Results 11 to 20 of about 154,109 (120)
Translation of Quantum Circuits into Quantum Turing Machines for Deutsch and Deutsch-Jozsa Problems [PDF]
arXiv.org, 2021 We want in this article to show the usefulness of Quantum Turing Machine (QTM) in a high-level didactic context as well as in theoretical studies. We use QTM to show its equivalence with quantum circuit model for Deutsch and Deutsch-Jozsa algorithms ...
Giuseppe Corrente
semanticscholar +1 more source
Exploring the abyss in Kleene’s computability theory [PDF]
De Computis, 2023 Kleene’s computability theory based on the S1–S9 computation schemes constitutes a model for computing with objects of any finite type and extends Turing’s ‘machine model’ which formalises computing with real numbers.
Sam Sanders
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Integer-arithmetic-only Certified Robustness for Quantized Neural Networks [PDF]
IEEE International Conference on Computer Vision, 2021 Adversarial data examples have drawn significant attention from the machine learning and security communities. A line of work on tackling adversarial examples is certified robustness via randomized smoothing that can provide a theoretical robustness ...
Haowen Lin +3 more
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Effective Concept Classes of PAC and PACi Incomparable Degrees, Joins and Embedding of Degrees
Bulletin of Symbolic Logic, 2023 The Probably Approximately Correct (PAC) learning is a machine learning model introduced by Leslie Valiant in 1984. The PACi reducibility refers to the PAC reducibility independent of size and computation time. This reducibility in PAC learning resembles
D. G. M. Senadheera
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The Second Quantized Quantum Turing Machine and Kolmogorov Complexity [PDF]
, 2005 The Kolmogorov complexity of a physical state is the minimal physical resources required to reproduce that state. We define a second quantized quantum Turing machine and use it to define second quantized Kolmogorov complexity. There are two advantages to
Caroline Rogers, V. Vedral
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Towards common-sense reasoning via conditional simulation: legacies of Turing in Artificial Intelligence [PDF]
Turing's Legacy, 2012 The problem of replicating the flexibility of human common-sense reasoning has captured the imagination of computer scientists since the early days of Alan Turing's foundational work on computation and the philosophy of artificial intelligence.
Cameron E. Freer +2 more
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A survey on deep reinforcement learning architectures, applications and emerging trends
IET Communications, EarlyView., 2022 Abstract From a future perspective and with the current advancements in technology, deep reinforcement learning (DRL) is set to play an important role in several areas like transportation, automation, finance, medical and in many more fields with less human interaction.
Surjeet Balhara +6 more
wiley +1 more source
Features requirement elicitation process for designing a chatbot application
IET Networks, EarlyView., 2022 This article seeks to assist the chatbot community by outlining the characteristics that a chatbot needs to possess and explaining how to create a chatbot for a bank. In order to determine which capabilities are most crucial to ending users, a study of a small sample of chatbot users was conducted.
Nurul Muizzah Johari +4 more
wiley +1 more source
Technologies Supporting Artificial Intelligence and Robotics Application Development
Journal of Artificial Intelligence and Technology, 2021 Artificial intelligence (AI) and robotics have gone through three generations of development, from Turing test, logic theory machine, to expert system and self-driving car.
Yinong Chen, G. Luca
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On the Proper Treatment of Dynamics in Cognitive Science
Topics in Cognitive Science, EarlyView., 2023 Abstract This essay examines the relevance of dynamical ideas for cognitive science. On its own, the mere mathematical idea of a dynamical system is too weak to serve as a scientific theory of anything, and dynamical approaches within cognitive science are too rich and varied to be subsumed under a single “dynamical hypothesis.” Instead, after first ...
Randall D. Beer
wiley +1 more source