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 1601–1650 of 3304 papers

TitleStatusHype
Implicit Sparse Code Hashing—0
Improved Dimensionality Reduction for Inverse Problems in Nuclear Fusion and High-Energy Astrophysics—0
Building an Efficient Intrusion Detection System Based on Feature Selection and Ensemble Classifier—0
Improved Gaussian-Bernoulli Restricted Boltzmann Machines for UAV-Ground Communication Systems—0
Efficient and Scalable Batch Bayesian Optimization Using K-Means—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
Efficient and Robust Bayesian Selection of Hyperparameters in Dimension Reduction for Visualization—0
Improving Lexical Semantics for Sentential Semantics: Modeling Selectional Preference and Similar Words in a Latent Variable Model—0
Bounds on Causal Effects and Application to High Dimensional Data—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
Deep Manifold Computing and Visualization Using Elastic Locally Isometric Smoothness—0
Improving the generalization of network based relative pose regression: dimension reduction as a regularizer—0
A Comparative Study of Text Preprocessing Approaches for Topic Detection of User Utterances—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
Deep neural networks for the evaluation and design of photonic devices—0
A study of semantic augmentation of word embeddings for extractive summarization—0
Incremental Ensemble Gaussian Processes—0
Generalizing Correspondence Analysis for Applications in Machine Learning—0
Individualized Multilayer Tensor Learning with An Application in Imaging Analysis—0
Interpretability Beyond Classification Output: Semantic Bottleneck Networks—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
Deep Reinforcement Learning-Assisted Federated Learning for Robust Short-term Utility Demand Forecasting in Electricity Wholesale Markets—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
Deep topic modeling by multilayer bootstrap network and lasso—0
An Empirical Study on Fault Detection and Root Cause Analysis of Indium Tin Oxide Electrodes by Processing S-parameter Patterns—0
Interpretable and Efficient Data-driven Discovery and Control of Distributed Systems—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