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A SAT-based Resolution of Lam's Problem

Bright, Curtis, Cheung, Kevin K. H., Stevens, Brett, Kotsireas, Ilias, Ganesh, Vijay

arXiv.org Artificial Intelligence

In 1989, computer searches by Lam, Thiel, and Swiercz experimentally resolved Lam's problem from projective geometry$\unicode{x2014}$the long-standing problem of determining if a projective plane of order ten exists. Both the original search and an independent verification in 2011 discovered no such projective plane. However, these searches were each performed using highly specialized custom-written code and did not produce nonexistence certificates. In this paper, we resolve Lam's problem by translating the problem into Boolean logic and use satisfiability (SAT) solvers to produce nonexistence certificates that can be verified by a third party. Our work uncovered consistency issues in both previous searches$\unicode{x2014}$highlighting the difficulty of relying on special-purpose search code for nonexistence results.


Analog Neural Networks as Decoders

Erlanson, Ruth, Abu-Mostafa, Yaser

Neural Information Processing Systems

In turn, KWTA networks can be used as decoders of a class of nonlinear error-correcting codes. By interconnecting suchKWTA networks, we can construct decoders capable of decoding more powerful codes. We consider several families of interconnected KWTAnetworks, analyze their performance in terms of coding theory metrics, and consider the feasibility of embedding such networks in VLSI technologies.


Analog Neural Networks as Decoders

Erlanson, Ruth, Abu-Mostafa, Yaser

Neural Information Processing Systems

In turn, KWTA networks can be used as decoders of a class of nonlinear error-correcting codes. By interconnecting such KWTA networks, we can construct decoders capable of decoding more powerful codes. We consider several families of interconnected KWTA networks, analyze their performance in terms of coding theory metrics, and consider the feasibility of embedding such networks in VLSI technologies.


Analog Neural Networks as Decoders

Erlanson, Ruth, Abu-Mostafa, Yaser

Neural Information Processing Systems

In turn, KWTA networks can be used as decoders of a class of nonlinear error-correcting codes. By interconnecting such KWTA networks, we can construct decoders capable of decoding more powerful codes. We consider several families of interconnected KWTA networks, analyze their performance in terms of coding theory metrics, and consider the feasibility of embedding such networks in VLSI technologies.