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 2051–2100 of 3304 papers

TitleStatusHype
Implementation of the Principal Component Analysis onto High-Performance Computer Facilities for Hyperspectral Dimensionality Reduction: Results and Comparisons—0
Implementing NLPs in industrial process modeling: Addressing Categorical Variables—0
Implicit Sparse Code Hashing—0
Improved Dimensionality Reduction for Inverse Problems in Nuclear Fusion and High-Energy Astrophysics—0
Improved Dimensionality Reduction of various Datasets using Novel Multiplicative Factoring Principal Component Analysis (MPCA)—0
Improved Gaussian-Bernoulli Restricted Boltzmann Machines for UAV-Ground Communication Systems—0
Improved Regularity Model-based EDA for Many-objective Optimization—0
Improving Channel Charting using a Split Triplet Loss and an Inertial Regularizer—0
Improving Channel Charting with Representation-Constrained Autoencoders—0
Improving evaluation and optimization of MT systems against MEANT—0
Improving information retrieval through correspondence analysis instead of latent semantic analysis—0
Improving Lexical Semantics for Sentential Semantics: Modeling Selectional Preference and Similar Words in a Latent Variable Model—0
Improving Oral Cancer Outcomes Through Machine Learning and Dimensionality Reduction—0
Improving Problem Identification via Automated Log Clustering using Dimensionality Reduction—0
Improving Sparse Representation-Based Classification Using Local Principal Component Analysis—0
Improving the generalization of network based relative pose regression: dimension reduction as a regularizer—0
Improving the Projection of Global Structures in Data through Spanning Trees—0
Improving Triplet-Based Channel Charting on Distributed Massive MIMO Measurements—0
Imputation of Time-varying Edge Flows in Graphs by Multilinear Kernel Regression and Manifold Learning—0
IMU-based Modularized Wearable Device for Human Motion Classification—0
Incentives and co-evolution: Steering linear dynamical systems with noncooperative agents—0
Inceptive Event Time-Surfaces for Object Classification Using Neuromorphic Cameras—0
Incomplete Pivoted QR-based Dimensionality Reduction—0
Incremental Ensemble Gaussian Processes—0
Individualized Multilayer Tensor Learning with An Application in Imaging Analysis—0
Inductive Regularized Learning of Kernel Functions—0
Inference and Interference: The Role of Clipping, Pruning and Loss Landscapes in Differentially Private Stochastic Gradient Descent—0
Inference for Regression with Variables Generated by AI or Machine Learning—0
Influ\^encia de T\'ecnicas N\~ao-supervisionadas de Redu \~ao de Dimensionalidade para Organiza \~ao Flex\' de Documentos (The Unsupervised Dimensionality Reduction Weight on Flexible Document Organization)[In Portuguese]—0
InfoClus: Informative Clustering of High-dimensional Data Embeddings—0
Information loss from dimensionality reduction in 5D-Gaussian spectral data—0
Information Processing by Neuron Populations in the Central Nervous System: Mathematical Structure of Data and Operations—0
Information retrieval in single cell chromatin analysis using TF-IDF transformation methods—0
Information-Theoretic Bounds and Approximations in Neural Population Coding—0
Information Theoretic Feature Transformation Learning for Brain Interfaces—0
Information-Theoretic Representation Learning for Positive-Unlabeled Classification—0
Feature Clustering for Support Identification in Extreme Regions—0
Infrastructure-Assisted Collaborative Perception in Automated Valet Parking: A Safety Perspective—0
Injecting Wiktionary to improve token-level contextual representations using contrastive learning—0
Input Guided Multiple Deconstruction Single Reconstruction neural network models for Matrix Factorization—0
In search of the most efficient and memory-saving visualization of high dimensional data—0
An Empirical Study on Fault Detection and Root Cause Analysis of Indium Tin Oxide Electrodes by Processing S-parameter Patterns—0
InstanceBEV: Unifying Instance and BEV Representation for Global Modeling—0
Instance Space Analysis for the Car Sequencing Problem—0
Instance-wise Linearization of Neural Network for Model Interpretation—0
Integrating LEO Satellite and UAV Relaying via Reinforcement Learning for Non-Terrestrial Networks—0
Integrating LEO Satellites and Multi-UAV Reinforcement Learning for Hybrid FSO/RF Non-Terrestrial Networks—0
Integrating Random Effects in Variational Autoencoders for Dimensionality Reduction of Correlated Data—0
Integrative analysis reveals disrupted pathways regulated by microRNAs in cancer—0
Adaptive Weighted Multi-View Clustering—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