Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 25 for “"learning rules"”.
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Learning to Plan by Learning Rules
Many environments involve following rules and tasks; for example, a chef cooking a dish follows a recipe, and a person driving follows rules of the road. People are naturally fluent with rules: we can learn rules efficiently; we can follow rules; we can interpret rules and explain them to others; …
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Spike-based learning rules and stabilization of persistent neural activity
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.
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Uncovering Efficient Learning and Initialisation Algorithms for Neural Networks Using Evolutionary Algorithms and Theoretical Analyses
… are one of the most widely used form of machine learning algorithms. Over the years numerous types of ANN have been developed and applied to many domains. However, there are still important problems to overcome including their slow learning and the inability of certain types of deep ANNs to …
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Dynamics of adaptive recurrent neural networks
… rule is chosen from the class of Hebbian learning rules, in which the synaptic connection between two neurons evolves continuously as a function of their correlation in the recent past. Initially an analysis of networks of two neurons is presented, which exhibit relaxation oscillations in …
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An optimization approach to relate neural circuit architecture, loss landscapes and learning performance in static and dynamic tasks
Learning is challenging for large and complex neural circuits. There is a fundamental difficulty in determining how individual neurons or synapses affect the overall behavior of a circuit, which is known as the credit assignment problem. Rather than looking at single neurons or synapses then, one …
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Models of sensory coding
… modifiable connections between the units, the rules governing the activity-dependent modification of these connections are studied. One class of such ‘learning rules’, local learning rules, are particularly important for understanding the nervous system. Specific hypotheses about the form of …
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Essays on Long-Term Relationships and Networks
… The third chapter studies properties of learning and information aggregation on social networks. The first chapter, joint with Adam Harris, provides evidence on the scope and incentive mechanisms of long-term relationships in the US truckload freight industry. In this setting, shippers …
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Experimental evidence that group foragers can converge on predicted producer-scrounger equilibria
… look at testing the performance of different learning rules using a similar experimental design.
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Engineering System Design for Automated Space Weather Forecast. Designing Automatic Software Systems for the Large-Scale Analysis of Solar Data, Knowledge Extraction and the Prediction of Solar Activities Using Machine Learning Techniques.
… introduces novel, fully computerised, machine learning-based decision rules and models that can be used within a system design for automated space weather forecasting. The system design in this work consists of three stages: (1) designing computer tools to find the associations among sunspot …
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Engineering System Design for Automated Space Weather Forecast. Designing Automatic Software Systems for the Large-Scale Analysis of Solar Data, Knowledge Extraction and the Prediction of Solar Activities Using Machine Learning Techniques
… introduces novel, fully computerised, machine learning-based decision rules and models that can be used within a system design for automated space weather forecasting. The system design in this work consists of three stages: (1) designing computer tools to find the associations among sunspot …
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Engineering System Design for Automated Space Weather Forecast. Designing Automatic Software Systems for the Large-Scale Analysis of Solar Data, Knowledge Extraction and the Prediction of Solar Activities Using Machine Learning Techniques.
… introduces novel, fully computerised, machine learning-based decision rules and models that can be used within a system design for automated space weather forecasting. The system design in this work consists of three stages: (1) designing computer tools to find the associations among sunspot …
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Growing synfire chains with triphasic spike-time-dependent plasticity
… constraints in addition to any synaptic learning rules. Here, it is shown that this necessity can be removed. In this model, development is guided by an experimentally reported spike-timing-dependent plasticity (STDP) rule, triphasic STDP, plus activity-dependent excitability. This STDP …
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Automatically learning optimal formula simplifiers and database entity matching rules
Traditionally, machine learning (ML) is used to find a function from data to optimize a numerical score. On the other hand, synthesis is traditionally used to find a function (or a program) that can be derived from a grammar and satisfies a logical specification. The boundary between ML and …
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Investigating neuronal network dynamics : scale-invariance, preferred firing rates, and plasticity via phase-shift encoding
… Targeted stimulation based on Hebbian learning rules with Granger causality analysis was used to evaluate pre-synaptic and post-synaptic relationships. Distinct firing patterns emerged from the baseline and Poisson stimulations via Fourier transform analysis, suggesting stable, …
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Price formation under uncertainty
… by a known example that shows that adaptive learning rules can lead rational agents to believe in nonstationary, indeterminate equilibria that are locally stable, such as Sunspot Equilibria. This leads to an important conclusion; diverse beliefs are not temporary phenomena since …
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Induction and Maintenance of Synaptic Plasticity
… activation are believed to be at the origin of learning and long-term memory. Recent experiments suggest that these long-term synaptic changes are all-or-none switch-like events between discrete states of a single synapse. The biochemical network involving calcium/calmodulin-dependent protein …
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Low Power Adaptive Circuits: An Adaptive Log Domain Filter and A Low Power Temperature Insensitive Oscillator Applied in Smart Dust Radio
… The adaptive filter is presented with integrated learning rules for model reference estimation. The system is a first order low pass filter with two parameters: gain and cut-off frequency. It is implemented using multiple input floating gate transistors to realize online learning of system …
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Classifying and Predicting Dynamics with Bioinspired Machine Learning
… of adaptive dynamical networks, where biological learning rules influence the network weights, the monotonic nature of these rules (that is, where weights increase or decrease monotonically to converge to some local minimum of the loss), including backpropagation, poses yet another problem: the …
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Investigation and modeling of unsaturated flow through swelling soils
… the back-propagation error method with adaptive learning rules by means of the neural network tool box of MATLAB software. A finite difference numerical model, based on a fully implicit method, was proposed to numerically solve the one dimensional governing equation (simplified form of 3D …
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Modeling Integrated Cortical Learning: Explorations of Cortical Map Development, Unit Selectivity, and Object Recognition
… are exceedingly abstract models of cortical learning. First, DCNNs use fixed connectivity, whereas cortical connectivity is plastic. Second, DCNNs use convolutional weight-sharing, whereas simple cells in visual cortex learn using local competition rules. Third, DCNNs use fixed pools, whereas …
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