Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Zerfos, P."'
Autor:
Wood, David, Lublinsky, Boris, Roytman, Alexy, Singh, Shivdeep, Adam, Constantin, Adebayo, Abdulhamid, An, Sungeun, Chang, Yuan Chi, Dang, Xuan-Hong, Desai, Nirmit, Dolfi, Michele, Emami-Gohari, Hajar, Eres, Revital, Goto, Takuya, Joshi, Dhiraj, Koyfman, Yan, Nassar, Mohammad, Patel, Hima, Selvam, Paramesvaran, Shah, Yousaf, Surendran, Saptha, Tsuzuku, Daiki, Zerfos, Petros, Daijavad, Shahrokh
Data preparation is the first and a very important step towards any Large Language Model (LLM) development. This paper introduces an easy-to-use, extensible, and scale-flexible open-source data preparation toolkit called Data Prep Kit (DPK). DPK is a
Externí odkaz:
http://arxiv.org/abs/2409.18164
Autor:
Mishra, Mayank, Stallone, Matt, Zhang, Gaoyuan, Shen, Yikang, Prasad, Aditya, Soria, Adriana Meza, Merler, Michele, Selvam, Parameswaran, Surendran, Saptha, Singh, Shivdeep, Sethi, Manish, Dang, Xuan-Hong, Li, Pengyuan, Wu, Kun-Lung, Zawad, Syed, Coleman, Andrew, White, Matthew, Lewis, Mark, Pavuluri, Raju, Koyfman, Yan, Lublinsky, Boris, de Bayser, Maximilien, Abdelaziz, Ibrahim, Basu, Kinjal, Agarwal, Mayank, Zhou, Yi, Johnson, Chris, Goyal, Aanchal, Patel, Hima, Shah, Yousaf, Zerfos, Petros, Ludwig, Heiko, Munawar, Asim, Crouse, Maxwell, Kapanipathi, Pavan, Salaria, Shweta, Calio, Bob, Wen, Sophia, Seelam, Seetharami, Belgodere, Brian, Fonseca, Carlos, Singhee, Amith, Desai, Nirmit, Cox, David D., Puri, Ruchir, Panda, Rameswar
Large Language Models (LLMs) trained on code are revolutionizing the software development process. Increasingly, code LLMs are being integrated into software development environments to improve the productivity of human programmers, and LLM-based age
Externí odkaz:
http://arxiv.org/abs/2405.04324
Time series forecasting presents a significant challenge, particularly when its accuracy relies on external data sources rather than solely on historical values. This issue is prevalent in the financial sector, where the future behavior of time serie
Externí odkaz:
http://arxiv.org/abs/2310.01232
Autor:
Shah, Syed Yousaf, Patel, Dhaval, Vu, Long, Dang, Xuan-Hong, Chen, Bei, Kirchner, Peter, Samulowitz, Horst, Wood, David, Bramble, Gregory, Gifford, Wesley M., Ganapavarapu, Giridhar, Vaculin, Roman, Zerfos, Petros
A large number of time series forecasting models including traditional statistical models, machine learning models and more recently deep learning have been proposed in the literature. However, choosing the right model along with good parameter value
Externí odkaz:
http://arxiv.org/abs/2102.12347
Multimodal analysis that uses numerical time series and textual corpora as input data sources is becoming a promising approach, especially in the financial industry. However, the main focus of such analysis has been on achieving high prediction accur
Externí odkaz:
http://arxiv.org/abs/1912.10858
seq2graph: Discovering Dynamic Dependencies from Multivariate Time Series with Multi-level Attention
Discovering temporal lagged and inter-dependencies in multivariate time series data is an important task. However, in many real-world applications, such as commercial cloud management, manufacturing predictive maintenance, and portfolios performance
Externí odkaz:
http://arxiv.org/abs/1812.04448
Akademický článek
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Publikováno v:
Paris
7th IEEE Int. Conference on Network and Service Management (CNSM 2011)
7th IEEE Int. Conference on Network and Service Management (CNSM 2011)
Sensor networks are used for applications in monitoring harsh environments including reconnaissance and surveillance of areas that may be inaccessible to humans. Such applications depend on reliable collection, distribution and delivery of informatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1032::c3aa50da386d0e8a3d96c1a79469ddf6
http://hdl.handle.net/10044/1/9681
http://hdl.handle.net/10044/1/9681
Kniha
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Akademický článek
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