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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 8626–8650 of 9051 papers

TitleStatusHype
A Unified Multi-Faceted Video Summarization System—0
Using Coreference Links to Improve Spanish-to-English Machine TranslationCode0
Online Automatic Post-editing for MT in a Multi-Domain Translation Environment—0
BEGAN: Boundary Equilibrium Generative Adversarial NetworksCode0
Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational AutoencodersCode0
Diversity of preferences can increase collective welfare in sequential exploration problems—0
Adversarial Transformation Networks: Learning to Generate Adversarial ExamplesCode0
BIISQ: Bayesian nonparametric discovery of Isoforms and Individual Specific QuantificationCode0
Recurrent and Contextual Models for Visual Question Answering—0
Random Features for Compositional Kernels—0
Insular microbiogeography—0
A Fully-Automated Pipeline for Detection and Segmentation of Liver Lesions and Pathological Lymph Nodes—0
TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial NetworkCode1
Aggregation of Classifiers: A Justifiable Information Granularity Approach—0
Detecting Sockpuppets in Deceptive Opinion Spam—0
Tree-Structured Reinforcement Learning for Sequential Object Localization—0
SRN: Side-output Residual Network for Object Symmetry Detection in the WildCode0
Computational Eco-Systems for Handwritten Digits Recognition—0
Activation Maximization Generative Adversarial NetsCode0
Diversified Texture Synthesis with Feed-forward Networks—0
A Unifying View of Explicit and Implicit Feature Maps of Graph Kernels—0
Phylogenetic Tools in Astrophysics—0
Remote Sensing Image Scene Classification: Benchmark and State of the ArtCode1
PMLB: A Large Benchmark Suite for Machine Learning Evaluation and ComparisonCode0
Characterization of phase transitions in a model ecosystem of sessile species—0
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