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Horizontal and Vertical Ensemble with Deep Representation for Classification

arXiv 1306.2759 ↗First posted 12 Jun 2013cs.LG stat.MLcited by 22

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Abstract (arXiv)

Representation learning, especially which by using deep learning, has been widely applied in classification. However, how to use limited size of labeled data to achieve good classification performance with deep neural network, and how can the learned features further improve classification remain indefinite. In this paper, we propose Horizontal Voting Vertical Voting and Horizontal Stacked Ensemble methods to improve the classification performance of deep neural networks. In the ICML 2013 Black Box Challenge, via using these methods independently, Bing Xu achieved 3rd in public leaderboard, and 7th in private leaderboard; Jingjing Xie achieved 4th in public leaderboard, and 5th in private leaderboard.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Jun 2013.

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Citing papers per year: 2021: 8; 2022: 6; 2023: 3; 2024: 2; 2025: 3.

22 papers.

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  1. 2021Ensemble deep learning: A reviewcited by 283
  2. 2021Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsitycited by 44
  3. 2021Sparse MoEs meet Efficient Ensemblescited by 19
  4. 2022Prune and Tune Ensembles: Low-Cost Ensemble Learning With Sparse Independent Subnetworkscited by 13
  5. 2022A Survey of Computer Vision Technologies In Urban and Controlled-environment Agriculturecited by 6
  6. 2024A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentationcited by 6
  7. 2022Sequential Bayesian Neural Subnetwork Ensemblescited by 5
  8. 2023Logit-Based Ensemble Distribution Distillation for Robust Autoregressive Sequence Uncertaintiescited by 5
  9. 2021Boost Neural Networks by Checkpointscited by 4
  10. 2021Explore the Potential Performance of Vision-and-Language Navigation Model: a Snapshot Ensemble Methodcited by 4
  11. 2022Learning Proximal Operators to Discover Multiple Optimacited by 4
  12. 2022Instability in clinical risk stratification models using deep learningcited by 3
10 more
  1. 2021High-Dimensional Stock Portfolio Trading with Deep Reinforcement Learningcited by 2
  2. 2021Efficient Model Performance Estimation via Feature Historiescited by 1
  3. 2022Boosted Ensemble Learning based on Randomized NNs for Time Series Forecastingcited by 1
  4. 2024Towards a Systematic Approach to Design New Ensemble Learning Algorithmscited by 1
  5. 2021NeuSE: A Neural Snapshot Ensemble Method for Collaborative Filteringcited by 0
  6. 2023HCE: Improving Performance and Efficiency with Heterogeneously Compressed Neural Network Ensemblecited by 0
  7. 2023Relearning Forgotten Knowledge: on Forgetting, Overfit and Training-Free Ensembles of DNNscited by 0
  8. 2025Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillationcited by 0
  9. 2025Symbolic Snapshot Ensemblescited by 0
  10. 2025Parameter Averaging in Link Predictioncited by 0