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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 7526–7550 of 9051 papers

TitleStatusHype
Task-Oriented Dialog Systems that Consider Multiple Appropriate Responses under the Same ContextCode1
Meta Adaptation using Importance Weighted Demonstrations—0
A Discrete CVAE for Response Generation on Short-Text Conversation—0
Analysis of Evolutionary Behavior in Self-Learning Media Search Engines—0
Generating Diverse Translation by Manipulating Multi-Head Attention—0
Rule Extraction in Unsupervised Anomaly Detection for Model Explainability: Application to OneClass SVMCode0
Deep Active Learning: Unified and Principled Method for Query and TrainingCode0
Complexity and Diversity in Sparse Code Priors Improve Receptive Field Characterization of Macaque V1 Neurons—0
Simple yet Effective Way for Improving the Performance of GAN—0
Learning to Synthesize Fashion Textures—0
Grassmannian Packings in Neural Networks: Learning with Maximal Subspace Packings for Diversity and Anti-Sparsity—0
The Proper Care and Feeding of CAMELS: How Limited Training Data Affects Streamflow PredictionCode0
DE/RM-MEDA: A New Hybrid Multi-Objective Generator—0
Empirical Study of Off-Policy Policy Evaluation for Reinforcement LearningCode0
CatGAN: Category-aware Generative Adversarial Networks with Hierarchical Evolutionary Learning for Category Text GenerationCode0
Capturing the Production of the Innovative Ideas: An Online Social Network Experiment and "Idea Geography" Visualization—0
IRIS: Implicit Reinforcement without Interaction at Scale for Learning Control from Offline Robot Manipulation Data—0
Allowing for equal opportunities for artists in music recommendation—0
Double cycle-consistent generative adversarial network for unsupervised conditional generation—0
Creating Auxiliary Representations from Charge Definitions for Criminal Charge Prediction—0
Multidataset Independent Subspace Analysis with Application to Multimodal FusionCode0
Diversity by Phonetics and its Application in Neural Machine Translation—0
Scaling Robot Supervision to Hundreds of Hours with RoboTurk: Robotic Manipulation Dataset through Human Reasoning and Dexterity—0
Sequential Recommendation with Dual Side Neighbor-based Collaborative Relation ModelingCode0
Using LSTMs for climate change assessment studies on droughts and floods—0
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