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.
Results
Showing 1 to 20 of 387 for “"discriminative"”.
-
Gabapentin Discriminative Stimulus Effects
… drug effects of gabapentin when established as a discriminative stimulus as well as GABA<sub>A</sub> and NMDA ligands. Ten female Sprague-Dawley rats were trained on a drug discrimination paradigm using a 300.0 mg/kg gabapentin training dose as a discriminative stimulus. Gabapentin was …
-
Discriminative Stimulus Effects of Gabapentin
<p>The present study sought to evaluate the discriminative stimulus effects of the anticonvulsant gabapentin in rats trained to discriminate 30.0 mg/kg gabapentin from vehicle in a two-lever drug discrimination task. All of the ten rats tested were able to establish gabapentin as an interoceptive …
-
Investigations on discriminative training criteria
In this work, a framework for efficient discriminative training and modeling is developed and implemented for both small and large vocabulary continuous speech recognition. Special attention will be directed to the comparison and formalization of varying discriminative training criteria and …
-
Discriminative, generative, and imitative learning
… paradigms in machine learning: generative, discriminative and imitative learning. A generative probabilistic distribution is a principled way to model many machine learning and machine perception problems. Therein, one provides domain specific knowledge in terms of structure and parameter …
-
Advances in discriminative dependency parsing
… in dependency parsing has highlighted the discriminative structured prediction framework (McDonald et al., 2005a; Carreras, 2007; Suzuki et al., 2009), which is characterized by two advantages: first, the availability of powerful discriminative learning algorithms like log-linear and …
-
Discriminative Classification Models for Internet Security
… received from the sending server. In general, discriminative classification methods learn to distinguish positive from negative entities. Each decision for a label may be based on features of the entity and related entities. When labels of related entities have strong interdependencies---as can …
-
Aspects of generative and discriminative classifiers
… under the new terminology of generative and discriminative classifiers, research interest in classical statistical approaches to discriminant analysis has re-emerged in the machine learning community. In discriminant analysis, observations with features $\mathbf{x}$ measured are classified …
-
Learning discriminative models with incomplete data
… to incorrect labels in the training data. The discriminative paradigm of classification aims to model the classification boundary directly by conditioning on the data points; however, discriminative models cannot easily handle incompleteness since the distribution of the observations is never …
-
Image retrieval, object recognition, and discriminative models
… to image retrieval, object recognition, and discriminative models. For image retrieval, we evaluate a large variety of different descriptors and answer the questions how descriptors can be combined and which descriptor should be chosen according to which criterion. We suggest a set of local …
-
Discriminative Stimulus Effects of Putative Antipsychotic Drugs
<p>This study attempted to further explore the discriminative stimulus properties of antipsychotic drugs, by establishing the typical antipsychotic drug chlorpromazine, and the atypical antipsychotic drug clozapine as discriminative stimulus in two different groups of rats. The rats trained to …
-
Mining time-series data using discriminative subsequences
… A shapelet is a time-series subsequence that is discriminative of the class of the original series. We use a heterogeneous ensemble classifier on the transformed data. The accuracy of our method is significantly better than the time-series classification benchmark (1-nearest-neighbour with …
-
Discriminative methods for statistical spoken dialogue systems
… potentially be useful. This thesis presents how discriminative methods can overcome these problems in Spoken Language Understanding (SLU) and Dialogue State Tracking (DST). A robust method for SLU is proposed, based on features extracted from the full posterior distribution of recognition …
-
Discriminative stimulus properties of 3-substituent rimonabant analogs
… These analogs also failed to elicit THC-like discriminative stimulus effects, nor did they antagonize THC’s discriminative stimulus in mice discriminating 5.6 mg/kg THC from vehicle. Finally, mice were trained to discriminate 5.6 mg/kg O-6629 from vehicle. O-6658 produced full substitution for …
-
Unified Discriminative Subspace Learning for Multimodality Image Analysis
To demonstrate the effectiveness of the framework, an expert model of the query-driven locally adaptive (QDLA) method and four new subspace learning algorithms corresponding to different learning-locality criteria are presented. These four algorithms are locally embedded analysis (LEA), …
-
Application of Prior Information to Discriminative Feature Learning
Learning discriminative feature representations has attracted a great deal of attention since it is a critical step to facilitate the subsequent classification, retrieval and recommendation tasks. In this dissertation, besides incorporating prior knowledge about image labels into the image …
-
Generative and Discriminative Models in Phase Transition Prediction
… understanding physical systems. Generative and discriminative models offer promising yet distinct approaches. Considering varying knowledge levels of the system, accessible data amounts, and computation resources of the experiments, these methods exhibit different accuracy and efficiency. This …
-
A log-linear discriminative modeling framework for speech recognition
… based on Gaussian hidden Markov models (HMMs).Discriminative techniques such as log-linear modeling have been investigated in speech recognition only recently. This thesis establishes a log-linear modeling framework in the context of discriminative training criteria, with examples from …
-
Discriminative training and acoustic modeling for automatic speech recognition
Discriminative training has become an important means for estimating model parameters in many statistical pattern recognition tasks. While standard learning methods based on the Maximum Likelihood criterion aim at optimizing model parameters only class individually, discriminative approaches …
Page 1 of 20