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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 8401–8450 of 9051 papers

TitleStatusHype
Synthetic data augmentation for robotic mobility aids to support blind and low vision people—0
Distilling Privileged Multimodal Information for Expression Recognition using Optimal Transport—0
Synthetic Data Augmentation using GAN for Improved Liver Lesion Classification—0
Distributed Antenna Selection for Massive MIMO using Reversing Petri Nets—0
Distributed Deep Learning for Modulation Classification in 6G Cell-Free Wireless Networks—0
Synthetic Data Generation for Augmenting Small Samples—0
Distributed Maximization of Submodular plus Diversity Functions for Multi-label Feature Selection on Huge Datasets—0
Distributed Multi-Head Learning Systems for Power Consumption Prediction—0
Conditional Single-view Shape Generation for Multi-view Stereo Reconstruction—0
Advancing Cross-Organ Domain Generalization with Test-Time Style Transfer and Diversity Enhancement—0
Distribution Aligned Multimodal and Multi-Domain Image Stylization—0
Distribution augmentation for low-resource expressive text-to-speech—0
Conditional Neural Generation using Sub-Aspect Functions for Extractive News Summarization—0
Distribution Aware Metrics for Conditional Natural Language Generation—0
Synthetic Data Generation for Residential Load Patterns via Recurrent GAN and Ensemble Method—0
Distribution Learning Based on Evolutionary Algorithm Assisted Deep Neural Networks for Imbalanced Image Classification—0
Distribution-restrained Softmax Loss for the Model Robustness—0
DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation—0
How Diversely Can Language Models Solve Problems? Exploring the Algorithmic Diversity of Model-Generated Code—0
DITTO-NeRF: Diffusion-based Iterative Text To Omni-directional 3D Model—0
div2vec: Diversity-Emphasized Node Embedding—0
Conditional Distribution Modelling for Few-Shot Image Synthesis with Diffusion Models—0
DivAvatar: Diverse 3D Avatar Generation with a Single Prompt—0
DivBO: Diversity-aware CASH for Ensemble Learning—0
CONDEN-FI: Consistency and Diversity Learning-based Multi-View Unsupervised Feature and In-stance Co-Selection—0
Conceptual Mapping of Controversies—0
DivCon-NeRF: Generating Augmented Rays with Diversity and Consistency for Few-shot View Synthesis—0
Dive3D: Diverse Distillation-based Text-to-3D Generation via Score Implicit Matching—0
Synthetic Patient-Physician Dialogue Generation from Clinical Notes Using LLM—0
Conceptual Content in Deep Convolutional Neural Networks: An analysis into multi-faceted properties of neurons—0
DiverGAN: An Efficient and Effective Single-Stage Framework for Diverse Text-to-Image Generation—0
Synthetic Unknown Class Learning for Learning Unknowns—0
Conceptual capacity and effective complexity of neural networks—0
Advancing Video Anomaly Detection: A Concise Review and a New Dataset—0
Diverse 3D Human Pose Generation in Scenes based on Decoupled Structure—0
Diverse Agents for Ad-Hoc Cooperation in Hanabi—0
Conceptors: an easy introduction—0
Concept-Monitor: Understanding DNN training through individual neurons—0
Diverse and Coherent Paragraph Generation from Images—0
Diverse and Consistent Multi-view Networks for Semi-supervised Regression—0
Diverse and Effective Red Teaming with Auto-generated Rewards and Multi-step Reinforcement Learning—0
ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficulty—0
Diverse and Fine-Grained Instruction-Following Ability Exploration with Synthetic Data—0
Diverse and Lifespan Facial Age Transformation Synthesis with Identity Variation Rationality Metric—0
Diverse and Relevant Visual Storytelling with Scene Graph Embeddings—0
Concept Drift Adaptation by Exploiting Historical Knowledge—0
Diverse Audio Captioning via Adversarial Training—0
Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems—0
Computing High-Quality Solutions for the Patient Admission Scheduling Problem using Evolutionary Diversity Optimisation—0
Diverse Beam Search for Increased Novelty in Abstractive Summarization—0
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