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Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1651–1675 of 3304 papers

TitleStatusHype
Efficient and Robust Bayesian Selection of Hyperparameters in Dimension Reduction for Visualization—0
Efficient and Scalable Batch Bayesian Optimization Using K-Means—0
Bayesian tomography using polynomial chaos expansion and deep generative networks—0
Efficient Binary Embedding of Categorical Data using BinSketch—0
Efficient channel charting via phase-insensitive distance computation—0
Efficient Contextual Representation Learning Without Softmax Layer—0
Efficient Design of Hardware-Enabled Reservoir Computing in FPGAs—0
Efficient Estimation of the Central Mean Subspace via Smoothed Gradient Outer Products—0
Efficient Fair Principal Component Analysis—0
Efficient GPU implementation of randomized SVD and its applications—0
Efficient L1-Norm Principal-Component Analysis via Bit Flipping—0
Efficient Large-Scale Similarity Search Using Matrix Factorization—0
Efficient Large-Scale Urban Parking Prediction: Graph Coarsening Based on Real-Time Parking Service Capability—0
Efficient Learning and Planning with Compressed Predictive States—0
Efficiently Computing Similarities to Private Datasets—0
Efficient Malware Detection with Optimized Learning on High-Dimensional Features—0
Efficient Nearest Neighbor based Uncertainty Estimation for Natural Language Processing Tasks—0
Efficient NTK using Dimensionality Reduction—0
Efficient Optimization for Discriminative Latent Class Models—0
Efficient Principal Subspace Projection of Streaming Data Through Fast Similarity Matching—0
Efficient Quantum Convolutional Neural Networks for Image Classification: Overcoming Hardware Constraints—0
Efficient Sketching Algorithm for Sparse Binary Data—0
Efficient Sparse PCA via Block-Diagonalization—0
Efficient Tensor Contraction via Fast Count Sketch—0
Efficient Text Classification Using Tree-structured Multi-linear Principal Component Analysis—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