3 papers
quant-ph2025
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…
quant-ph2025
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…
cs.LG2021
Effective dimension of machine learning models
Amira Abbas, David Sutter, Alessio Figalli +1
Making statements about the performance of trained models on tasks involving new data is one of the primary goals of machine learning, i.e., to understand the generalization power…