We lifted 1 functions out of this paper's own repositories and ran 0 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| carlosherediapimienta/numerical_simulations_nonlocal | canonical | 0 of 1 |
| Function | Status | Where it lives |
|---|---|---|
| chunked_vmap | Not yet run | carlosherediapimienta/numerical_simulations_nonlocal/solvers/adagradsolver.py code served (permissive licence) · get_code("f0c2daedaa2e12d7") |
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In this paper, we propose a continuous-time formulation for the AdaGrad, RMSProp, and Adam optimization algorithms by modeling them as first-order integro-differential equations. We perform numerical simulations of these equations, along with stability and convergence analyses, to demonstrate their validity as accurate approximations of the original algorithms. Our results indicate a strong agreement between the behavior of the continuous-time models and the discrete implementations, thus providing a new perspective on the theoretical understanding of adaptive optimization methods.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2411.09734")
get_code_for_paper("2411.09734")
have("2411.09734")
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