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Shi-Jie Pan

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Preprint Sep 2026

Data-Driven MPC with Adaptively Sampled Non-Expert Demonstrations: Performance Guarantees and Sample Complexity

A memory-based, nonparametric policy is proposed that constructs a Lipschitz-regularized upper envelope of the finite- horizon surrogate value function, which serves as an explicit upper bound on the value of the resulting policy, thereby providing a computable performance certificate while bypassing explicit optimizat...

Shi-Jie Pan, Agustin Castellano, Enrique Mallada · 0 citations
Jul 2026

Memory-Computation Tradeoffs in Semi Amortized Parametric Optimization

A general proof framework is provided that explicitly quantifies the memory cost of acceleration---how much offline memory is required to achieve a prescribed speedup over the unaided online optimizer---and identifies two key quantities driving this cost: the convergence rate of the online optimizer and the Lipschitz s...

Shijie Pan, Agustin Castellano, Zeyu Shen et al. · 0 citations

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