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Proving Conjectures Acquired by Composing Multiple Biases
We present the proofs of the conjectures mentioned in the paper published in the proceedings of the 2024 AAAI conference [1], and discovered by the decomposition methods presented in the same paper.
Partial Queries for Constraint Acquisition
Learning constraint networks is known to require a number of membership queries exponential in the number of variables.
Classifying Pattern and Feature Properties to Get a $Θ(n)$ Checker and Reformulation for Sliding Time-Series Constraints
Given, a sequence $\mathcal{X}$ of $n$ variables, a time-series constraint ctr using the Sum aggregator, and a sliding time-series constraint enforcing the constraint ctr on each sliding window of $\mathcal{X}$ of $m$ consecutive variables, we describe a $\Theta(n)$ time complexity checker, as well as a $\Theta(n)$ space complexity reformulation for such sliding constraint.
Counting-Based Search: Branching Heuristics for Constraint Satisfaction Problems
Designing a search heuristic for constraint programming that is reliable across problem domains has been an important research topic in recent years.
