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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 8451–8500 of 9051 papers

TitleStatusHype
Semi-Supervised Convolutional Neural Networks for Human Activity Recognition—0
Fully Point-wise Convolutional Neural Network for Modeling Statistical Regularities in Natural Images—0
Semi-supervised FusedGAN for Conditional Image Generation—0
Building a Conversational Agent Overnight with Dialogue Self-PlayCode1
Deep Metric Learning with BIER: Boosting Independent Embeddings RobustlyCode0
Simple Unsupervised Keyphrase Extraction using Sentence EmbeddingsCode0
Emergent memory in cell signaling: Persistent adaptive dynamics in cascades can arise from the diversity of relaxation time-scales—0
Topic-based Evaluation for Conversational BotsCode0
Moments in Time Dataset: one million videos for event understandingCode0
Synthetic Data Augmentation using GAN for Improved Liver Lesion Classification—0
Ensemble One-dimensional Convolution Neural Networks for Skeleton-based Action Recognition—0
Indian Regional Movie Dataset for Recommender SystemsCode0
Learning from Neighbors about a Changing State—0
Explorations in an English Poetry Corpus: A Neurocognitive Poetics Perspective—0
Generating Neural Networks with Neural NetworksCode0
Intelligence Graph—0
Dynamic Island Model based on Spectral Clustering in Genetic Algorithm—0
Extraction of Verbal Synsets and Relations for FarsNet—0
A Classification-Based Perspective on GAN Distributions—0
Hallucinating brains with artificial brains—0
Minimax Curriculum Learning: Machine Teaching with Desirable Difficulties and Scheduled Diversity—0
Personal Names in Modern Turkey—0
Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness RewardCode0
DancingLines: An Analytical Scheme to Depict Cross-Platform Event Popularity—0
Deep Hashing with Category Mask for Fast Video RetrievalCode0
Model-Based Clustering of Nonparametric Weighted Networks with Application to Water Pollution Analysis—0
Variational Attention for Sequence-to-Sequence ModelsCode0
On the Diversity of Realistic Image SynthesisCode0
Item-Item Music Recommendations With Side Information—0
Tracking of plus-ends reveals microtubule functional diversity in different cell types—0
Self-adaptation of Genetic Operators Through Genetic Programming TechniquesCode0
Probabilistic Semantic Retrieval for Surveillance Videos with Activity Graphs—0
Logo Synthesis and Manipulation with Clustered Generative Adversarial Networks—0
PacGAN: The power of two samples in generative adversarial networksCode0
Self-supervised Multi-level Face Model Learning for Monocular Reconstruction at over 250 Hz—0
From Lifestyle Vlogs to Everyday Interactions—0
Adaptive stimulus selection for optimizing neural population responses—0
Subset Selection and Summarization in Sequential Data—0
IIIT-H at IJCNLP-2017 Task 3: A Bidirectional-LSTM Approach for Review Opinion Diversification—0
Structured Deep Neural Network Pruning via Matrix Pivoting—0
InclusiveFaceNet: Improving Face Attribute Detection with Race and Gender DiversityCode0
Toward Multimodal Image-to-Image TranslationCode0
Computational strategies for dissecting the high-dimensional complexity of adaptive immune repertoires—0
Generalized Grounding Graphs: A Probabilistic Framework for Understanding Grounded Commands—0
Restricting Greed in Training of Generative Adversarial Network—0
End-to-end Adversarial Learning for Generative Conversational AgentsCode0
The Price of Quota-based Diversity in Assignment Problems—0
Camera Style Adaptation for Person Re-identificationCode0
Theoretical tool bridging cell polarities with development of robust morphologiesCode0
Minor climatic fluctuations lead to species extinction in a conceptual ecosystem model—0
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