Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:28:16.563095Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 84 of 84 outbound references and 0 inbound Pith citation observations for arXiv:2507.08543.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:28:16.563095Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
84 of 84 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation df40467e-6b8c-4016-986e-7a6d8863f53c · outbound
Quantum Algorithms for Projection-Free Sparse Convex Optimization Linear convergence of a frank-wolfe type algorithm over trace-norm balls
Reference 1
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Quantum Algorithms for Projection-Free Sparse Convex Optimization Variable time amplitude amplification and a faster quantum algorithm for solving systems of linear equations
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Quantum Algorithms for Projection-Free Sparse Convex Optimization Quantum speedups for linear programming via interior point meth- ods
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Reference 5
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Quantum Algorithms for Projection-Free Sparse Convex Optimization Quantum amplitude amplification and estimation
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Quantum Algorithms for Projection-Free Sparse Convex Optimization A tight upper bound on the rate of convergence of frank-wolfe algorithm
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Quantum Algorithms for Projection-Free Sparse Convex Optimization The power of block-encoded matrix powers: Improved regression techniques via faster hamiltonian simulation
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Quantum Algorithms for Projection-Free Sparse Convex Optimization Projection-free online optimization with stochastic gradient: From convexity to submodularity
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Quantum Algorithms for Projection-Free Sparse Convex Optimization Lifted coordinate descent for learning with trace- norm regularization
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Quantum Algorithms for Projection-Free Sparse Convex Optimization A Quantum Algorithm for Finding the Minimum
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Reference 30
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Quantum Algorithms for Projection-Free Sparse Convex Optimization Accelerated training for matrix-norm regulariza- tion: A boosting approach
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Quantum Algorithms for Projection-Free Sparse Convex Optimization By Theorem 1 of [24], the algorithm finds the minimum gi(x) with probability 1 /2, O( √ d) applications of Ug, U † g and O( √ d) elementary gates
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