Pages that link to "Item:Q4816852"
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The following pages link to Laplacian Eigenmaps for Dimensionality Reduction and Data Representation (Q4816852):
Displaying 50 items.
- A note on Laplacian eigenmaps (Q615259) (← links)
- Noise reduction method for nonlinear signal based on maximum variance unfolding and its application to fault diagnosis (Q617244) (← links)
- Image feature optimization based on nonlinear dimensionality reduction (Q621450) (← links)
- Dependence of locally linear embedding on the regularization parameter (Q621734) (← links)
- Approximation of functions of few variables in high dimensions (Q623354) (← links)
- Randomized anisotropic transform for nonlinear dimensionality reduction (Q623745) (← links)
- Iterative denoising (Q626230) (← links)
- Graph spectra in computer science (Q627958) (← links)
- Supervised optimal locality preserving projection (Q645859) (← links)
- Locally discriminative topic modeling (Q645890) (← links)
- Graph optimization for dimensionality reduction with sparsity constraints (Q650966) (← links)
- Spectral clustering and the high-dimensional stochastic blockmodel (Q651016) (← links)
- A method for visual identification of small sample subgroups and potential biomarkers (Q652375) (← links)
- Solving eigenvalue problems on curved surfaces using the closest point method (Q655077) (← links)
- Trace ratio criterion based generalized discriminative learning for semi-supervised dimensionality reduction (Q663376) (← links)
- Laplacian spectral basis functions (Q668982) (← links)
- Unsupervised feature selection based on kernel Fisher discriminant analysis and regression learning (Q669319) (← links)
- From classifiers to discriminators: a nearest neighbor rule induced discriminant analysis (Q716369) (← links)
- Convergence of the point integral method for Laplace-Beltrami equation on point cloud (Q721962) (← links)
- Diffusion representations (Q723009) (← links)
- Approximating snowflake metrics by trees (Q723016) (← links)
- An effective discretization method for disposing high-dimensional data (Q726197) (← links)
- Sparsity preserving projections with applications to face recognition (Q733184) (← links)
- An estimate of mutual information that permits closed-form optimisation (Q742718) (← links)
- Isometric sliced inverse regression for nonlinear manifold learning (Q746295) (← links)
- A two-dimensional neighborhood preserving projection for appearance-based face recognition (Q763368) (← links)
- Kernel discriminant analysis for regression problems (Q763381) (← links)
- Theoretical guarantees for graph sparse coding (Q778037) (← links)
- Self-regularized fixed-rank representation for subspace segmentation (Q778387) (← links)
- Complex systems: features, similarity and connectivity (Q823211) (← links)
- Conceptual and empirical comparison of dimensionality reduction algorithms (PCA, KPCA, LDA, MDS, SVD, LLE, ISOMAP, LE, ICA, t-SNE) (Q826335) (← links)
- Natural graph wavelet packet dictionaries (Q829903) (← links)
- Topological analysis of syntactic structures (Q832728) (← links)
- Embedding tangent space extreme learning machine for EEG decoding in brain computer interface systems (Q832784) (← links)
- Geometry on probability spaces (Q843724) (← links)
- Translated Poisson mixture model for stratification learning (Q847468) (← links)
- Topology-invariant similarity of nonrigid shapes (Q847482) (← links)
- The spectrum of kernel random matrices (Q847627) (← links)
- Hermite learning with gradient data (Q848563) (← links)
- Robust kernel Isomap (Q856442) (← links)
- The Cauchy--Schwarz divergence and Parzen windowing: Connections to graph theory and Mercer kernels (Q860375) (← links)
- Graph embedding using tree edit-union (Q869016) (← links)
- Latent semantic analysis and Fiedler retrieval (Q869904) (← links)
- A new algorithm of non-Gaussian component analysis with radial kernel functions (Q878193) (← links)
- Learning Markov random walks for robust subspace clustering and estimation (Q889299) (← links)
- Trends in extreme learning machines: a review (Q889343) (← links)
- Agglomerative clustering via maximum incremental path integral (Q898059) (← links)
- Variable bandwidth diffusion kernels (Q900774) (← links)
- Low-rank bilinear classification: efficient convex optimization and extensions (Q901815) (← links)
- Generalized transfer subspace learning through low-rank constraint (Q903542) (← links)
