scientific article; zbMATH DE number 7008327
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Publication:4614114
zbMath1441.68056MaRDI QIDQ4614114
Srinivasan Arunachalam, Ronald de Wolf
Publication date: 30 January 2019
Full work available at URL: http://jmlr.csail.mit.edu/papers/v19/18-195.html
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Computational learning theory (68Q32) Quantum computation (81P68) Quantum algorithms and complexity in the theory of computing (68Q12)
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Quantum learning Boolean linear functions w.r.t. product distributions ⋮ Learning bounds for quantum circuits in the agnostic setting ⋮ Learning quantum finite automata with queries ⋮ Quantum science and quantum technology ⋮ Unnamed Item ⋮ Quantum learning of concentrated Boolean functions ⋮ A quantum algorithm of K-means toward practical use
Cites Work
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- The quantum query complexity of learning multilinear polynomials
- On the distinguishability of random quantum states
- The geometry of quantum learning
- New bounds on classical and quantum one-way communication complexity
- Decision theoretic generalizations of the PAC model for neural net and other learning applications
- Sample size lower bounds in PAC learning by Algorithmic Complexity Theory
- Sharper bounds for Gaussian and empirical processes
- Toward efficient agnostic learning
- An efficient membership-query algorithm for learning DNF with respect to the uniform distribution
- Improved lower bounds for learning from noisy examples: An information-theoretic approach
- General bounds on the number of examples needed for learning probabilistic concepts
- An improved lower bound on query complexity for quantum PAC learning
- Quantum speed-up for unsupervised learning
- Exact lower bounds for the agnostic probably-approximately-correct (PAC) machine learning model
- Fast learning rates in statistical inference through aggregation
- Quantum algorithms for learning and testing juntas
- Improved bounds on quantum learning algorithms
- Learnability and the Vapnik-Chervonenkis dimension
- The learnability of quantum states
- Optimal measurements for the dihedral hidden subgroup problem
- A theory of the learnable
- Learning DNF over the Uniform Distribution Using a Quantum Example Oracle
- Cryptographic limitations on learning Boolean formulae and finite automata
- Quantum Complexity Theory
- On quantum detection and the square-root measurement
- Equivalences and Separations Between Quantum and Classical Learnability
- Designing optimal quantum detectors via semidefinite programming
- Reversing quantum dynamics with near-optimal quantum and classical fidelity
- Neural Network Learning
- Analysis of Boolean Functions
- Understanding Machine Learning
- On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities
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