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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 5151–5200 of 9051 papers

TitleStatusHype
School closures and educational path: how the Covid-19 pandemic affected transitions to college—0
scHyena: Foundation Model for Full-Length Single-Cell RNA-Seq Analysis in Brain—0
SciDMT: A Large-Scale Corpus for Detecting Scientific Mentions—0
SCME: A Self-Contrastive Method for Data-free and Query-Limited Model Extraction Attack—0
SCONE-GAN: Semantic Contrastive learning-based Generative Adversarial Network for an end-to-end image translation—0
Score-based Denoising Diffusion with Non-Isotropic Gaussian Noise Models—0
ScoreMix: A Scalable Augmentation Strategy for Training GANs with Limited Data—0
SCO-VIST: Social Interaction Commonsense Knowledge-based Visual Storytelling—0
Scrapping The Web For Early Wildfire Detection: A New Annotated Dataset of Images and Videos of Smoke Plumes In-the-wild—0
SDFD: Building a Versatile Synthetic Face Image Dataset with Diverse Attributes—0
SDTP: Semantic-aware Decoupled Transformer Pyramid for Dense Image Prediction—0
SEAL: Semantic Attention Learning for Long Video Representation—0
Search For Deep Graph Neural Networks—0
Searching for Designs in-between—0
Search results diversification in competitive search—0
Seasonal Station-Keeping of Short Duration High Altitude Balloons using Deep Reinforcement Learning—0
Sea You Later: Metadata-Guided Long-Term Re-Identification for UAV-Based Multi-Object Tracking—0
Secrecy Performance of Antenna-Selection-Aided MIMOME Channels with BPSK/QPSK Modulations—0
Secure and Privacy Preserving Proxy Biometrics Identities—0
Secure Power Control for Downlink Cell-Free Massive MIMO With Passive Eavesdroppers—0
SeDi-Instruct: Enhancing Alignment of Language Models through Self-Directed Instruction Generation—0
Selection Principles for Gaia—0
Seeding Diversity into AI Art—0
SEE-DPO: Self Entropy Enhanced Direct Preference Optimization—0
Seeing is Believing? Enhancing Vision-Language Navigation using Visual Perturbations—0
Seeing Sound: Assembling Sounds from Visuals for Audio-to-Image Generation—0
Seeing Your Speech Style: A Novel Zero-Shot Identity-Disentanglement Face-based Voice Conversion—0
Seeking Visual Discomfort: Curiosity-driven Representations for Reinforcement Learning—0
SEERL: Sample Efficient Ensemble Reinforcement Learning—0
SegGen: Supercharging Segmentation Models with Text2Mask and Mask2Img Synthesis—0
Segmentation-based Extraction of Key Components from ECG Images: A Framework for Precise Classification and Digitization—0
SELA: Tree-Search Enhanced LLM Agents for Automated Machine Learning—0
Select before Act: Spatially Decoupled Action Repetition for Continuous Control—0
Selecting Backtranslated Data from Multiple Sources for Improved Neural Machine Translation—0
Selecting Better Samples from Pre-trained LLMs: A Case Study on Question Generation—0
Selecting Diverse Features via Spectral Regularization—0
Selecting for Selection: Learning To Balance Adaptive and Diversifying Pressures in Evolutionary Search—0
Selection-Expansion: A Unifying Framework for Motion-Planning and Diversity Search Algorithms—0
Mutation Effect Generalizability under Selection-Drift—0
Selective clustering ensemble based on kappa and F-score—0
Selective Focusing Learning in Conditional GANs—0
Selectively increasing the diversity of GAN-generated samples—0
Self-Adversarial Learning with Comparative Discrimination for Text Generation—0
Self-attention Multi-view Representation Learning with Diversity-promoting Complementarity—0
Self-Consuming Generative Models Go MAD—0
Self-Distillation Prototypes Network: Learning Robust Speaker Representations without Supervision—0
Self-Feedback DETR for Temporal Action Detection—0
Self-Paced Learning with Diversity—0
Self-Referential Quality Diversity Through Differential Map-Elites—0
Self-reinforcing Unsupervised Matching—0
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