Zobrazeno 1 - 10
of 265
pro vyhledávání: '"Bruza, Peter"'
Amidst the array of quantum machine learning algorithms, the quantum kernel method has emerged as a focal point, primarily owing to its compatibility with noisy intermediate-scale quantum devices and its promise to achieve quantum advantage. This met
Externí odkaz:
http://arxiv.org/abs/2407.13809
This article extends the combinatorial approach to support the determination of contextuality amidst causal influences. Contextuality is an active field of study in Quantum Cognition, in systems relating to mental phenomena, such as concepts in human
Externí odkaz:
http://arxiv.org/abs/2202.08209
In this paper, we propose a novel lightweight relation extraction approach of structural block driven - convolutional neural learning. Specifically, we detect the essential sequential tokens associated with entities through dependency analysis, named
Externí odkaz:
http://arxiv.org/abs/2103.11356
There has been a growing interest in model-agnostic methods that can make deep learning models more transparent and explainable to a user. Some researchers recently argued that for a machine to achieve a certain degree of human-level explainability,
Externí odkaz:
http://arxiv.org/abs/2103.04244
Autor:
Moreira, Catarina, Chou, Yu-Liang, Velmurugan, Mythreyi, Ouyang, Chun, Sindhgatta, Renuka, Bruza, Peter
The use of sophisticated machine learning models for critical decision making is faced with a challenge that these models are often applied as a "black-box". This has led to an increased interest in interpretable machine learning, where post hoc inte
Externí odkaz:
http://arxiv.org/abs/2007.10668
In this paper, by mapping datasets to a set of non-linear coherent states, the process of encoding inputs in quantum states as a non-linear feature map is re-interpreted. As a result of this fact that the Radial Basis Function is recovered when data
Externí odkaz:
http://arxiv.org/abs/2007.07887
This paper uses deformed coherent states, based on a deformed Weyl-Heisenberg algebra that unifies the well-known SU(2), Weyl-Heisenberg, and SU(1,1) groups, through a common parameter. We show that deformed coherent states provide the theoretical fo
Externí odkaz:
http://arxiv.org/abs/2006.02904
Publikováno v:
Proceedings of the 42nd Annual Meeting of the Cognitive Science Society, 2020
This paper provides the foundations of a unified cognitive decision-making framework (QulBIT) which is derived from quantum theory. The main advantage of this framework is that it can cater for paradoxical and irrational human decision making. Althou
Externí odkaz:
http://arxiv.org/abs/2006.02256
This article presents a unified probabilistic framework that allows both rational and irrational decision making to be theoretically investigated and simulated in classical and quantum games. Rational choice theory is a basic component of game theore
Externí odkaz:
http://arxiv.org/abs/2004.03474
This paper explores interpretability techniques for two of the most successful learning algorithms in medical decision-making literature: deep neural networks and random forests. We applied these algorithms in a real-world medical dataset containing
Externí odkaz:
http://arxiv.org/abs/2002.09192