Trust Region Preference Approximation: A simple and stable reinforcement learning algorithm for LLM reasoning We propose the Trust Region Preference Approximation (TRPA) algorithm ⚙️, which integrates ...

Algorithm Analysis: In-depth discussion of the implemented algorithms, including time and space complexity analysis. Comparative Study: A comparison between the exact and approximation methods in ...

Although efficient in a strictly theoretical sense (i.e., in the sense of taking polynomial versus exponential time), this algorithm for the permanent is not practical. Indeed, to date, no practical ...

Therefore, for all examples of SAP that admit an approximation scheme for the single-bin problem, we obtain an LP-based algorithm with (1 — 1/e — ε)-approximation and a local search algorithm with (½ ...

WENZHUAN ZHANG, HONGJIE WEI, MAXIMUM LIKELIHOOD ESTIMATION FOR SIMPLEX DISTRIBUTION NONLINEAR MIXED MODELS VIA THE STOCHASTIC APPROXIMATION ALGORITHM, The Rocky Mountain Journal of Mathematics, Vol.

CSCA 5424: Approximation Algorithms and Linear Programming CSCA 5424: Approximation Algorithms and Linear Programming Get a head start on program admission Preview this course in the non-credit ...

Gaussian mixture models are a very useful tool for modeling data distribution. While estimating parameters using the expectation-maximization algorithm, this approach does not scale well with big ...