General Bounds on Satisfiability Thresholds for Random CSPs via Fourier Analysis

Authors: Colin Wei, Stefano Ermon

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

Reproducibility Variable Result LLM Response
Research Type Experimental We demonstrate that our bounds can be easily instantiated to obtain thresholds for many constraint functions that had not been previously studied, and evaluate them experimentally. [...] We empirically test our bounds with the goal of examining their tightness.
Researcher Affiliation Academia Colin Wei and Stefano Ermon Computer Science Department Stanford University {colinwei,ermon}@cs.stanford.edu
Pseudocode No The paper does not contain any structured pseudocode or algorithm blocks.
Open Source Code No The paper does not provide concrete access to source code for the methodology described.
Open Datasets No For our experiments, we randomly generate CSP formulas based on TRIBESa,b. The paper describes a method for generating problem instances rather than using a public dataset, and no information is provided on accessing these generated instances.
Dataset Splits No The paper describes generating random CSP formulas and running experiments on them, not splitting a pre-existing dataset into train/validation/test sets.
Hardware Specification No The paper does not provide specific hardware details (exact GPU/CPU models, processor types, or memory amounts) used for running its experiments.
Software Dependencies No The paper mentions using the 'Dimetheus1 random CSP solver' but does not provide a specific version number for it or any other software dependencies.
Experiment Setup Yes For our experiments, we randomly generate CSP formulas based on TRIBESa,b. [...] We show our results in Figure 3. As expected, our values for lower bounds rf,low are looser than the upper bounds rf,up. [...] Proportion of CSPs satisfiable out of 50 trials vs. r for tribes functions.