externí odkaz:
http://arxiv.org/abs/2409.16015
Publikováno v:
Biomedical Signal Processing and Control, vol. 71, p. 103134, Jan. 2022
Despite continued efforts to improve classification accuracy, it has been reported that offline accuracy is a poor indicator of the usability of pattern recognition-based myoelectric control. One potential source of this disparity is the existence of
Externí odkaz:
http://arxiv.org/abs/2409.14172
Publikováno v:
S. T. P. Raghu, D. MacIsaac and E. Scheme, IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 12, pp. 6051-6061, Dec. 2023
Post-processing techniques have been shown to improve the quality of the decision stream generated by classifiers used in pattern-recognition-based myoelectric control. However, these techniques have largely been tested individually and on well-behav
Externí odkaz:
http://arxiv.org/abs/2409.14169