SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 2851–2900 of 3304 papers

TitleStatusHype
bigMap: Big Data Mapping with Parallelized t-SNE—0
Bi-Linear Modeling of Data Manifolds for Dynamic-MRI Recovery—0
Binary Matrix Factorisation via Column Generation—0
Binding constants of membrane-anchored receptors and ligands: a general theory corroborated by Monte Carlo simulations—0
Bit Cipher -- A Simple yet Powerful Word Representation System that Integrates Efficiently with Language Models—0
Black-Box k-to-1-PCA Reductions: Theory and Applications—0
Blind signal decomposition of various word embeddings based on join and individual variance explained—0
Block-diagonal covariance selection for high-dimensional Gaussian graphical models—0
Blockwise Principal Component Analysis for monotone missing data imputation and dimensionality reduction—0
Boarding for ISS: Imbalanced Self-Supervised: Discovery of a Scaled Autoencoder for Mixed Tabular Datasets—0
BOLIMES: Boruta and LIME optiMized fEature Selection for Gene Expression Classification—0
Book Review: Graph-Based Natural Language Processing and Information Retrieval by Rada Mihalcea and Dragomir Radev—0
Borel Isomorphic Dimensionality Reduction of Data and Supervised Learning—0
Bounded Manifold Completion—0
Bounds on Causal Effects and Application to High Dimensional Data—0
Brain Inspired Face Recognition: A Computational Framework—0
Bridging Autoencoders and Dynamic Mode Decomposition for Reduced-order Modeling and Control of PDEs—0
Bridging Classical and Quantum Machine Learning: Knowledge Transfer From Classical to Quantum Neural Networks Using Knowledge Distillation—0
Bridging Dense and Sparse Maximum Inner Product Search—0
Bridging Fairness and Environmental Sustainability in Natural Language Processing—0
Bringing Order to Chaos: A Non-Sequential Approach for Browsing Large Sets of Found Audio Data—0
Broadband Beamforming via Linear Embedding—0
Broadcast Product: Shape-aligned Element-wise Multiplication and Beyond—0
Building Models for Biopathway Dynamics Using Intrinsic Dimensionality Analysis—0
BYTECOVER2: TOWARDS DIMENSIONALITY REDUCTION OF LATENT EMBEDDING FOR EFFICIENT COVER SONG IDENTIFICATION—0
CAMEL: Curvature-Augmented Manifold Embedding and Learning—0
Can Genetic Programming Do Manifold Learning Too?—0
Canonical Correlation Analysis of Datasets with a Common Source Graph—0
Canonical Variates in Wasserstein Metric Space—0
Can the Problem-Solving Benefits of Quality Diversity Be Obtained Without Explicit Diversity Maintenance?—0
Capacity Analysis of Vector Symbolic Architectures—0
CA-PCA: Manifold Dimension Estimation, Adapted for Curvature—0
Capture Agent Free Biosensing using Porous Silicon Arrays and Machine Learning—0
Capturing Regional Variation with Distributed Place Representations and Geographic Retrofitting—0
Cardiomyopathy Diagnosis Model from Endomyocardial Biopsy Specimens: Appropriate Feature Space and Class Boundary in Small Sample Size Data—0
Cascaded Gaussian Processes for Data-efficient Robot Dynamics Learning—0
CASE -- Condition-Aware Sentence Embeddings for Conditional Semantic Textual Similarity Measurement—0
CASS: Cross Adversarial Source Separation via Autoencoder—0
Causal Deep Learning—0
Causal Feature Selection with Dimension Reduction for Interpretable Text Classification—0
Causal learning with sufficient statistics: an information bottleneck approach—0
CAVIAR: Categorical-Variable Embeddings for Accurate and Robust Inference—0
Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects—0
Cell2State: Learning Cell State Representations From Barcoded Single-Cell Gene-Expression Transitions—0
Channel Charting: Locating Users within the Radio Environment using Channel State Information—0
Chasing Collective Variables using Autoencoders and biased trajectories—0
Chiron: A Robust Recommendation System with Graph Regularizer—0
Circuit design in biology and machine learning. II. Anomaly detection—0
Circular Coordinate Methods with Generalized Penalty Functions—0
CitiusNLP at SemEval-2018 Task 10: The Use of Transparent Distributional Models and Salient Contexts to Discriminate Word Attributes—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