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pro vyhledávání: '"Lawrence, Ramon"'
With the rapid evolution of Natural Language Processing (NLP), Large Language Models (LLMs) like ChatGPT have emerged as powerful tools capable of transforming various sectors. Their vast knowledge base and dynamic interaction capabilities represent
Externí odkaz:
http://arxiv.org/abs/2401.00052
Autor:
Carvalho, Ivan, Lawrence, Ramon
This work analyzes and parallelizes LearnedSort, the novel algorithm that sorts using machine learning models based on the cumulative distribution function. LearnedSort is analyzed under the lens of algorithms with predictions, and it is argued that
Externí odkaz:
http://arxiv.org/abs/2307.08637
Embedded devices collect and process significant amounts of data in a variety of applications including environmental monitoring, industrial automation and control, and other Internet of Things (IoT) applications. Storing data efficiently is critical
Externí odkaz:
http://arxiv.org/abs/2302.07800
Autor:
Currie, Matthew, Lawrence, Ramon
Digitization of historical records has produced a significant amount of data for analysis and interpretation. A critical challenge is the ability to relate historical information across different archives to allow for the data to be framed in the app
Externí odkaz:
http://arxiv.org/abs/2302.07784
In 2018, the City of Kelowna entered into a license agreement with Dropbike to operate a dockless bike-share pilot in and around the downtown core. The bikes were tracked by the user's cell phone GPS through the Dropbike app. The City's Active Transp
Externí odkaz:
http://arxiv.org/abs/2302.06715
Autor:
Nagpal, Ritayu, Long, Sam, Jahagirdar, Shahid, Liu, Weiwei, Fazackerley, Scott, Lawrence, Ramon, Singh, Amritpal
Tree fruit breeding is a long-term activity involving repeated measurements of various fruit quality traits on a large number of samples. These traits are traditionally measured by manually counting the fruits, weighing to indirectly measure the frui
Externí odkaz:
http://arxiv.org/abs/2302.06698
Publikováno v:
Proceedings of the 12th International Conference on Sensor Networks (SENSORNETS 2023), pages 23-31
Efficiently querying data on embedded sensor and IoT devices is challenging given the very limited memory and CPU resources. With the increasing volumes of collected data, it is critical to process, filter, and manipulate data on the edge devices whe
Externí odkaz:
http://arxiv.org/abs/2302.03085
Adaptive and sequential experiment design is a well-studied area in numerous domains. We survey and synthesize the work of the online statistical learning paradigm referred to as multi-armed bandits integrating the existing research as a resource for
Externí odkaz:
http://arxiv.org/abs/1510.00757
Publikováno v:
Journal Of Artificial Intelligence Research, Volume 39, pages 269-300, 2010
Real-time heuristic search algorithms satisfy a constant bound on the amount of planning per action, independent of problem size. As a result, they scale up well as problems become larger. This property would make them well suited for video games whe
Externí odkaz:
http://arxiv.org/abs/1401.3857
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