Zobrazeno 1 - 10
of 26 862
pro vyhledávání: '"Norm (mathematics)"'
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 33:7717-7727
Most modern learning problems are highly overparameterized, i.e., have many more model parameters than the number of training data points. As a result, the training loss may have infinitely many global minima (parameter vectors that perfectly ``inter
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 44:8992-9010
Low-rank plus sparse matrix decomposition (LSD) is an important problem in computer vision and machine learning. It has been solved using convex relaxations of the matrix rank and l0-pseudo-norm, which are the nuclear norm and l1-norm, respectively.
Autor:
Sergei Kalmykov, Leonid V. Kovalev
Publikováno v:
Proceedings of the American Mathematical Society. 151:547-554
We extend Quine's bound on the number of self-intersection of curves with polynomial parameterization to the case of Laurent polynomials. As an application, we show that circle embeddings are dense among all maps from a circle to a plane with respect
Publikováno v:
IEEE Transactions on Cybernetics. 52:11794-11804
This article identifies a new upper bound norm for the intervalized interconnection matrices pertaining to delayed dynamical neural networks under the parameter uncertainties. By formulating the appropriate Lyapunov functional and slope-bounded activ
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 33:5775-5788
A recommender system (RS) is highly efficient in filtering people's desired information from high-dimensional and sparse (HiDS) data. To date, a latent factor (LF)-based approach becomes highly popular when implementing a RS. However, current LF mode
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 34:4572-4585
A dilemma faced by classification is that the data is not collected at the same frequency in some applications. We investigate the mixed frequency data in a new way and recognize them as a special style of multi-view data, in which each view data is
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 34:4812-4825
Inspired by the mean calculation of RPCA_OM and inductiveness of IRPCA, we first propose an inductive robust principal component analysis method with removing the optimal mean automatically, which is shorted as IRPCA_OM. Furthermore, IRPCA_OM is exte
Autor:
Pan Shang, Lingchen Kong
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 44:6254-6263
lsub1/sub-norm quantile regression is a common choice if there exists outlier or heavy-tailed error in high-dimensional data sets. However, it is computationally expensive to solve this problem when the feature size of data is ultra high. As far as w
Constrained Autoencoder-Based Pulse Compressed Thermal Wave Imaging for Sub-Surface Defect Detection
Publikováno v:
IEEE Sensors Journal. 22:17335-17342
Non-destructive testing & evaluation techniques play an essential role in ensuring safety of materials in operation at various industry sectors. Pulse compressed favourable thermal wave imaging is one of the widely used non-destructive testing techni
Autor:
Ittay Weiss, Derek Scott Cook
Publikováno v:
Fuzzy Sets and Systems. 444:79-102
It is well known that metric spaces are an instance of categorical enrichment in a particular quantale. We show that in a categorically natural way a notion of Lipschitz norm arises in the context of an arbitrary diagram of quantales, instead of just