Robust Broad Learning System with Wave Loss for Classification under Data Uncertainty

arXiv:2608.29983 · cs.LG · Submitted 2026-08-30 · Read on arXiv

cs.LG

Submitted: 2026-08-30

Updated: 2026-08-30

Terminology

• Accuracy — 28× in this paper · explained in 1 episode
• Loss Function — 26× in this paper · explained in 2 episodes
• Robustness — 23× in this paper · explained in 5 episodes
• Broad Learning System — 12× in this paper
• Benchmark — 9× in this paper · explained in 2 episodes
• Regularization — 8× in this paper · explained in 3 episodes
• Objective Function — 6× in this paper · explained in 2 episodes
• Generalization — 4× in this paper · explained in 13 episodes
• Computational overhead — 3× in this paper · explained in 2 episodes
• Copula — 3× in this paper · explained in 2 episodes
• Activation Function — 2× in this paper · explained in 1 episode
• Clustering — 2× in this paper · explained in 2 episodes
• Adaptive Strategy — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks