arXiv:2607. 21188v1 Announce Type: new Abstract: The Single Constant Multiplication problem is a fundamental NP-hard optimization task in hardware design, which seeks to decompose a fixed constant using only additions, subtractions, and bit-shifts.
Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.
arXiv:2412. 18134v5 Announce Type: replace Abstract: Randomized self-reductions (RSRs) express $f(x)$ using $f$ evaluated at random correlated points, enabling self-correcting programs, instance-hiding protocols, and applications in complexity theory and cryptography.
arXiv:2607. 16523v1 Announce Type: new Abstract: One of the main strengths of Constraint Programming is the ability to reduce the search space via propagation.
arXiv:2510. 04500v3 Announce Type: replace Abstract: This work demonstrates how increasing the number of neurons in a network without increasing its total number of non-zero parameters improves performance.
arXiv:2608. 00029v1 Announce Type: cross Abstract: The performance of deep learning models at scale relies heavily on how effectively high-level mathematical operations are mapped to underlying physical hardware.
arXiv:2505. 23696v2 Announce Type: replace Abstract: Solving systems of polynomial equations, particularly those with finitely many solutions, is a crucial challenge across many scientific fields.
arXiv:2601. 13731v2 Announce Type: replace-cross Abstract: Symbolic computation, powered by modern computer algebra systems, has important applications in mathematical reasoning through exact deep computations.