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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 8751–8800 of 9051 papers

TitleStatusHype
Diversified Visual Attention Networks for Fine-Grained Object Classification—0
Characterization of Methicillin-resistant Staphylococcus aureus Isolates from Fitness Centers in Memphis Metropolitan Area, USA—0
PAC-Bayesian Analysis for a two-step Hierarchical Multiview Learning Approach—0
Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization—0
Kernel-based Generative Learning in Distortion Feature Space—0
An Empirical Comparison of Sampling Quality Metrics: A Case Study for Bayesian Nonnegative Matrix Factorization—0
Adapting ELM to Time Series Classification: A Novel Diversified Top-k Shapelets Extraction Method—0
Query-Focused Opinion Summarization for User-Generated Content—0
Smart Reply: Automated Response Suggestion for Email—0
Deep Reinforcement Learning for Dialogue GenerationCode0
On Benefits of Selection Diversity via Bilevel Exclusive Sparsity—0
Online Detection and Classification of Dynamic Hand Gestures With Recurrent 3D Convolutional Neural Network—0
Samsung Poland NLP Team at SemEval-2016 Task 1: Necessity for diversity; combining recursive autoencoders, WordNet and ensemble methods to measure semantic similarity.—0
Communities as cliques—0
Evolutionary Demographic Algorithms—0
A model for the clustered distribution of SNPs in the human genome—0
Mitochondrial genealogy of Maria Mercedes Cairol Antunez, footprint of recent immigration to Costa Rica / La genealogia mitocondrial de Maria Mercedes Cairol Antunez, huella de la inmigracion reciente a Costa Rica—0
Automatic Detection and Categorization of Election-Related Tweets—0
Locally Weighted Ensemble Clustering—0
Human Action Localization with Sparse Spatial Supervision—0
Diversity of emergent dynamics in competitive threshold-linear networksCode0
Wisdom of Crowds cluster ensemble—0
When Do Luxury Cars Hit the Road? Findings by A Big Data Approach—0
Adversarial Diversity and Hard Positive Generation—0
The ACQDIV Database: Min(d)ing the Ambient Language—0
Review on the Existing Language Resources for Languages of France—0
TGermaCorp -- A (Digital) Humanities Resource for (Computational) Linguistics—0
Wiktionnaire's Wikicode GLAWIfied: a Workable French Machine-Readable Dictionary—0
Defining and Counting Phonological Classes in Cross-linguistic Segment Databases—0
Multiword Expressions Dataset for Indian Languages—0
Fostering digital representation of EU regional and minority languages: the Digital Language Diversity Project—0
Error Typology and Remediation Strategies for Requirements Written in English by Non-Native Speakers—0
Differentia compositionem facit. A Slower-Paced and Reliable Parser for Latin—0
Feedback-based Approach to Introduce Freshness in Recommendations—0
Condorcet's Jury Theorem for Consensus Clustering and its Implications for Diversity—0
Weighted Spectral Cluster Ensemble—0
Parameterized Compilation Lower Bounds for Restricted CNF-formulas—0
Text-based LSTM networks for Automatic Music CompositionCode0
The genetic code, 8-dimensional hypercomplex numbers and dyadic shifts—0
Synthesizing Training Images for Boosting Human 3D Pose Estimation—0
Parameterized Analysis of Multi-objective Evolutionary Algorithms and the Weighted Vertex Cover Problem—0
Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding—0
The Open World of Micro-Videos—0
Quantifying topological invariants of neuronal morphologies—0
Exclusivity Regularized Machine—0
Colorful Image ColorizationCode0
The behavioural aspect of green technology investments: a general positive model in the context of heterogeneous agents—0
Localized Lasso for High-Dimensional Regression—0
R\'enyi entropy, abundance distribution and the equivalence of ensembles—0
Diversity in Object Proposals—0
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