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Monotonic Algebras

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Passive Learning of Symbolic Automata over Monotonic Algebras

arXiv:2606.06050v1 Announce Type: new Abstract: Symbolic automata extend classical finite-state automata to handle large or infinite alphabets by labeling transitions by predicates coming from a boolean algebra. Many results from automata theory have been lifted to this model, and it has proved its usefulness for example in multiple software verification applications. Here, we tackle the passive learning problem of identification in the limit, i.e. learning a model from a sample without...

arXiv CS 5d ago

Convex algebras on an interval with semicontinuous monotone operations

arXiv:2603.14955v2 Announce Type: replace Abstract: In a recent work of Matteo Mio on compact quantitative equational theories (here compact means that all its consequences are derivable by means of finite proofs) convex algebras on the carrier set [0,1] whose operations are monotone and satisfy certain semicontinuity properties occurred. We fully classify those algebraic structures by giving an explicit construction of all possible convex operations on [0,1] possessing the mentioned...

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Kronecker products and iterated matrix multiplication

arXiv:2606.08363v1 Announce Type: new Abstract: We observe that the Kronecker product of tensors is the operation that converts the determinant polynomial into Cayley's first hyperdeterminant. We apply the Kronecker product to iterated matrix multiplication, which results in the hypercomputant, a VNP-complete and VW[1]-complete polynomial whose hardness we prove via the equivariance of the Kronecker product. The construction works over arbitrary commutative semirings and also for the tensor...

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Hessian-recovery-based C0 finite element methods for non-divergence form elliptic equations

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Evaluating Relational Reasoning in LLMs with REL

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State-Dependent Lyapunov Analysis of Rank-1 Matrix Factorization

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Variational Free Energy Pivot Selection for Pivoted Cholesky

arXiv:2606.01821v1 Announce Type: new Abstract: Pivoted Cholesky factorizations construct low-rank approximations of symmetric positive definite matrices by sequentially selecting pivots from the residual diagonal. Classical greedy and randomized rules, such as randomly pivoted Cholesky, target the algebraic trace-norm error of the residual. In many applications, however, the matrix enters a nonlinear matrix functional whose value, not the trace-norm error, determines solution quality, and...

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