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Found 5 papers, 1 papers with code
Smoothing Structured Decomposable Circuits
Further, for the important case of All-Marginals, we show a more efficient linear-time algorithm.
Time-Space Tradeoffs for Learning from Small Test Spaces: Learning Low Degree Polynomial Functions
We develop an extension of recently developed methods for obtaining time-space tradeoff lower bounds for problems of learning from random test samples to handle the situation where the space of tests is signficantly smaller than the space of inputs, a class of learning problems that is not handled by prior work.
New Limits for Knowledge Compilation and Applications to Exact Model Counting
We use this relationship to prove exponential lower bounds on the SDD size for representing a large class of problems that occur naturally as queries over probabilistic databases.
Symmetric Weighted First-Order Model Counting
For the combined complexity, we prove that, for every fragment FO$^{k}$, $k\geq 2$, the combined complexity of FOMC (or WFOMC) is #P-complete.
Lower Bounds for Exact Model Counting and Applications in Probabilistic Databases
The best current methods for exactly computing the number of satisfying assignments, or the satisfying probability, of Boolean formulas can be seen, either directly or indirectly, as building 'decision-DNNF' (decision decomposable negation normal form) representations of the input Boolean formulas.
