Results 91 to 100 of about 8,042,432 (193)

VQE-generated quantum circuit dataset for machine learning

Physical Review Research
Quantum machine learning has the potential to computationally outperform classical machine learning, but it is not yet clear whether it will actually be valuable for practical problems.
Akimoto Nakayama, Kosuke Mitarai, Leonardo Placidi, Takanori Sugimoto, Keisuke Fujii   +4 more
doaj   +1 more source

Quantum Machine Learning: Foundational Principles to Practical Applications

IEEE Access
Quantum Machine Learning (QML) has emerged as a promising interdisciplinary field that combines quantum computing with machine learning to address complex computational problems.
Ashis Kumar Pati, Rajesh Vayyala, Kuldip Mohanty, Uttamita Das   +3 more
doaj   +1 more source

Targeted Active Learning for Bayesian Decision-Making

Active learning is usually applied to acquire labels of informative data points in supervised learning, to maximize accuracy in a sample-efficient way.
Kaski, Samuel, Tiulpin, Aleksei, Filstroff, Louis, Sundin, Iiris, Kylmäoja, Juuso, Mikkola, Petrus   +5 more
core   +1 more source

Toward structure-preserving quantum encodings

Physical Review Research
Harnessing the potential computational advantage of quantum computers for machine learning tasks relies on the uploading of classical data onto quantum computers through what are commonly referred to as quantum encodings. The choice of such encodings may
Arthur J. Parzygnat, Tai-Danae Bradley, Andrew Vlasic, Anh Pham   +3 more
doaj   +1 more source

Learning reduced representations for quantum classifiers

Data sets that are specified by a large number of features are currently outside the area of applicability for quantum machine learning algorithms.
Grossi, Michele, Belis, Vasilis, Vallecorsa, Sofia, Odagiu, Patrick, Dissertori, Günther, Tavernelli, Ivano, Schulze, Lennart, Reiter, Florentin, Barkoutsos, Panagiotis   +8 more
core   +1 more source

Learning labelled dependencies in machine translation evaluation [PDF]

, 2009
Recently novel MT evaluation metrics have been presented which go beyond pure string matching, and which correlate better than other existing metrics with human judgements.
He, Yifan, Way, Andy
core   +2 more sources

Quantum Machine Learning for Enhanced Cybersecurity: Proposing a Hypothetical Framework for Next-Generation Security Solutions

The rapid evolution of cyber threats has rendered conventional security approaches inadequate for managing increasingly sophisticated risks. This study introduces a Quantum Machine Learning Cybersecurity Framework that leverages quantum computing and ...
Amin, Al, Mahmud, Shakik, Hossain, Forhad, Hasan, Kamrul   +3 more
core   +1 more source

Hands-On Introduction to Quantum Machine Learning

Proceedings of the International Florida Artificial Intelligence Research Society Conference
This tutorial covers a hands-on introduction to quantum machine learning. Foundational concepts of quantum information science (QIS) are presented (qubits, single and multiple qubit gates, measurements, and entanglement).
Muhammad Ismail, Mohamed Shaban, Samuel Yen-Chi Chen   +2 more
doaj   +1 more source

A Multi-Objective Evaluation Framework for Analyzing Utility-Fairness Trade-Offs in Machine Learning Systems

The evaluation of fairness models in Machine Learning involves complex challenges, such as defining appropriate metrics, balancing trade-offs between utility and fairness, and there are still gaps in this stage. This work presents a novel multi-objective
Özbulak, Gökhan, Jimenez-del-Toro, Oscar, Anjos, André, Berton, Lilian, Fatoretto, Maíra   +4 more
core   +1 more source

Guided quantum compression for high dimensional data classification

Machine Learning: Science and Technology
Quantum machine learning provides a fundamentally different approach to analyzing data. However, many interesting datasets are too complex for currently available quantum computers.
Vasilis Belis, Patrick Odagiu, Michele Grossi, Florentin Reiter, Günther Dissertori, Sofia Vallecorsa   +5 more
doaj   +1 more source