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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 5151–5175 of 9051 papers

TitleStatusHype
Exploring Diversity-based Active Learning for 3D Object Detection in Autonomous DrivingCode0
Accented Speech Recognition: Benchmarking, Pre-training, and Diverse Data—0
The Diversity of Argument-Making in the Wild: from Assumptions and Definitions to Causation and Anecdote in Reddit's "Change My View"—0
DendroMap: Visual Exploration of Large-Scale Image Datasets for Machine Learning with TreemapsCode1
Practical Insights of Repairing Model Problems on Image Classification—0
Self-supervised Assisted Active Learning for Skin Lesion SegmentationCode1
Towards Understanding the Link Between Modularity and Performance in Neural Networks for Reinforcement LearningCode0
StyLandGAN: A StyleGAN based Landscape Image Synthesis using Depth-map—0
Beyond Static Models and Test Sets: Benchmarking the Potential of Pre-trained Models Across Tasks and Languages—0
What's in a Caption? Dataset-Specific Linguistic Diversity and Its Effect on Visual Description Models and MetricsCode1
kNN-Embed: Locally Smoothed Embedding Mixtures For Multi-interest Candidate Retrieval—0
TreeMix: Compositional Constituency-based Data Augmentation for Natural Language UnderstandingCode1
Efficient and Training-Free Control of Language Generation—0
A Chit-Chats Enhanced Task-Oriented Dialogue Corpora for Fuse-Motive Conversation SystemsCode0
Efficient Distributed Framework for Collaborative Multi-Agent Reinforcement Learning—0
Tiny Robot Learning: Challenges and Directions for Machine Learning in Resource-Constrained Robots—0
Deep Gait Tracking With Inertial Measurement Unit—0
M3ED: Multi-modal Multi-scene Multi-label Emotional Dialogue DatabaseCode1
Should attention be all we need? The epistemic and ethical implications of unification in machine learning—0
Cross-Utterance Conditioned VAE for Non-Autoregressive Text-to-SpeechCode1
Improving negation detection with negation-focused pre-training—0
Attracting and Dispersing: A Simple Approach for Source-free Domain AdaptationCode1
Multi-Domain Targeted Sentiment Analysis—0
Network Traffic Anomaly Detection Method Based on Multi scale Residual Feature—0
A Closer Look at Few-shot Image Generation—0
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