Potential-Function Proofs for First-Order Methods
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Abstract (arXiv)
This note discusses proofs for convergence of first-order methods based on simple potential-function arguments. We cover methods like gradient descent (for both smooth and non-smooth settings), mirror descent, and some accelerated variants.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 13 Dec 2017.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 1; 2026: 1.
4 papers.
- 2022From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descentcited by 5
- 2024Stacking as Accelerated Gradient Descentcited by 5
- 2025A Class of Accelerated Fixed-Point-Based Methods with Delayed Inexact Oracles and Its Applicationscited by 1
- 2026Exact information accounting for SGD methodscited by 0
- 2026Exact information accounting for SGD methods30 Sep 2026
- 2025A Class of Accelerated Fixed-Point-Based Methods with Delayed Inexact Oracles and Its Applications15 Dec 2025
- 2024Stacking as Accelerated Gradient Descent8 Mar 2024
- 2022From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent13 Oct 2022