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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 7176–7200 of 9051 papers

TitleStatusHype
Attribute-guided Feature Extraction and Augmentation Robust Learning for Vehicle Re-identification—0
Progressive growing of self-organized hierarchical representations for exploration—0
Towards Hate Speech Detection at Large via Deep Generative ModelingCode0
Introducing Coherent MIMO Sensing, a fading-resilient, polarization-independent approach to phase-OTDR—0
PSDet: Efficient and Universal Parking Slot DetectionCode0
Non-Orthogonal Multiple Access in the Presence of Additive Generalized Gaussian Noise—0
Diversifying Dialogue Generation with Non-Conversational TextCode0
Generating Pertinent and Diversified Comments with Topic-aware Pointer-Generator Networks—0
Learning Generalized Spoof Cues for Face Anti-spoofingCode1
BOP-Elites, a Bayesian Optimisation algorithm for Quality-Diversity search—0
Comparison and Benchmarking of AI Models and Frameworks on Mobile Devices—0
End-to-End Domain Adaptive Attention Network for Cross-Domain Person Re-Identification—0
Evaluating text coherence based on the graph of the consistency of phrases to identify symptoms of schizophrenia—0
AIBench Scenario: Scenario-distilling AI Benchmarking—0
TAGNN: Target Attentive Graph Neural Networks for Session-based RecommendationCode1
Token Manipulation Generative Adversarial Network for Text GenerationCode0
Attentive Semantic Exploring for Manipulated Face Detection—0
NOMA Visible Light Communication System with Angle Diversity Receivers—0
Russian Natural Language Generation: Creation of a Language Modelling Dataset and Evaluation with Modern Neural ArchitecturesCode0
Neural Syntactic Preordering for Controlled Paraphrase GenerationCode1
StereoGAN: Bridging Synthetic-to-Real Domain Gap by Joint Optimization of Domain Translation and Stereo MatchingCode1
Impact of user distribution on optical wireless systems—0
Distributional Discrepancy: A Metric for Unconditional Text GenerationCode0
Compose Like Humans: Jointly Improving the Coherence and Novelty for Modern Chinese Poetry Generation—0
A New Data Normalization Method to Improve Dialogue Generation by Minimizing Long Tail Effect—0
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