Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Ghassemi, Farhad"'
Autor:
Zhang, Heidi C., Semnani, Sina J., Ghassemi, Farhad, Xu, Jialiang, Liu, Shicheng, Lam, Monica S.
We introduce SPAGHETTI: Semantic Parsing Augmented Generation for Hybrid English information from Text Tables and Infoboxes, a hybrid question-answering (QA) pipeline that utilizes information from heterogeneous knowledge sources, including knowledge
Externí odkaz:
http://arxiv.org/abs/2406.00562
Search Optimization with Query Likelihood Boosting and Two-Level Approximate Search for Edge Devices
Autor:
Zhang, Jianwei, Feng, Helian, He, Xin, Strimel, Grant P., Ghassemi, Farhad, Kebarighotbi, Ali
We present a novel search optimization solution for approximate nearest neighbor (ANN) search on resource-constrained edge devices. Traditional ANN approaches fall short in meeting the specific demands of real-world scenarios, e.g., skewed query like
Externí odkaz:
http://arxiv.org/abs/2312.07517
Autor:
Wang, Longshaokan, Wang, Lingda, Georgieva, Mina, Machado, Paulo, Ulagappa, Abinaya, Ahmed, Safwan, Lu, Yan, Bakshi, Arjun, Ghassemi, Farhad
Distribution forecast can quantify forecast uncertainty and provide various forecast scenarios with their corresponding estimated probabilities. Accurate distribution forecast is crucial for planning - for example when making production capacity or i
Externí odkaz:
http://arxiv.org/abs/2202.07955
Autor:
Madiman, Mokshay, Ghassemi, Farhad
Publikováno v:
IEEE Transactions on Information Theory, vol. 65, no. 3, pp. 1375-1386, March 2019
We initiate the study of the Stam region, defined as the subset of the positive orthant in $\mathbb{R}^{2^n-1}$ that arises from considering entropy powers of subset sums of $n$ independent random vectors in a Euclidean space of finite dimension. We
Externí odkaz:
http://arxiv.org/abs/1704.01177
Publikováno v:
Operations Research, 2015 Mar 01. 63(2), 353-362.
Externí odkaz:
http://www.jstor.org/stable/24540376
Akademický článek
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Autor:
Ghassemi, Farhad
In this dissertation, we explore several themes in sensor management with an emphasis on their applications for target localization and tracking. We consider the sensor subset selection problem where a pre-specified number of sensors must be selected
Externí odkaz:
http://hdl.handle.net/2429/9964
Autor:
Yassaei, Shahla, Ghassemi, Farhad
Publikováno v:
2015 International Conference on Industrial Engineering & Operations Management (IEOM); 2015, p1-11, 11p
Autor:
Ghassemi, Farhad
An indirect, self-calibrating, easy to install, and robust joint angle sensing method is presented in this thesis. The approach is based on the use of a pair of accelerometers placed on each link near the joint axis. Two different methods are describ
Externí odkaz:
http://hdl.handle.net/2429/11729
Akademický článek
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