LPC-SM is a hybrid architecture separating local attention, persistent memory, predictive correction, and control with ONT for memory writes, showing loss reductions on 158M-parameter models up to 4096-token contexts.
SIAM Review 38(3), 367–426 (1996)
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Extends semigroup methods and measurable selection results to prove global existence for partially nonautonomous evolution inclusion systems under Hausdorff continuity and convexity conditions on couplings.
New inconsistent alternating projection scheme for basis pursuit with linear convergence proofs and competitive benchmarks.
Investigates Fejér* monotonicity in Hilbert spaces for optimization algorithms, its weak and strong convergence, and comparisons to quasi-Fejér-type notions via examples.
citing papers explorer
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LPC-SM: Local Predictive Coding and Sparse Memory for Long-Context Language Modeling
LPC-SM is a hybrid architecture separating local attention, persistent memory, predictive correction, and control with ONT for memory writes, showing loss reductions on 158M-parameter models up to 4096-token contexts.
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Nonautonomous systems of evolution inclusions
Extends semigroup methods and measurable selection results to prove global existence for partially nonautonomous evolution inclusion systems under Hausdorff continuity and convexity conditions on couplings.
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Basis pursuit by inconsistent alternating projections
New inconsistent alternating projection scheme for basis pursuit with linear convergence proofs and competitive benchmarks.
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Fej\'er* monotonicity in optimization algorithms
Investigates Fejér* monotonicity in Hilbert spaces for optimization algorithms, its weak and strong convergence, and comparisons to quasi-Fejér-type notions via examples.