Why Google’s TurboQuant Algorithm is Disrupting the AI Memory Chip Market

Google's TurboQuant combines PolarQuant with Quantized Johnson-Lindenstrauss correction to shrink memory use, raising questions ...
Search Engine Land

Why creative, not bidding, is limiting PPC performance

For a long time, PPC performance conversations inside agencies have centered on bidding – manual versus automated, Target CPA versus Maximize Conversions, incrementality debates, budget pacing and ...
Frontiers

Estimating rice yield-related traits using machine learning models integrating hyperspectral and texture features

Rapidly estimating multiple trait indicators simultaneously, nondestructively, and with high precision is an important means of accurate diagnosis in modern phenomics. Increasing the accuracy of ...
ascopubs.org

Evaluating Dimensionality Reduction for Patient-Reported Outcome–Based Survival Modeling in Patients With Head and Neck Cancer

This study aims to improve survival modeling in head and neck cancer (HNC) by integrating patient-reported outcomes (PROs) using dimensionality reduction techniques. PROs capture symptom severity ...
C&EN

Clustering and Analyzing Ensembles of Residue Interaction Networks from Molecular Dynamics Simulations

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Network methods and molecular dynamics (MD) simulations have become essential tools ...
C&EN

EncoderMap III: A Dimensionality Reduction Package for Feature Exploration in Molecular Simulations

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. EncoderMap is a dimensionality reduction method that is tailored for the analysis of ...
Scientific Research Publishing

Allaoui, M., Kherfi, M.L. and Cheriet, A. (2020) Considerably Improving Clustering Algorithms Using UMAP Dimensionality Reduction Technique: A Comparative Study. In: Lecture ...

ABSTRACT: Bipolar disorder is a multifaceted psychiatric illness characterized by unpredictable mood episodes and highly variable treatment responses across individuals. Predicting response to ...
IEEE

An Enhanced Density Peak Clustering Algorithm With Dimensionality Reduction and Relative Density Normalization for High-Dimensional Duplicate Data

Abstract: Cluster analysis is a fundamental method for studying big data problems, as it groups samples based on shared features. In cluster analysis, a particular class of big data problems is ...
Frontiers

SuperTac - tactile data super-resolution via dimensionality reduction

The advancement of tactile sensing in robotics and prosthetics is constrained by the trade-off between spatial and temporal resolution in artificial tactile sensors. To address this limitation, we ...
ahajournals.org

Revisiting Abnormalities of Ventricular Depolarization: Redefining Phenotypes and Associated Outcomes Using Tree‐Based Dimensionality Reduction

Abnormal ventricular depolarization, evident as a broad QRS complex on an ECG, is traditionally categorized into left bundle‐branch block (LBBB) and right bundle‐branch block or nonspecific ...