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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 7801–7850 of 9051 papers

TitleStatusHype
Selection Principles for Gaia—0
Salient Slices: Improved Neural Network Training and Performance with Image Entropy—0
Scalable Source Code Similarity Detection in Large Code Repositories—0
Universal Pooling -- A New Pooling Method for Convolutional Neural Networks—0
Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta LearningCode0
Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards—0
Investigating Evaluation of Open-Domain Dialogue Systems With Human Generated Multiple ReferencesCode0
Shared Generative Latent Representation Learning for Multi-view ClusteringCode0
Analyzing the Variety Loss in the Context of Probabilistic Trajectory Prediction—0
Comparing reliability of grid-based Quality-Diversity algorithms using artificial landscapes—0
Controlling biases and diversity in diverse image-to-image translation—0
Automatic Calibration of Artificial Neural Networks for Zebrafish Collective Behaviours using a Quality Diversity Algorithm—0
Neural Cross-Domain Collaborative Filtering with Shared Entities—0
Probabilistic Regressor Chains with Monte Carlo Methods—0
How many different clonotypes do immune repertoires contain?—0
Towards Markerless Grasp Capture—0
The Role of Local Intrinsic Dimensionality in Benchmarking Nearest Neighbor Search—0
Data Selection for training Semantic Segmentation CNNs with cross-dataset weak supervision—0
Modeling competitive evolution of multiple languages—0
Improved Reinforcement Learning through Imitation Learning Pretraining Towards Image-based Autonomous Driving—0
Fairness and Diversity in the Recommendation and Ranking of Participatory Media Content—0
Modeling User Selection in Quality Diversity—0
Evolvability ES: Scalable and Direct Optimization of EvolvabilityCode0
Diverse Trajectory Forecasting with Determinantal Point Processes—0
On the Evaluation of Conditional GANsCode0
Activitynet 2019 Task 3: Exploring Contexts for Dense Captioning Events in Videos—0
Impact of ECG Dataset Diversity on Generalization of CNN Model for Detecting QRS Complex—0
Domain Adaptation-based Augmentation for Weakly Supervised Nuclei Detection—0
Diverse Agents for Ad-Hoc Cooperation in Hanabi—0
Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm—0
Video Question Generation via Cross-Modal Self-Attention Networks Learning—0
Twin Auxiliary Classifiers GANCode0
Sim2real transfer learning for 3D human pose estimation: motion to the rescue—0
Trading Redundancy for Communication: Speeding up Distributed SGD for Non-convex OptimizationCode0
Supervised Uncertainty Quantification for Segmentation with Multiple AnnotationsCode0
How we do things with words: Analyzing text as social and cultural data—0
Deep Convolutional Compression for Massive MIMO CSI Feedback—0
Forecasting high-dimensional dynamics exploiting suboptimal embeddings—0
Multi-scale Template Matching with Scalable Diversity Similarity in an Unconstrained Environment—0
Neural Network Verification for the Masses (of AI graduates)—0
T-CVAE: Transformer-Based Conditioned Variational Autoencoder for Story CompletionCode0
Generating Diverse Translations with Sentence Codes—0
Learning to Abstract for Memory-augmented Conversational Response GenerationCode0
Beyond BLEU:Training Neural Machine Translation with Semantic Similarity—0
Bandit Learning for Diversified Interactive Recommendation—0
Generating Responses with a Specific Emotion in Dialog—0
An Automated Ensemble Learning Framework Using Genetic Programming for Image ClassificationCode0
A Multilingual BPE Embedding Space for Universal Sentiment Lexicon Induction—0
Boosting Dialog Response Generation—0
One Size Does Not Fit All: Modeling Users' Personal Curiosity in Recommender Systems—0
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