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Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

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Papers

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Showing 3001–3050 of 3304 papers

TitleStatusHype
Factorization of Latent Variables in Distributional Semantic Models—0
Online Supervised Subspace Tracking—0
A Fuzzy Approach for Feature Evaluation and Dimensionality Reduction to Improve the Quality of Web Usage Mining Results—0
Topic Identification and Discovery on Text and Speech—0
Gaussian Mixture Models with Component Means Constrained in Pre-selected Subspaces—0
MultiView Diffusion Maps—0
Scalable Out-of-Sample Extension of Graph Embeddings Using Deep Neural Networks—0
Dimensionality Reduction of Collective Motion by Principal Manifolds—0
Identifying manifolds underlying group motion in Vicsek agents—0
Model-based SIR for dimension reduction—0
Dimension reduction for model-based clustering—0
Direct Estimation of the Derivative of Quadratic Mutual Information with Application in Supervised Dimension Reduction—0
Dimension Reduction with Non-degrading Generalization—0
Beyond Gauss: Image-Set Matching on the Riemannian Manifold of PDFs—0
Fast Robust PCA on Graphs—0
Online Censoring for Large-Scale Regressions with Application to Streaming Big Data—0
Dimensionality-reduced subspace clustering—0
A study of the classification of low-dimensional data with supervised manifold learning—0
Sparsity in Multivariate Extremes with Applications to Anomaly Detection—0
Extracting grid characteristics from spatially distributed place cell inputs using non-negative PCA—0
Adaptive Mixtures of Factor AnalyzersCode0
Optimal approximate matrix product in terms of stable rank—0
Early and Late Combinations of Criteria for Reranking Distributional Thesauri—0
New Transfer Learning Techniques for Disparate Label Sets—0
Feature Selection for Short Text Classification using Wavelet Packet Transform—0
Notes on Low-rank Matrix Factorization—0
Detecting single-trial EEG evoked potential using a wavelet domain linear mixed model: application to error potentials classification—0
Diagnosing ADHD from fMRI Scans Using Hidden Markov Models—0
Random Maxout Features—0
Spectral Representations for Convolutional Neural Networks—0
Isometric sketching of any set via the Restricted Isometry Property—0
Heteroscedastic Max-Min Distance Analysis—0
Vector Space Models for Scientific Document Summarization—0
USAAR-SHEFFIELD: Semantic Textual Similarity with Deep Regression and Machine Translation Evaluation Metrics—0
Projection Metric Learning on Grassmann Manifold With Application to Video Based Face Recognition—0
Non-Orthogonal Explicit Semantic Analysis—0
PRHLT: Combination of Deep Autoencoders with Classification and Regression Techniques for SemEval-2015 Task 11—0
Sufficient Forecasting Using Factor Models—0
Sequential Dimensionality Reduction for Extracting Localized Features—0
Using Dimension Reduction to Improve the Classification of High-dimensional Data—0
oASIS: Adaptive Column Sampling for Kernel Matrix Approximation—0
Bayesian Sparse Tucker Models for Dimension Reduction and Tensor CompletionCode0
Spike and Slab Gaussian Process Latent Variable Models—0
Trees Assembling Mann Whitney Approach for Detecting Genome-wide Joint Association among Low Marginal Effect loci—0
Self-Expressive Decompositions for Matrix Approximation and Clustering—0
Using PCA to Efficiently Represent State Spaces—0
High-Order Low-Rank Tensors for Semantic Role Labeling—0
NASARI: a Novel Approach to a Semantically-Aware Representation of Items—0
Robust Principal Component Analysis on Graphs—0
Effective Discriminative Feature Selection with Non-trivial Solutions—0
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All datasetsMCAEMNIST

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9—Unverified
2tSNEClassification Accuracy51.5—Unverified
3IVISClassification Accuracy46.6—Unverified
4UMAPClassification Accuracy41.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1—Unverified
2QSClassification Accuracy68—Unverified