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Diversity

Diversity in data sampling is crucial across various use cases, including search, recommendation systems, and more. Ensuring diverse samples means capturing a wide range of variations and perspectives, which leads to more robust, unbiased, and comprehensive models. In search use cases, for instance, diversity helps avoid redundancy, ensuring that users are exposed to a broader set of relevant information rather than repeated similar results.

Papers

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Showing 5676–5700 of 9051 papers

TitleStatusHype
Modulating transfer between tasks in gradient-based meta-learning—0
MOEA/D with Angle-based Constrained Dominance Principle for Constrained Multi-objective Optimization Problems—0
MoEController: Instruction-based Arbitrary Image Manipulation with Mixture-of-Expert Controllers—0
Transmitter Diversity with Beam Steering—0
A trust-based recommendation method using network diffusion processes—0
MoFusion: A Framework for Denoising-Diffusion-based Motion Synthesis—0
MolCAP: Molecular Chemical reActivity pretraining and prompted-finetuning enhanced molecular representation learning—0
Molecular Diversity and Network Complexity in Growing Protocells—0
A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes—0
Molecular Structure Extraction From Documents Using Deep Learning—0
Molecule Optimization by Explainable Evolution—0
A tool for computing diversity and consideration on differences between diversity indices—0
MoMa: A Modular Deep Learning Framework for Material Property Prediction—0
MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images—0
Trap of Feature Diversity in the Learning of MLPs—0
Bugs as Features (Part I): Concepts and Foundations for the Compositional Data Analysis of the Microbiome-Gut-Brain Axis—0
MonoCT: Overcoming Monocular 3D Detection Domain Shift with Consistent Teacher Models—0
Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervision—0
Atom Responding Machine for Dialog Generation—0
MonoPlace3D: Learning 3D-Aware Object Placement for 3D Monocular Detection—0
Monopoly agenda control with privately informed voters—0
Monotonic Robust Policy Optimization with Model Discrepancy—0
Dynamic Latent Separation for Deep Learning—0
Monte Carlo Diffusion for Generalizable Learning-Based RANSAC—0
A collaborative decomposition-based evolutionary algorithm integrating normal and penalty-based boundary intersection for many-objective optimization—0
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