Latest Research in Machine Learning

Top Research Topics in Machine Learning

• Machine Learning — 23 papers
• Machine Learning — 4 papers
• Machine Learning in Materials Science — 3 papers
• Methodology — 3 papers
• Neural Networks and Applications — 2 papers
• Metaheuristic Optimization Algorithms Research — 2 papers
• Generative Adversarial Networks and Image Synthesis — 2 papers
• Artificial Intelligence — 2 papers
• Advanced Graph Neural Networks — 2 papers
• Rough Sets and Fuzzy Logic — 2 papers

Highest-Cited Papers

1. Burnside Orbit Histogram Network (BOHN) and Symmetry-Breaking BOHN (SBOHN): From Group Orbits to Symmetry-Breaking Observables in Machine Learning Complete Documentation with Source Codes and Experimental Results
2. Burnside Orbit Histogram Network (BOHN) and Symmetry-Breaking BOHN (SBOHN): From Group Orbits to Symmetry-Breaking Observables in Machine Learning Complete Documentation with Source Codes and Experimental Results
3. Extract, Audit, Certify: A Unified Pipeline for Finding and Proving What Small Recurrent Networks Compute
4. A Prior-Guided Structure-Aware Multi-Objective Differential Evolution Method for High-Dimensional Feature Selection
5. Covering Numbers for Deep ReLU Networks with Applications to Function Approximation and Nonparametric Regression
6. Beyond Quadratic Loss: The Stability Phase Diagram of Adam
7. When a High Score Is an Illusion: Certifying Genuine versus Repackaged Forecasting Skill
8. Blind directions of physical learning networks: where to measure and what to measure
9. Comparative Evaluation of Random, Sobol, and Dragon-Family-Guided PSO and Quantum Inspired PSO on CEC 2022 Benchmarks and Cleveland Heart Disease Wrapper Feature Selection
10. Tensorization is a powerful but underexplored tool for compression and interpretability of neural networks
11. Architecture--Optimization Co-Design for Physics-Informed Neural Networks via Layer-wise Coordinate Adaptation and Gradient Conflict Resolution
12. TopK Sparse Autoencoders Across Three Model Architectures: Dictionary Collapse, Dense-Feature Degeneracy, and the Limits of Activation-Pattern Feature Matching
13. TopK Sparse Autoencoders Across Three Model Architectures: Dictionary Collapse, Dense-Feature Degeneracy, and the Limits of Activation-Pattern Feature Matching
14. Representation Multiplicity in Causal Forests
15. Improvement of chaotic maps for k-NN classification using Lévy-flight whale optimization: multiple dataset comparison
16. The Information Complexity of Decision Trees
17. Generalization in VAE and Diffusion Models: A Unified Information-Theoretic Analysis
18. From Rashomon Theory to PRAXIS: Efficient Decision Tree Rashomon Sets
19. When Does Scale-Invariant Optimization Become Unstable? An Exact Schedule Law with Weight Decay
20. The Dynamics of Generalization in Deep Learning