Fast Quantum Algorithms for Learning Linear Threshold Functions

arXiv:2609.40331 · quant-ph · Submitted 2026-09-30 · Read on arXiv

quant-ph

Submitted: 2026-09-30

Updated: 2026-10-05

Terminology

• Query Complexity — 31× in this paper · explained in 2 episodes
• Trace — 8× in this paper · explained in 2 episodes
• Trace Distance — 7× in this paper · explained in 3 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Quantization — 4× in this paper · explained in 12 episodes
• Annual ACM Symposium on Theory of Computing — 3× in this paper
• Conference on Learning Theory — 3× in this paper
• Sample Complexity — 3× in this paper · explained in 15 episodes
• Active Learning — 2× in this paper · explained in 6 episodes
• Hilbert Space — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Semidefinite Program (SDP) — 2× in this paper · explained in 2 episodes
• Ambient Dimension — 1× in this paper · explained in 1 episode
• Annual Symposium on Foundations of Computer Science — 1× in this paper
• Generalization — 1× in this paper · explained in 13 episodes

Sources

• Active and passive learning of linear separators under log-concave distributions
• Quantum algorithms and lower bounds for convex optimization
• A new quantum ripple-carry addition circuit
• Contributions of Issai Schur to Analysis
• A Brief Introduction to Quantum Query Complexity
• Efficient Quantum Hermite Transform
• Low-depth quantum symmetrization
• Provable Advantage in Quantum PAC Learning

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