Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Alaa Maalouf"'
Publikováno v:
Sensors, Vol 21, Iss 19, p 6689 (2021)
Coreset is usually a small weighted subset of an input set of items, that provably approximates their loss function for a given set of queries (models, classifiers, hypothesis). That is, the maximum (worst-case) error over all queries is bounded. To
Externí odkaz:
https://doaj.org/article/26bcef9252b0428280e372df224f3a98
Publikováno v:
Sensors, Vol 21, Iss 16, p 5599 (2021)
A common technique for compressing a neural network is to compute the k-rank ℓ2 approximation Ak of the matrix A∈Rn×d via SVD that corresponds to a fully connected layer (or embedding layer). Here, d is the number of input neurons in the layer,
Externí odkaz:
https://doaj.org/article/18b56702a14f476393df979512e7125a
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 44:9977-9994
Least-mean-squares (LMS) solvers such as Linear / Ridge-Regression and SVD not only solve fundamental machine learning problems, but are also the building blocks in a variety of other methods, such as matrix factorizations. We suggest an algorithm th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab57da2f5950664809b04fcde1dcf723
https://doi.org/10.1109/tpami.2021.3139612
https://doi.org/10.1109/tpami.2021.3139612
Publikováno v:
IEEE transactions on neural networks and learning systems.
Coreset of a given dataset and loss function is usually a small weighed set that approximates this loss for every query from a given set of queries. Coresets have shown to be very useful in many applications. However, coresets construction is done in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d36bd77dc04db3dc9715337de56376c
https://pubmed.ncbi.nlm.nih.gov/36343002
https://pubmed.ncbi.nlm.nih.gov/36343002
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision (ICCV).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::59d54db98d6f8cf6904610e7b7c53ce5
https://doi.org/10.1109/iccv48922.2021.01302
https://doi.org/10.1109/iccv48922.2021.01302
Publikováno v:
WIREs Data Mining and Knowledge Discovery. 11
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2f1b7c33bc658e9973889d87d6d2511
https://doi.org/10.1002/widm.1429
https://doi.org/10.1002/widm.1429
Publikováno v:
Sensors
Volume 21
Issue 16
Sensors (Basel, Switzerland)
Sensors, Vol 21, Iss 5599, p 5599 (2021)
Volume 21
Issue 16
Sensors (Basel, Switzerland)
Sensors, Vol 21, Iss 5599, p 5599 (2021)
A common technique for compressing a neural network is to compute the k-rank ℓ2 approximation Ak of the matrix A∈Rn×d via SVD that corresponds to a fully connected layer (or embedding layer). Here, d is the number of input neurons in the layer,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06c3752290c7e9ad8c06645a96243da2
Publikováno v:
KDD
An $\varepsilon$-coreset for Least-Mean-Squares (LMS) of a matrix $A\in{\mathbb{R}}^{n\times d}$ is a small weighted subset of its rows that approximates the sum of squared distances from its rows to every affine $k$-dimensional subspace of ${\mathbb
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::95b2611431de712900e126ce68364026
https://doi.org/10.1145/3394486.3403256
https://doi.org/10.1145/3394486.3403256