Topic: manifold-optimization Goto Github
Some thing interesting about manifold-optimization
Some thing interesting about manifold-optimization
manifold-optimization,Latent Space Geometry for Neural Networks in Python
User: ae-bii
Home Page: https://ae-bii.github.io/neural-geometry/
manifold-optimization,Self-Paced Multi-Label Learning with Diversity
User: amjadseyedi
manifold-optimization,The code for vector transport free LBFGS quasi-Newton's optimization on the Riemannian manifolds
User: bghojogh
Home Page: https://proceedings.mlr.press/v157/godaz21a.html
manifold-optimization,Manifold Optimization
User: christophorusx
manifold-optimization,Coding parts of the exercises in N. Boumal's lecture "optimization on manifolds"
User: g20090279
Home Page: https://www.nicolasboumal.net/book/index.html
manifold-optimization,We present a framework called TLF that builds a classifier for the target domain having only few labeled training records by transferring knowledge from the source domain having many labeled records. While existing methods often focus on one issue and leave the other one for the further work, TLF is capable of handling both issues simultaneously. In TLF, we alleviate feature discrepancy by identifying shared label distributions that act as the pivots to bridge the domains. We handle distribution divergence by simultaneously optimizing the structural risk functional, joint distributions between domains, and the manifold consistency underlying marginal distributions. Moreover, for the manifold consistency we exploit its intrinsic properties by identifying $k$ nearest neighbors of a record, where the value of k is determined automatically in TLF. Furthermore, since negative transfer is not desired, we consider only the source records that are belonging to the source pivots during the knowledge transfer. We evaluate TLF on seven publicly available natural datasets and compare the performance of TLF against the performance of eleven state-of-the-art techniques. We also evaluate the effectiveness of TLF in some challenging situations. Our experimental results, including statistical sign test and Nemenyi test analyses, indicate a clear superiority of the proposed framework over the state-of-the-art techniques.
User: grahman20
Home Page: https://csusap.csu.edu.au/~grahman/
manifold-optimization,A MATLAB toolbox for classifier: Version 1.0.7
User: hiroyuki-kasai
manifold-optimization,Optimization algorithms for hybrid precoding in mmWave MIMO systems: Version 1.1.0
User: hiroyuki-kasai
manifold-optimization,A nonlinear least square(NLLS) solver. Fomulate the NLLS as graph optimization.
User: hitdshu
manifold-optimization,A comprehensive code for AI & Robotics.
User: kanishknavale
manifold-optimization,Constrained optimization toolkit for PyTorch
User: lezcano
Home Page: https://geotorch.readthedocs.io
manifold-optimization,A manifold optimization library for deep learning
Organization: mctorch
manifold-optimization,Implementing the algorithms of Kim et al. 2014 for regressing multiple symmetric positive definite matrices against real valued covariates.
User: mrparker909
manifold-optimization,quantum information toolbox
Organization: numqi
Home Page: https://numqi.github.io/numqi/
manifold-optimization,minimum bipartite matching via Riemann optimization
User: ocramz
manifold-optimization,Riemmanian Manifold representation library with automatic first order differentiation
User: rafaelrojasmiliani
manifold-optimization,Automatically adjust a set of formula-constrained variables
User: wangnianyi2001
manifold-optimization,Some knowledge about manifolds :atom:
User: wudangt
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