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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 6201–6250 of 9051 papers

TitleStatusHype
Ortho-Shot: Low Displacement Rank Regularization with Data Augmentation for Few-Shot Learning—0
Result Diversification by Multi-objective Evolutionary Algorithms with Theoretical GuaranteesCode0
Active Learning for Deep Visual Tracking—0
Know your tools well: Better and faster QA with synthetic examples—0
Emotion Style Transfer with a Specified Intensity Using Deep Reinforcement Learning—0
Qualitative and Quantitative Analysis of Diversity in Cross-document Coreference Resolution Datasets—0
Dataset Geography: Mapping Language Data to Language Users—0
ASR4REAL: An extended benchmark for speech models—0
On The Ingredients of an Effective Zero-shot Semantic Parser—0
Effects of Different Optimization Formulations in Evolutionary Reinforcement Learning on Diverse Behavior Generation—0
DG-Labeler and DGL-MOTS Dataset: Boost the Autonomous Driving Perception—0
Dropping diversity of products of large US firms: Models and measures—0
Analysis of the first Genetic Engineering Attribution ChallengeCode0
CT-SGAN: Computed Tomography Synthesis GAN—0
Retrieval-guided Counterfactual Generation for QA—0
Open-Domain Question-Answering for COVID-19 and Other Emergent DomainsCode0
Diverse Audio Captioning via Adversarial Training—0
Vibration-Based Condition Monitoring By Ensemble Deep Learning—0
Quantifying Cognitive Factors in Lexical DeclineCode0
Advances in Multi-turn Dialogue Comprehension: A Survey—0
Evolutionary drivers, morphological evolution and diversity dynamics of a surviving mammal clade: cainotherioids at the Eocene--Oligocene transition—0
Internal Feedback in Biological Control: Architectures and Examples—0
Multi-Task Learning for Situated Multi-Domain End-to-End Dialogue Systems—0
Surrogate-Assisted Reference Vector Adaptation to Various Pareto Front Shapes for Many-Objective Bayesian OptimizationCode0
Recoverability of Ancestral Recombination Graph Topologies—0
Active learning for interactive satellite image change detection—0
Aura: Privacy-preserving Augmentation to Improve Test Set Diversity in Speech EnhancementCode0
Game Theory for Adversarial Attacks and DefensesCode0
TRUNet: Transformer-Recurrent-U Network for Multi-channel Reverberant Sound Source Separation—0
Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity—0
Enhanced Memory Network: The novel network structure for Symbolic Music GenerationCode0
Evolutionary Computation-Assisted Brainwriting for Large-Scale Online Ideation—0
A Hierarchical Variational Neural Uncertainty Model for Stochastic Video Prediction—0
HYPER: Learned Hybrid Trajectory Prediction via Factored Inference and Adaptive Sampling—0
Max and Coincidence Neurons in Neural Networks—0
Heritable Nongenetic Information That is Independent of DNA and That Governs Organismal Development, Tissue Regeneration, and Tumor Architecture—0
InfiniteForm: A synthetic, minimal bias dataset for fitness applications—0
Boost Neural Networks by Checkpoints—0
Seeking Visual Discomfort: Curiosity-driven Representations for Reinforcement Learning—0
Improving Zero-shot Multilingual Neural Machine Translation for Low-Resource Languages—0
Learning of Inter-Label Geometric Relationships Using Self-Supervised Learning: Application To Gleason Grade Segmentation—0
Decoupling Pragmatics: Discriminative Decoding for Referring Expression Generation—0
Fake It Till You Make It: Face analysis in the wild using synthetic data alone—0
Robust Allocations with Diversity Constraints—0
Reconstructing Word Embeddings via Scattered k-Sub-Embedding—0
Deep Ensemble Policy Learning—0
Unconditional Diffusion Guidance—0
Synaptic Diversity in ANNs Can Facilitate Faster Learning—0
Diverse and Consistent Multi-view Networks for Semi-supervised Regression—0
Neural Network Ensembles: Theory, Training, and the Importance of Explicit Diversity—0
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