Convex Optimization Is Free When Accuracy Is Expensive
math.OC, cs.LG, stat.ML
Submitted: 2026-09-28
Updated: 2026-09-28
Terminology
Sources
- On the Convergence of SGD with Biased Gradients
- Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity
- Scaling Laws for Autoregressive Generative Modeling
- Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning
- Multi-level Monte-Carlo Gradient Methods for Stochastic Optimization with Biased Oracles
- Deep Learning as a Convex Paradigm of Computation: Minimizing Circuit Size with ResNets
- Polynomial Speedup in Diffusion Models with the Multilevel Euler-Maruyama Method
- Scaling Laws for Neural Language Models
- Optimal inexactness schedules for Tunable Oracle based Methods
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