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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 6851–6900 of 9051 papers

TitleStatusHype
Measuring GAN Training in Real Time—0
Monotonic Robust Policy Optimization with Model Discrepancy—0
ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity—0
Tradeoffs in Data Augmentation: An Empirical Study—0
NOSE Augment: Fast and Effective Data Augmentation Without Searching—0
Molecule Optimization by Explainable Evolution—0
Learning a Non-Redundant Collection of Classifiers—0
Diverse Image Style Transfer via Invertible Cross-Space Mapping—0
TaskSet: A Dataset of Optimization TasksCode0
CIGMO: Learning categorical invariant deep generative models from grouped data—0
Learning Disentangled Representations for Image Translation—0
Deep Ensembles with Hierarchical Diversity PruningCode0
Sample efficient Quality Diversity for neural continuous control—0
FGraDA: A Dataset and Benchmark for Fine-Grained Domain Adaptation in Machine TranslationCode0
Generalized Operating Procedure for Deep Learning: an Unconstrained Optimal Design Perspective—0
Enhancing Pre-trained Language Model with Lexical Simplification—0
Artificial Intelligence Development Races in Heterogeneous Settings—0
Deep Unsupervised Identification of Selected SNPs between Adapted Populations on Pool-seq Data—0
Evaluation and Comparison of Edge-Preserving Filters—0
A Hybrid Bandit Framework for Diversified Recommendation—0
Reconfigurable Intelligent Surface-assisted Networks: Phase Alignment Categories—0
Evolving the Behavior of Machines: From Micro to Macroevolution—0
Get It Scored Using AutoSAS -- An Automated System for Scoring Short Answers—0
An Overview of Facial Micro-Expression Analysis: Data, Methodology and Challenge—0
Minimax Active Learning—0
Recommenders with a mission: assessing diversity in newsrecommendations—0
Regularized Attentive Capsule Network for Overlapped Relation Extraction—0
STNet: Scale Tree Network with Multi-level Auxiliator for Crowd Counting—0
RAILS: A Robust Adversarial Immune-inspired Learning System—0
ErGAN: Generative Adversarial Networks for Entity Resolution—0
Interactive Speech and Noise Modeling for Speech Enhancement—0
A New Many-Objective Evolutionary Algorithm Based on Determinantal Point Processes—0
On the Importance of Diversity in Re-Sampling for Imbalanced Data and Rare Events in Mortality Risk Models—0
Policy Manifold Search for Improving Diversity-based Neuroevolution—0
FedeRank: User Controlled Feedback with Federated Recommender Systems—0
Intrinsic Image Captioning Evaluation—0
Sparse Multi-Family Deep Scattering Network—0
Relative Variational Intrinsic Control—0
Syntactic representation learning for neural network based TTS with syntactic parse tree traversal—0
Enhanced species coexistence in Lotka-Volterra competition models due to nonlocal interactions—0
Ensemble Squared: A Meta AutoML System—0
Cost-Based Budget Active Learning for Deep Learning—0
Promoting Semantics in Multi-objective Genetic Programming based on Decomposition—0
Occupational segregation in a Roy model with composition preferences—0
Data InStance Prior (DISP) in Generative Adversarial Networks—0
IRS-Assisted Massive MIMO-NOMA Networks: Exploiting Wave Polarization—0
Diverse Melody Generation from Chinese Lyrics via Mutual Information Maximization—0
Does the dataset meet your expectations? Explaining sample representation in image data—0
Bayesian optimization assisted unsupervised learning for efficient intra-tumor partitioning in MRI and survival prediction for glioblastoma patients—0
Energy-Efficient Design of Broad Beams for Massive MIMO Systems—0
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