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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

Showing 71517200 of 9051 papers

TitleStatusHype
One-Pot Multi-Frame Denoising0
One-Shot Generative Domain Adaptation0
One-shot Imitation in a Non-Stationary Environment via Multi-Modal Skill0
One Size Does Not Fit All: Modeling Users' Personal Curiosity in Recommender Systems0
One Stack, Diverse Vehicles: Checking Safe Portability of Automated Driving Software0
On Evaluation of Document Classification using RVL-CDIP0
On Evolvability and Behavior Landscapes in Neuroevolutionary Divergent Search0
One-Way Ticket: Time-Independent Unified Encoder for Distilling Text-to-Image Diffusion Models0
One world, one opinion? The superstar effect in LLM responses0
On Extreme Pruning of Random Forest Ensembles for Real-time Predictive Applications0
On Fairness, Diversity and Randomness in Algorithmic Decision Making0
On Feature Diversity in Energy-based Models0
On How Users Edit Computer-Generated Visual Stories0
On Hyperspectral Classification in the Compressed Domain0
On Languaging a Simulation Engine0
Exploring Social Media Image Categorization Using Large Models with Different Adaptation Methods: A Case Study on Cultural Nature's Contributions to People0
On Learning the Tail Quantiles of Driving Behavior Distributions via Quantile Regression and Flows0
Online Automatic Post-editing for MT in a Multi-Domain Translation Environment0
Online Behavior Modification for Expressive User Control of RL-Trained Robots0
Online Camera-to-ground Calibration for Autonomous Driving0
Online Detection and Classification of Dynamic Hand Gestures With Recurrent 3D Convolutional Neural Network0
Online Diversity Control in Symbolic Regression via a Fast Hash-based Tree Similarity Measure0
Online Knowledge Distillation via Multi-branch Diversity Enhancement0
Online News Media Website Ranking Using User Generated Content0
On Minimizing Symbol Error Rate Over Fading Channels with Low-Resolution Quantization0
Affinity-based extension of non-extensive entropy and statistical mechanics0
ON NEURAL NETWORK GENERALIZATION VIA PROMOTING WITHIN-LAYER ACTIVATION DIVERSITY0
On Nondeterminism and Instability in Optimizing Neural Networks0
On Nondeterminism and Instability in Neural Network Optimization0
On Paraphrase Identification Corpora0
On Performance of Fluid Antenna System using Maximum Ratio Combining0
On properties driving diversity index selection0
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling, and Beyond0
On Sampling and Greedy MAP Inference of Constrained Determinantal Point Processes0
On Stein Variational Neural Network Ensembles0
On the Amplification of Linguistic Bias through Unintentional Self-reinforcement Learning by Generative Language Models -- A Perspective0
The quest for the definition of life0
On the Arithmetic and Geometric Fusion of Beliefs for Distributed Inference0
On the clustering of correlated random variables0
On the Complexity of Optimising Variants of Phylogenetic Diversity on Phylogenetic Networks0
On the Computational Tractability of the (Many) Shapley Values0
On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization0
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness0
On the Diversity and Coded Modulation Design of Fluid Antenna Systems0
On the Diversity and Limits of Human Explanations0
On the Diversity and Limits of Human Explanations0
On the Diversity of Synthetic Data and its Impact on Training Large Language Models0
On the Dynamics of Mating Preferences in Genetic Programming0
On the Effectiveness of Acoustic BPE in Decoder-Only TTS0
On the Effectiveness of Genetic Operations in Symbolic Regression0
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