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 69 for “"Latent Factors"”.
-
Variational Autoencoders for Discovering Influential Latent Factors
… data distribution is composed of a few latent random variables. For example, a VAE (or some other generative learning model) might learn that an image of a person can be generated from the hair color, face shape, and background color. By decomposing the data into latent factors, we could …
-
Statistical Methods for Inferring Latent Factors in Biological Networks
… question in network biology is the estimation of latent factors, such as protein or pathway activity, which play a critical role in driving disease phenotypes but are not easily measurable in the laboratory. My research focuses on utilizing large-scale sequencing data and statistical modeling to …
-
STUDIES ON HOUSING MARKET DYNAMICS AND COINTEGRATION ANALYSIS WITH LATENT FACTORS
… market dynamics and cointegration analysis with latent factors. The theme of this dissertation is housing market dynamics, with the first essay an application of advanced panel time series models to the studies of housing market dynamics, and the second essay a theoretic derivation of an …
-
Exploiting Observation Bias to Improve Matrix Completion
… are driven by the same set of underlying latent or unobserved factors. This leads to a two stage matrix completion algorithm: first, recover (distances between) the latent factors by utilizing matrix completion for the fully observed noisy binary matrix corresponding to the observation …
-
Applying Weighting Biases in Cognitive Energetics Theory to Behavior Change
… (1) positivity and negativity inclinations as latent factors reflecting sensitivities to positive and negative aspects of goal pursuit, (2) CET weighting biases (i.e., increased sensitivity to either driving or restraining forces in CET based on positivity and negativity latent factors) and (3) …
-
Essays in econometrics and random matrix theory
… that traditional approaches to the estimation of latent factors in financial data underestimate the number of risk factors. They are also biased towards a single market factor, the importance of which is overestimated in samples. In Chapter 3, I derive a new consistent procedure for the estimation …
-
Advances in Bayesian Factor Modeling and Scalable Gaussian Process Regression
… association between variables by assuming some latent factors drive structured variation therein. Gaussian process (GP) models, on the other hand, describe the association between variables using a distance-based covariance kernel. This dissertation introduces two novel extensions of Bayesian …
-
Collaborative Genre Tagging
… of users in the absence of any metadata. Latent factor models have been used to achieve state-of-the-art accuracy in many CF settings, playing an especially large role in beating the benchmark set in the Netflix Prize in 2008. These models learn latent features for users and items to …
-
Gratitude as a Mechanism by which Agreeable Individuals Maintain Good Quality Interpersonal Relationships
… quality. Structural equation model analyses with latent factors revealed that dispositional gratitude fully mediated the effects of agreeableness on friendship support, intimacy, and affection. Study 2 extended the findings of Study 1 by examining whether frequency of grateful affect was a more …
-
Constrained Matrix and Tensor Factorization: Theory, Algorithms, and Applications
… for estimating the underlying generative matrix factors, which are generally non-orthogonal. On the other hand, it has been observed that imposing simple constraints on the latent factors, for example non-negativity (which in a way opposes orthogonality) can make these factors essentially unique …
-
Mining social sensing data: Representation, modeling, and applications
… is to develop unsupervised solutions that learn latent structures and models from observed social media data to advance social sensing applications, including misinformation detection, link prediction, and polarity detection. The work lies in the exploration of learning systems that include both …
-
Bayesian Factor Models for Clustering and Spatiotemporal Analysis
… this dissertation, we propose two novel Bayesian factors models. These models are designed to effectively reduce the dimensionality of the data, as the number of latent factors is typically much smaller than that of the observation vectors. Therefore, our proposed models can achieve substantial …
-
Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents
… the agents as a low rank tensor decomposition of latent factors associated with agents, states, and actions. We perform experiments on various benchmark environments and demonstrate improvement over existing offline approaches in the scarce data regime.
-
Factors of the term structure of sovereign yield spreads and the effect on the uncovered interest rate parity model for exchange rate prediction
… for these markets are primarily driven by three latent factors which can be classified as the spread level, slope and curvature factors. We further postulate that a country’s yield curve contains valuable information about its future economic state and as such the PCA derived spread factors, …
-
Reasoning about objects under full occlusion
… task, provides a general framework to infer latent factors of scene via physics simulation, and extends support for intuitive physics-based approaches for robust visual reasoning.
-
Understanding Public Library Services and Use: A Structural Equation Modeling Framework
… public libraries relating operating revenue to latent factors measuring service availability and library use within the context of matched community demographic data. The process of using theory-based data analysis to investigate publicly-available data is examined. Key findings include …
-
Essays on structural changes in high dimensional econometric models
… factor model with an unknown number of latent factors and a single common change in the number of factors and/or factor loadings. The third essay considers estimating a high dimensional factor model with an unknown number of latent factors and multiple common changes in the number of …
-
Are You Ready? A Proposed Framework For The Assessment Of Digital Forensic Readiness
… variables. Factor analysis was used to identify latent factors within the two groups of variables. A statistically-based framework to assess DFR is presented, wherein the extant indicators are used as a proxy of the real DFR status and the perceptual factors as the perception of this status.
-
Bayesian and Information-Theoretic Learning of High Dimensional Data
… expression data is reduced to a small number of latent factors, each with a prototypical dynamic trajectory. In the Bayesian Graphical LASSO, the inverse covariance matrix of the data distribution is assumed to be sparse, inducing a sparsely connected Gaussian graph. In the nonparametric Mixture …
-
Exploring Factors in the Relationship Balance Assessment
… of individuals and couples identified 12 latent factors underlying relationship equality. While the study looked for significant correlations with their score averages, this study indicated that </p> <p>While studies have highlighted the role of gendered power in relationships, many …
Page 1 of 4