SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2851–2875 of 3304 papers

TitleStatusHype
Variational Koopman models: slow collective variables and molecular kinetics from short off-equilibrium simulations—0
Structured adaptive and random spinners for fast machine learning computations—0
Improving Covariance-Regularized Discriminant Analysis for EHR-based Predictive Analytics of Diseases—0
Probabilistic Dimensionality Reduction via Structure Learning—0
Towards K-means-friendly Spaces: Simultaneous Deep Learning and ClusteringCode1
A Harmonic Mean Linear Discriminant Analysis for Robust Image Classification—0
An Information Theoretic Feature Selection Framework for Big Data under Apache Spark—0
Towards a Theoretical Analysis of PCA for Heteroscedastic Data—0
Efficient L1-Norm Principal-Component Analysis via Bit Flipping—0
Using Non-invertible Data Transformations to Build Adversarial-Robust Neural Networks—0
Sequential Low-Rank Change Detection—0
Decoding dynamic brain patterns from evoked responses: A tutorial on multivariate pattern analysis applied to time-series neuroimaging data—0
The face-space duality hypothesis: a computational model—0
Multi-view Dimensionality Reduction for Dialect Identification of Arabic Broadcast Speech—0
ADAGIO: Fast Data-aware Near-Isometric Linear EmbeddingsCode0
Recursive nearest agglomeration (ReNA): fast clustering for approximation of structured signalsCode0
Supervised multiway factorizationCode0
Peacock Bundles: Bundle Coloring for Graphs with Globality-Locality Trade-off—0
Robust Discriminative Clustering with Sparse Regularizers—0
Constraint matrix factorization for space variant PSFs field restorationCode0
Large Scale Behavioral Analytics via Topical Interaction—0
Interacting with Massive Behavioral Data—0
Comparison among dimensionality reduction techniques based on Random Projection for cancer classification—0
Unsupervised Feature Selection Based on the Morisita Estimator of Intrinsic Dimension—0
Probabilistic Data Analysis with Probabilistic ProgrammingCode0
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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