The Symbolic Interior Point Method

Authors: Martin Mladenov, Vaishak Belle, Kristian Kersting

AAAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental To evaluate the performance of the approach, we implemented the entire pipeline described here... We applied the Symbolic IPM on the problem of computing the value function of a family of Markov decision processes... We compared our approach to a matrix implementation of the primal-dual barrier method... The results are summarized in Fig. 2(top).
Researcher Affiliation Academia Martin Mladenov TU Dortmund University, Germany... Vaishak Belle University of Edinburgh, UK... Kristian Kersting TU Dortmund University, Germany
Pseudocode Yes Algorithm 1: Primal-Dual Barrier Method... Algorithm 2: Conjugate Gradient Method
Open Source Code No The paper mentions implementing the pipeline and comparing against reference MATLAB code, but does not provide any link or explicit statement about the public availability of their own source code.
Open Datasets Yes To address (Q1) and (Q2), we applied the symbolic IPM on the problem of computing the value function of a family of Markov decision processes used in (Hoey et al. 1999)... We apply the Symbolic IPM to the BPDN reformulation of (Fountoulakis, Gondzio, and Zhlobich 2014), with the Walsh matrix specified symbolically, recovering random sparse vectors.
Dataset Splits No The paper does not explicitly mention validation sets, specific dataset splits (e.g., percentages, counts), or cross-validation strategies.
Hardware Specification No The paper does not provide specific hardware details (e.g., CPU, GPU models, memory) used for running the experiments.
Software Dependencies No The paper mentions that the compiler to ADDs is 'based on the popular CUDD package' and compares to 'MATLAB code'. However, it does not provide specific version numbers for these or any other software dependencies used in their implementation.
Experiment Setup Yes We compared our approach to a matrix implementation of the primal-dual barrier method, both algorithms terminate at the same relative residual, 10-5.