SOTAVerified

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

Showing 66016650 of 9051 papers

TitleStatusHype
Unsupervised Estimation of Ensemble Accuracy0
Practical Insights of Repairing Model Problems on Image Classification0
Taxonomy of Machine Learning Safety: A Survey and Primer0
AnyFace: Free-style Text-to-Face Synthesis and Manipulation0
Unity in Diversity: Multi-expert Knowledge Confrontation and Collaboration for Generalizable Vehicle Re-identification0
Pragmatically Appropriate Diversity for Dialogue Evaluation0
Prague Dependency Treebank - Consolidated 1.00
Prague Dependency Treebank -- Consolidated 1.00
Prb-GAN: A Probabilistic Framework for GAN Modelling0
AnyEdit: Mastering Unified High-Quality Image Editing for Any Idea0
Predator-prey survival pressure is sufficient to evolve swarming behaviors0
Predicting Adversarial Examples with High Confidence0
Predicting Camera Viewpoint Improves Cross-dataset Generalization for 3D Human Pose Estimation0
Unity in Diversity: Video Editing via Gradient-Latent Purification0
Predicting conversion of mild cognitive impairment to Alzheimer's disease0
Predicting Foreground Object Ambiguity and Efficiently Crowdsourcing the Segmentation(s)0
Predicting Query-Item Relationship using Adversarial Training and Robust Modeling Techniques0
Predicting retrosynthetic pathways using a combined linguistic model and hyper-graph exploration strategy0
Predicting scalar diversity with context-driven uncertainty over alternatives0
Predicting Star Scientists in the Field of Artificial Intelligence: A Machine Learning Approach0
Predicting Success in Goal-Driven Human-Human Dialogues0
Predicting the diversity of early epidemic spread on networks0
Universal and data-adaptive algorithms for model selection in linear contextual bandits0
Predicting the Skies: A Novel Model for Flight-Level Passenger Traffic Forecasting0
Prediction of viral spillover risk based on the mass action principle0
Universal and generalizable restoration strategies for degraded ecological networks0
Predictive Analysis for Optimizing Port Operations0
Predictive modeling and anomaly detection in large-scale web portals through the CAWAL framework0
Predictive PER: Balancing Priority and Diversity towards Stable Deep Reinforcement Learning0
Towards Open-Set Myoelectric Gesture Recognition via Dual-Perspective Inconsistency Learning0
Preference-Conditioned Gradient Variations for Multi-Objective Quality-Diversity0
Preference-Guided Diffusion for Multi-Objective Offline Optimization0
An upper bound of the mutation probability in the genetic algorithm for general 0-1 knapsack problem0
An Unsupervised Semantic Sentence Ranking Scheme for Text Documents0
Preference Optimization with Multi-Sample Comparisons0
Prefix-diffusion: A Lightweight Diffusion Model for Diverse Image Captioning0
An Unsupervised Domain Adaptation Method for Locating Manipulated Region in partially fake Audio0
Pre-Optimized Irregular Arrays versus Moveable Antennas in Multi-User MIMO Systems0
Preparing for Black Swans: The Antifragility Imperative for Machine Learning0
Preparing for the Unexpected: Diversity Improves Planning Resilience in Evolutionary Algorithms0
Universal Cold RNA Phase Transitions0
Universal Dependencies for Punjabi0
Universal Features Guided Zero-Shot Category-Level Object Pose Estimation0
Preserving Product Fidelity in Large Scale Image Recontextualization with Diffusion Models0
Presto! Distilling Steps and Layers for Accelerating Music Generation0
Universal Information Extraction as Unified Semantic Matching0
Deep Single Image Deraining using An Asymetric Cycle Generative and Adversarial Framework0
Pre-Training BERT on Arabic Tweets: Practical Considerations0
An Unscented Kalman Filter-Informed Neural Network for Vehicle Sideslip Angle Estimation0
Preventing Value Function Collapse in Ensemble Q-Learning by Maximizing Representation Diversity0
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