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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 2426–2450 of 3304 papers

TitleStatusHype
Wavelet Based Dictionaries for Piecewise Dimensionality Reduction of ECG Signals—0
Weakly-correlated synapses promote dimension reduction in deep neural networks—0
Web image annotation by diffusion maps manifold learning algorithm—0
Weighted Low Rank Matrix Approximation and Acceleration—0
WeightScale: Interpreting Weight Change in Neural Networks—0
Weight Vector Tuning and Asymptotic Analysis of Binary Linear Classifiers—0
Wheat Crop Yield Prediction Using Deep LSTM Model—0
When Collaborative Filtering is not Collaborative: Unfairness of PCA for Recommendations—0
When Dimensionality Reduction Meets Graph (Drawing) Theory: Introducing a Common Framework, Challenges and Opportunities—0
Where do goals come from? A Generic Approach to Autonomous Goal-System Development—0
Why do similarity matching objectives lead to Hebbian/anti-Hebbian networks?—0
Why do universal adversarial attacks work on large language models?: Geometry might be the answer—0
Wireless Channel Charting: Theory, Practice, and Applications—0
Wireless Environment Information Sensing, Feature, Semantic, and Knowledge: Four Steps Towards 6G AI-Enabled Air Interface—0
Wireless Federated Learning with Limited Communication and Differential Privacy—0
Wisdom of the crowd from unsupervised dimension reduction—0
Word Embeddings as Features for Supervised Coreference Resolution—0
Word Embeddings through Hellinger PCA—0
Word Embedding Techniques for Classification of Star Ratings—0
Word, graph and manifold embedding from Markov processes—0
Word Sense Disambiguation using Diffusion Kernel PCA—0
Worst-Case Linear Discriminant Analysis—0
Worst-Case Linear Discriminant Analysis as Scalable Semidefinite Feasibility Problems—0
XPCA: Extending PCA for a Combination of Discrete and Continuous Variables—0
Xtreaming: an incremental multidimensional projection technique and its application to streaming data—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