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 19 of 19 for “"Bayes Risk"”.
-
Asymptotic cumulative risk and Bayes risk under entropy loss, with applications
In many areas of application of statistics one has a relevent parametric family of densities and wishes to estimate the density from a random sample. In such cases one can use the family to generate an estimator. We fix a prior and consider the properties of the predictive density as an estimator …
-
Efficient sequential designs with asymptotic second-order lower bound of Bayes risk for estimating product of means
… of sequentially designed procedures under the Bayesian framework with conjugate priors, a sharp lower bound for the Bayes risk has been derived. Chapter 1 and 2 introduce the background and fundamental concepts and theorems of this study. Chapter 3 focuses on deriving second-order efficiency of …
-
Aggregation and influence in teams of imperfect decision makers
Bayesian hypothesis testing inevitably requires prior probabilities of hypotheses. Motivated by human decision makers, this thesis studies how binary decision making is performed when the decision-making agents use imperfect prior probabilities. Three detection models with multiple agents are …
-
Sequential Designs with Application in Software Engineering
Presented here is a Bayesian approach to test case allocation in the software reliability estimation. Bayesian analysis allows us to update our beliefs about the reliability of a particular partition as we test, and thus, dynamically re refine our allocation of test cases during the reliability …
-
Wavelet-Based Statistical Modeling and Image Estimation
… performance as measured by the minimax or Bayes risk.
-
When Decision Meets Estimation: Theory and Applications
… is preferred. By noticing the resemblance, a new Bayes risk is generalized from those of decision and estimation, respectively. Based on this generalized Bayes risk, a novel, integrated solution to decision and estimation is introduced. Our study tries to give a more systematic view on the joint …
-
Stochastic Motion Planning for Applications in Subsea Survey and Area Protection
… by jointly minimizing a cost function utilizing Bayes risk.
-
Frugal hypothesis testing and classification
… tests. This distortion is given the name mean Bayes risk error (MBRE). The quantization framework is extended to model human decision making and discrimination in segregated populations.
-
Empirical Bayes estimators for the cross-product ratio of 2x2 contingency tables
… knowledge of the exact prior distribution the Bayes estimator cannot be obtained. However, as long as independent repetitions of the experiment occur, the empirical Bayes approach can then be applied. A general strategy underlying the empirical Bayes estimator consists of finding the Bayes …
-
Information-theoretic limitations of distributed information processing
… two problems, we derive converse results on the Bayes risk and the computation time, respectively. For the last problem, we first study the relationship between the generalization capability of a learning algorithm and its stability property measured by the mutual information between its input …
-
Advances in the Use of Finite-Set Statistics for Multitarget Tracking
… associating measurements to targets using the Bayes factor, which improves tracking performance for FISST methods as well as other approaches to multitarget tracking. Further, we derive a novel formulation of Bayes risk for use with set-valued random variables and develop a real-time planner …
-
Vision-Enhanced Communications: On the Benefits of NLOS/LOS Knowledge in Wireless Systems
… an emphasis on labeled vs unlabeled information. Bayes risk and composite likelihood ratio test (LRT) methods are used to derive the optimal decision rule in both constant false-alarm rate (CFAR) and minimum probability of error (min(Pe)) paradigms. It is shown that a dynamic detection scheme …
-
Information-theoretic analysis of human-machine mixed systems
… show fundamental limits in terms of capacity, Bayes risk, and rate-distortion. A system with queue-length-dependent service quality, motivated by crowdsourcing platforms, is investigated. Since human service quality changes depending on workload, a job designer must take the level of work into …
-
Similarity-Augmented Prediction Methods for Neural Machine Translation
… The most well-known instance of this is minimum Bayes risk (MBR) prediction, which returns the sequence with the highest expected similarity to the LM output distribution. MBR addresses the flaws of beam search and outperforms it across many NLP tasks. Our contributions are as follows. First, we …
-
Unreliable and resource-constrained decoding
… Quantizers that are optimal for mean Bayes risk error, a novel fidelity criterion, are designed. Human decision making in segregated populations is also studied with this framework. The ratio between the costs of false alarms and missed detections is also shown to fundamentally affect …
-
A neural relevance model for feature extraction from hyperspectral images, and its application in the wavelet domain
… to define class boundaries while minimizing the Bayes risk. Our analysis reveals two major algorithmic deficiencies of GRLVQ. Fixing these deficiencies leads to improved convergence performance and classification accuracy. We call our unproved version GRLVQ-Improved (GRLVQI). By using only the …
-
Statistical inference for complex networks
… the theoretical properties of the variational Bayes risk of the proposed algorithm and demonstrate the performance on simulated data and two real-world datasets. Heterogeneous mixed-membership stochastic blockmodel (MMSB) is powerful for modeling overlapping communities and multiple community …
-
Optimisation Methods For Training Deep Neural Networks in Speech Recognition
… to extend this approach to the domain of Minimum Bayes Risk objective functions for discriminative sequence training. With sigmoid models trained on a 50hr and 200hr training set from the Multi-Genre Broadcast 1 (MGB1) transcription task, the NG method applied in a HF styled optimisation framework …
-
Some parametric empirical Bayes techniques
… considers two distinct aspects of the empirical Bayes decision problem. The first aspect considered is the problem or point estimation and hypothesis testing. The second aspect considered is that of estimating the prior distribution and then the estimation of posterior distribution and confidence …