Latest Research in Information Theory

Top Research Topics in Information Theory

• Machine Learning — 17 papers
• Machine Learning — 11 papers
• Methodology — 3 papers
• Stochastic Gradient Optimization Techniques — 3 papers
• Information Theory — 2 papers
• Neural and Evolutionary Computing — 2 papers
• Random Matrices and Applications — 2 papers
• Face and Expression Recognition — 2 papers
• Tensor decomposition and applications — 2 papers
• Machine Learning and ELM — 1 papers

Highest-Cited Papers

1. A More Precise Elbow Method For Optimum K-means Clustering (7 citations)
2. A generalized robust twin extreme learning machine for robust classification under noisy data
3. Online Supervised Dimension Reduction with Random Features: Diagnostics and Computational Trade-offs
4. Low-rank Orthogonalization for Large-scale Matrix Optimization with Applications to Foundation Model Training
5. Learning Submanifolds for Subsequent Inference on Random Dot Product Graphs, Part 1: Theory
6. Out-of-Sample Embedding with Proximity Data: Projection versus Restricted Reconstruction
7. Supervised Random Feature Regression via Projection Pursuit
8. Universal Feature Selection with Noisy Observations and Weak Symmetry Conditions
9. On the disintegration of the stochastic majority vote: From PAC-Bayesian bounds to a self-bounding algorithm
10. Riemannian Deep Learning: Modules, Networks, and Geometries
11. Dead Directions: Geometric Singular Learning
12. Structural Fusion of Bayesian Networks with Limited Treewidth Using Genetic Algorithms
13. Geometry-Aware Bayesian Parameter-Efficient Fine-Tuning on the Stiefel Manifold via Stein Variational Gradient Descent
14. Linear and Quadratic Discriminant Analysis: Tutorial
15. Exact Spectral Degeneracies in Kernel Discriminant Operators Under Small-Sample Designs
16. Exact Spectral Degeneracies in Kernel Discriminant Operators Under Small-Sample Designs
17. Robust ℓp-Norm Two-Dimensional Discriminative Clustering for Image Data
18. A Fundamental Limit in Decentralized Decision-Making
19. A New Perspective on Clustering: A Mixed-norm Model and its Solution by Progressive Integer Programming
20. Revisiting Thinning Methods for Kernel Learning Problems