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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 2426–2450 of 9051 papers

TitleStatusHype
A Practical Introduction to Deep Reinforcement Learning—0
CJRC: A Reliable Human-Annotated Benchmark DataSet for Chinese Judicial Reading Comprehension—0
A practical generalization metric for deep networks benchmarking—0
Affine Frequency Division Multiplexing: Extending OFDM for Scenario-Flexibility and Resilience—0
CityGen: Infinite and Controllable 3D City Layout Generation—0
CityCraft: A Real Crafter for 3D City Generation—0
Approximating Pareto Frontier through Bayesian-optimization-directed Robust Multi-objective Reinforcement Learning—0
Citation Structural Diversity: A Novel and Concise Metric Combining Structure and Semantics for Literature Evaluation—0
Circulant Binary Convolutional Networks: Enhancing the Performance of 1-bit DCNNs with Circulant Back Propagation—0
Affect-Driven Dialog Generation—0
A3Net: Adversarial-and-Attention Network for Machine Reading Comprehension—0
Approximability of Discriminators Implies Diversity in GANs—0
CIGMO: Learning categorical invariant deep generative models from grouped data—0
Push and Pull Search Embedded in an M2M Framework for Solving Constrained Multi-objective Optimization Problems—0
Approach to Visual Attractiveness of Event Space Through Data-Driven Environment and Spatial Perception—0
Cifu: a Frequency Lexicon of Hong Kong Cantonese—0
A Few Good Counterfactuals: Generating Interpretable, Plausible and Diverse Counterfactual Explanations—0
Diversity in Faces—0
Approaches to studying virus pangenome variation graphs—0
AFEN: Respiratory Disease Classification using Ensemble Learning—0
Chosen methods of improving small object recognition with weak recognizable features—0
Applying Artificial Intelligence for Age Estimation in Digital Forensic Investigations—0
Cascading Hybrid Bandits: Online Learning to Rank for Relevance and Diversity—0
Diversity in immunogenomics: the value and the challenge—0
Diversity in Kemeny Rank Aggregation: A Parameterized Approach—0
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