Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Armin Askari"'
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-11 (2023)
Abstract Recent large language models (LLMs), such as ChatGPT, have demonstrated remarkable prediction performance for a growing array of tasks. However, their proliferation into high-stakes domains and compute-limited settings has created a burgeoni
Externí odkaz:
https://doaj.org/article/13ca7afc0ee54abaaa0a5d434f1c0e11
Publikováno v:
Mathematics of Operations Research.
Because of its linear complexity, naive Bayes classification remains an attractive supervised learning method, especially in very large-scale settings. We propose a sparse version of naive Bayes, which can be used for feature selection. This leads to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2126c7845d7e137ee813e4f3cfe7c110
https://doi.org/10.1287/moor.2023.1356
https://doi.org/10.1287/moor.2023.1356
Publikováno v:
SIAM Journal on Mathematics of Data Science. 3:833-853
We describe a series of algorithms that efficiently implement Gaussian model-X knockoffs to control the false discovery rate on large scale feature selection problems. Identifying the knockoff distribution requires solving a large scale semidefinite
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1832700545765924a863add4976e0193
https://doi.org/10.1137/20m1363698
https://doi.org/10.1137/20m1363698
Publikováno v:
SIAM Journal on Mathematics of Data Science
SIAM Journal on Mathematics of Data Science, 2022, 4 (2), pp.514-530. ⟨10.1137/21M1398677⟩
SIAM Journal on Mathematics of Data Science, 2022, 4 (2), pp.514-530. ⟨10.1137/21M1398677⟩
International audience; We show that sparsity constrained optimization problems over low dimensional spaces tend to have a small duality gap. We use the Shapley-Folkman theorem to derive both data-driven bounds on the duality gap, and an efficient pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bcf60cf0c3b18a480423b961f67a8a99
Implicit deep learning prediction rules generalize the recursive rules of feedforward neural networks. Such rules are based on the solution of a fixed-point equation involving a single vector of hidden features, which is thus only implicitly defined.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::be177822288399f4515b3ac86db2904f
http://arxiv.org/abs/1908.06315
http://arxiv.org/abs/1908.06315
Publikováno v:
Intelligent Vehicles Symposium
The paper evaluates the influence of the maximum vehicle acceleration and variable proportions of ACC/CACC vehicles on the throughput of an intersection. Two cases are studied: (1) free road downstream of the intersection; and (2) red light at some d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::61622e3bcd79e01462285d1e92e907b3