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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 8701–8750 of 9051 papers

TitleStatusHype
A Simple, Fast Diverse Decoding Algorithm for Neural GenerationCode0
Coherent Dialogue with Attention-based Language Models—0
Measuring Sample Quality with Diffusions—0
PolyNet: A Pursuit of Structural Diversity in Very Deep NetworksCode0
Diversity encouraged learning of unsupervised LSTM ensemble for neural activity video prediction—0
A Generic Coordinate Descent Framework for Learning from Implicit Feedback—0
A Learning Scheme for Microgrid Islanding and Reconnection—0
Batched Gaussian Process Bandit Optimization via Determinantal Point Processes—0
Diverse Neural Network Learns True Target Functions—0
Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control—0
Chinese/English mixed Character Segmentation as Semantic Segmentation—0
Unrolled Generative Adversarial NetworksCode1
Generalized Haar Filter based Deep Networks for Real-Time Object Detection in Traffic Scene—0
Conditional Image Synthesis With Auxiliary Classifier GANsCode1
Diversity Promoting Online Sampling for Streaming Video Summarization—0
A Learned Representation For Artistic StyleCode0
How to be Fair and Diverse?—0
KGEval: Estimating Accuracy of Automatically Constructed Knowledge Graphs—0
Enhancing ICA Performance by Exploiting Sparsity: Application to FMRI Analysis—0
Statistical Learning Theory Approach for Data Classification with l-diversity—0
Investigating the effects Diversity Mechanisms have on Evolutionary Algorithms in Dynamic Environments—0
A new selection strategy for selective cluster ensemble based on Diversity and Independency—0
Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence ModelsCode1
Places: An Image Database for Deep Scene Understanding—0
Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search—0
Expansion under climate change: the genetic consequences—0
The multiplicity of memory enhancement: Practical and ethical implications of the diverse neural substrates underlying human memory systems—0
Pose-Selective Max Pooling for Measuring SimilarityCode0
On the Mathematical Relationship between Expected n-call@k and the Relevance vs. Diversity Trade-off—0
PixelNet: Towards a General Pixel-level Architecture—0
An Approach for Self-Training Audio Event Detectors Using Web Data—0
Deep Neural Ensemble for Retinal Vessel Segmentation in Fundus Images towards Achieving Label-free Angiography—0
The MGB-2 Challenge: Arabic Multi-Dialect Broadcast Media Recognition—0
Mathematical toy model inspired by the problem of the adaptive origins of the sexual orientation continuum—0
Inhibitory loop robustly induces anticipated synchronization in neuronal microcircuits—0
A Flexible Recommendation System for Cable TV—0
Making Deep Neural Networks Robust to Label Noise: a Loss Correction ApproachCode0
Matching-Based Selection with Incomplete Lists for Decomposition Multi-Objective Optimization—0
Symmetric and Asymmetric Tendencies in Stable Complex Systems—0
A genomic map of the effects of linked selection in Drosophila—0
Frame- and Segment-Level Features and Candidate Pool Evaluation for Video Caption GenerationCode1
Escaping Local Optima using Crossover with Emergent or Reinforced Diversity—0
SimVerb-3500: A Large-Scale Evaluation Set of Verb SimilarityCode0
Heterogeneous Strategy Particle Swarm Optimization—0
Fisher-Wright model with deterministic seed bank and selection—0
Comeback kids: an evolutionary approach of the long-run innovation process—0
Joint Event Detection and Entity Resolution: a Virtuous Cycle—0
Interaction patterns and diversity in assembled ecological communities—0
The Benefits of Word Embeddings Features for Active Learning in Clinical Information Extraction—0
On Sampling and Greedy MAP Inference of Constrained Determinantal Point Processes—0
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