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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 8101–8125 of 9051 papers

TitleStatusHype
Show, Control and Tell: A Framework for Generating Controllable and Grounded CaptionsCode0
Resource Mention Extraction for MOOC Discussion Forums—0
Scene Text Detection with Supervised Pyramid Context NetworkCode0
New expressions on the performance of a novel multi-hop relay-assisted hybrid FSO / RF communication system with receive diversity—0
The long-term impact of ranking algorithms in growing networks—0
A novel hybrid FSO / RF communication system with receive diversity—0
Another Diversity-Promoting Objective Function for Neural Dialogue GenerationCode0
CompoNet: Learning to Generate the Unseen by Part Synthesis and CompositionCode0
Chat More If You Like: Dynamic Cue Words Planning to Flow Longer Conversations—0
Behavioral Malware Classification using Convolutional Recurrent Neural Networks—0
Clubmark: a Parallel Isolation Framework for Benchmarking and Profiling Clustering Algorithms on NUMA ArchitecturesCode0
Deep Determinantal Point Processes—0
Evolutionary Diversity Optimization Using Multi-Objective Indicators—0
Towards Large-Scale Exploratory Search over Heterogeneous Sources—0
Generating Multiple Diverse Responses for Short-Text Conversation—0
Universal and generalizable restoration strategies for degraded ecological networks—0
Modular Networks: Learning to Decompose Neural Computation—0
Parameterized Synthetic Image Data Set for Fisheye Lens—0
Combining Learned Lyrical Structures and Vocabulary for Improved Lyric Generation—0
Attentive Aspect Modeling for Review-aware Recommendation—0
User Modeling for Task Oriented Dialogues—0
Diversity-Driven Extensible Hierarchical Reinforcement LearningCode0
Multi-Cycle Assignment Problems with Rotational Diversity—0
Iterative Classroom Teaching—0
Behavioural Repertoire via Generative Adversarial Policy Networks—0
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