Q-Intersection Algorithms for Constraint-Based Robust Parameter Estimation
Authors: Clement Carbonnel, Gilles Trombettoni, Philippe Vismara, Gilles Chabert
AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We present a computational study of the q-intersection. We also propose a fast heuristic and a sophisticated exact q-intersection algorithm. First experiments show that our exact algorithm outperforms the existing one while our heuristic performs an efficient filtering on hard problems. |
| Researcher Affiliation | Academia | Clement Carbonnel LAAS-CNRS Universit e Toulouse, France carbonnel@laas.fr Gilles Trombettoni LIRMM Universit e Montpellier, France gilles.trombettoni@lirmm.fr Philippe Vismara LIRMM Sup Agro Montpellier, France vismara@lirmm.fr Gilles Chabert LINA EMN Nantes, France gilles.chabert@mines-nantes.fr |
| Pseudocode | Yes | Algorithm 1: core F(S, q); Algorithm 2: QInter2(S, q); Algorithm 3: Find Min Q(S, q, d, N) |
| Open Source Code | Yes | The code and instances of our experiments are available in the release 2.1.2 (and subsequent) of IBEX (www.ibex-lib.org). |
| Open Datasets | No | The paper uses "randomly generated instances" for its experiments, as stated in Section 5. It does not refer to a publicly available or open dataset with a specific link or citation. |
| Dataset Splits | No | The paper describes generating instances and comparing algorithms, but it does not specify training, validation, or test dataset splits. The experimental setup is not structured like a typical machine learning model evaluation with explicit data splits for these purposes. |
| Hardware Specification | Yes | All experiments have been performed on a 2.2Ghz Intel Core i7. |
| Software Dependencies | Yes | We have implemented the projective filtering, core F and QInter2 in the C++ numerical constraint programming library Ibex (Chabert and Jaulin 2009; Chabert 2014), which originally shipped with the grid algorithm. Q-clique problems are solved using Cliquer (Ostergard 2002). The code and instances of our experiments are available in the release 2.1.2 (and subsequent) of IBEX (www.ibex-lib.org). |
| Experiment Setup | Yes | The center of each of the p boxes in S and its radius in every dimension are uniformly drawn in [0, L]. The two values of qc we have studied are 0.3 p (many outliers) and 0.8 p (few outliers). The corresponding scaling factor (for transforming each random instance into a difficult one) is determined empirically. |