Latest Research in Stochastic Gradient Optimization Techniques

Top Research Topics in Stochastic Gradient Optimization Techniques

• Machine Learning — 4 papers
• Machine Learning — 3 papers
• Stochastic Gradient Optimization Techniques — 2 papers
• Statistical Mechanics and Entropy — 1 papers
• Statistics Theory — 1 papers
• Face and Expression Recognition — 1 papers
• Optimization and Control — 1 papers
• Quantum Mechanics and Applications — 1 papers
• Statistical Methods and Inference — 1 papers
• Advanced Multi-Objective Optimization Algorithms — 1 papers

Highest-Cited Papers

1. Residual distribution predictive systems (1 citations)
2. Zulfia Laws of Statistical Estimation: Φ-Force Over Information Curvature
3. Provable Guarantees and Efficient Learning of Structural Equation Models with Latent Confounders
4. Multi-source conformal prediction: leveraging heterogeneity via localization
5. Conformalized Super Learner
6. Are Bayesian networks typically faithful?
7. Finite Sample Complexity Analysis of Binary Segmentation
8. Percolation Dynamics in Optimization : Variance Cascades and Discrete Scale Invariance
9. The Multiple Timescales of Gradient Descent on the Edge of Stability: A Perturbative Derivation of the Central Flow
10. A Unified Perspective on Conformal Prediction and Wasserstein Distributionally Robust Optimization for Uncertainty Quantification
11. Algebraic Geometric Empirical Process (AGEP) Theory of Deep Learning Dynamics
12. Confidence Revisited: The Distribution of Information
13. Learning between the peaks: sharp asymptotics for kernel ridge regression under power-law anisotropy
14. Geometry-Constrained Kolmogorov-Arnold Networks: Learning Edge Geometry via Banach Duality
15. Statistical guarantees for italic k k $\textit{k}$ -degree neural networks via scale regularization
16. Estimating lower bound functions in surrogate optimization