arXiv Machine Learning
Jul 3
Optimal Stabilizer Testing and Learning with Limited Quantum Memory
arXiv:2607. 02444v1 Announce Type: cross Abstract: We study stabilizer state testing and learning with limited coherent quantum memory.
Reconquering Bell sampling on qudits: stabilizer learning and testing, quantum pseudorandomness bounds, and more
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Hugging Face Trending Papers
Jul 2
Optimal Stabilizer Testing and Learning with Limited Quantum Memory
We study stabilizer state testing and learning with limited coherent quantum memory. Here an algorithm sequentially receives copies of an unknown $n$-qubit state, but may keep only $k$ qubits of coherent quantum memory between measurements.
arXiv Machine Learning
Jun 11
Quantum Occam Learning: Sample-Supported Expressibility for Circuit-Based Quantum Learning
arXiv:2606. 12211v1 Announce Type: cross Abstract: A central principle in quantum machine learning is that an ansatz should be expressive enough to represent the quantum data of interest.
arXiv Machine Learning
Jun 3
Coherent Swap Regret and Channel-Proof Learning
arXiv:2606. 02655v1 Announce Type: cross Abstract: External regret certifies stability only against replacing one's behavior by a fixed alternative.
arXiv Machine Learning
Aug 12
The Exact Replica Threshold for Nonlinear Moments of Quantum States
arXiv:2604. 22627v2 Announce Type: replace-cross Abstract: Joint measurements on multiple copies of a quantum state provide access to nonlinear observables such as $\operatorname{tr}(\rho^t)$, but whether replica number marks a sharp information-theoretic resource boundary has remained unclear.
arXiv Machine Learning
Jun 25
Minimax PAC Bounds for Learning in Exogenous Contextual MDPs
arXiv:2606. 25170v1 Announce Type: cross Abstract: We study PAC learning in tabular discounted Markov decision processes with exogenous i.
arXiv Machine Learning
Jul 21
AQKA: Active Quantum Kernel Acquisition Under a Shot Budget
arXiv:2605. 14672v2 Announce Type: replace Abstract: Estimating an $N \times N$ quantum kernel from circuit fidelities requires $\Theta(N^2 S)$ measurement shots, the dominant bottleneck for deployment on near-term hardware.
arXiv Machine Learning
Jul 31
Quantum Speedups for Stochastic Optimization with Heavy-Tailed Noise
arXiv:2607. 25492v2 Announce Type: replace Abstract: We study stochastic optimization with heavy-tailed gradient noise.
arXiv Machine Learning
Jun 19
Effective Dimension Governs Generalization in Quantum Kernel Vision Models
arXiv:2606. 20183v1 Announce Type: new Abstract: Recent quantum vision models-quantum vision transformers and quantum convolutional networks-report two striking but unexplained empirical phenomena: (i) ansatze with more, or more uniformly distributed, entanglement generalize better, and (ii) injecting quantum noise can improve test accuracy rather than degrade it.
Hugging Face Trending Papers
Jul 7
Provable learning separation for predicting time-evolution of quantum many-body systems
Given that quantum computers are naturally suited to simulate the behavior of quantum many-body systems, an immediate question arises: can one formulate physically motivated quantum machine learning (QML) tasks that exhibit learning separations? We address this problem by studying the learnability of quantum many-body dynamics from the perspective of probably approximately correct (PAC)-learning.
arXiv Machine Learning
Sep 10
Tight Lower Bounds for State Tomography with Limited Entanglement
arXiv:2609.05718v1 Announce Type: cross Abstract: We study state tomography when each measurement acts on at most $k$ fresh copies and no quantum memory is retained between blocks. We prove a lower b...
Hugging Face Trending Papers
Sep 9
Optimal Low-Rank Quantum State Tomography with Bounded-Sample Joint Measurements
We determine the optimal sample complexity of low-rank quantum state tomography when each measurement may act jointly on at most $t$ samples. For sufficiently small $\varepsilon$, estimating an unknow...