4 papers
On Quantum Learning Advantage Under Symmetries
Tuyen Nguyen, Mária Kieferová, Amira Abbas
Symmetry underlies many of the most effective classical and quantum learning algorithms, yet whether quantum learners can gain a fundamental advantage under symmetry-imposed struct…
TunnElQNN: A Hybrid Quantum-classical Neural Network for Efficient Learning
A. H. Abbas
Hybrid quantum-classical neural networks (HQCNNs) represent a promising frontier in machine learning, leveraging the complementary strengths of both models. In this work, we propos…
QuantumBoost: A lazy, yet fast, quantum algorithm for learning with weak hypotheses
Amira Abbas, Yanlin Chen, Tuyen Nguyen +1
The technique of combining multiple votes to enhance the quality of a decision is the core of boosting algorithms in machine learning. In particular, boosting provably increases de…
Nearly optimal algorithms to learn sparse quantum Hamiltonians in physically motivated distances
Amira Abbas, Nunzia Cerrato, Francisco Escudero Gutiérrez +3
We study the problem of learning Hamiltonians that are -sparse in the Pauli basis, given access to their time evolution. Although Hamiltonian learning has been extensively i…