Results 11 to 20 of about 35,739 (240)
Robustifying Learnability [PDF]
Journal of Economic Dynamics and Control, 2005 In recent years, the learnability of rational expectations equilibria (REE) and determinacy of economic structures have rightfully joined the usual performance criteria among the sought after goals of policy design.
Peter von zur Muehlen, Robert J. Tetlow
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Learnable Subspace Clustering [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2022 This paper studies the large-scale subspace clustering (LSSC) problem with million data points. Many popular subspace clustering methods cannot directly handle the LSSC problem although they have been considered as state-of-the-art methods for small-scale data points. A basic reason is that these methods often choose all data points as a big dictionary
Jun Li +4 more
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Network architectures supporting learnability [PDF]
Philosophical Transactions of the Royal Society B: Biological Sciences, 2020 Human learners acquire complex interconnected networks of relational knowledge. The capacity for such learning naturally depends on two factors: the architecture (or informational structure) of the knowledge network itself and the architecture of the computational unit—the brain—that encodes and processes the information.
Perry Zurn, Danielle S. Bassett
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Communications of the ACM, 2017 New blocks frameworks open doors to greater experimentation for novices and professionals alike.
Bau, David +4 more
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What is usability in the context of the digital library and how can it be measured? [PDF]
, 2005 This paper reviews how usability has been defined in the context of the digital library, what methods have been applied and their applicability, and proposes an evaluation model and a suite of instruments for evaluating usability for academic digital ...
Jeng, Judy
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Semantically Adversarial Learnable Filters [PDF]
IEEE Transactions on Image Processing, 2021 We present an adversarial framework to craft perturbations that mislead classifiers by accounting for the image content and the semantics of the labels. The proposed framework combines a structure loss and a semantic adversarial loss in a multi-task objective function to train a fully convolutional neural network.
Ali Shahin Shamsabadi +2 more
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Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems, 2021 We have to learn all new technologies and we continue to learn for as long as we use them and develop that use. Learning is therefore an integral part of human engagement with technology, as it is with all areas of life. This paper proposes that we should consider learning as an important part of all human computer interaction and that theories of ...
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A Petri-Net Based Approach to Measure the Learnability of Interactive Systems [PDF]
, 2016 We propose an approach to measure the learnability of an interactive system. Our approach relies on recording in a user log all the user actions that take place during a run of the system and on replaying them over one or more interaction models of the ...
Catarci, Tiziana +3 more
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Information and Computation, 2012 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jain S., Kötzing T., Stephan F.
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Quantum versus classical learnability [PDF]
Proceedings 16th Annual IEEE Conference on Computational Complexity, 2002 We consider quantum versions of two well-studied classical learning models: Angluin's model of exact learning from membership queries and Valiant's Probably Approximately Correct (PAC) model of learning from random examples. We give positive and negative results for quantum versus classical learnability.
Servedio, Rocco A., Gortler, Steven J.
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