Practices of Ministerial Leadership of Korean-American United Methodist Clergywomen; Toward a Wesleyan Ecclesiology in a Global Context

This study documents, analyzes, and interprets Korean American United Methodist (KAUM) clergywomen‘s experiences in and understandings of the church. It examines contributions these (and potentially, other) clergywomen might make to Wesleyan ecclesiology generally, and particular ways United Methodists live out their faith in transitional, diverse, and global contexts. The project attempts to re-vision existing Wesleyan ecclesial discourse in the United Methodist Church (UMC) by recognizing and incorporating the contributions of racial-ethnic clergy as expressed through their leadership and practices of faith. A "practice-theory-practice" model of practical theology was used to pay systematic attention to the practical locus of the inquiries. Twenty Korean American United Methodist clergywomen were interviewed by telephone, using a voluntary sampling technique to ascertain how they both experienced the church and understood and lived out various practices of faith, including preaching, participation in and administration of the sacraments, preparation for ordained ministry, and other spiritual practices such as prayer, worship, retreats, and journaling. The dissertation summarizes those findings, provides contextual and historical interpretation, and then analyzes their responses in relation to Wesleyan theology, MinJung (mass of people) theology, and the theology of YeoSung (women who display dignity and honor as human beings). This study identifies the extraordinary call of the KAUM clergywomen interviewees to be bridge builders, strong nurturers, wounded healers, committed educators, breakers of old stereotypes, persistent seekers to fulfill God‘s call, and ecclesial leaders with ―tragic consciousness‖ who can disrupt marginality and facilitate the creative transformation of Han (a deep experience of suffering and oppression) into a constructive energy capable of shaping a new reality. According to this study, KAUM clergywomen‘s experiences and practices of faith as ecclesial leaders strengthen Wesleyan ecclesiology in terms of the UMC‘s efforts to be an inclusive church through connectionalism, and its commitment to social justice. MinJung theology and the theology of YeoSung, in their respective understandings of the church, broaden Wesleyan ecclesiology and enable the Church to be more relevant in a global context by embracing those who have not been normative theological subjects.

Simultaneous Learning of Non-Linear Manifold and Dynamical Models for High-Dimensional Time Series

The goal of this work is to learn a parsimonious and informative representation for high-dimensional time series. Conceptually, this comprises two distinct yet tightly coupled tasks: learning a low-dimensional manifold and modeling the dynamical process. These two tasks have a complementary relationship as the temporal constraints provide valuable neighborhood information for dimensionality reduction and conversely, the low-dimensional space allows dynamics to be learnt efficiently. Solving these two tasks simultaneously allows important information to be exchanged mutually. If nonlinear models are required to capture the rich complexity of time series, then the learning problem becomes harder as the nonlinearities in both tasks are coupled. The proposed solution approximates the nonlinear manifold and dynamics using piecewise linear models. The interactions among the linear models are captured in a graphical model. The model structure setup and parameter learning are done using a variational Bayesian approach, which enables automatic Bayesian model structure selection, hence solving the problem of over-fitting. By exploiting the model structure, efficient inference and learning algorithms are obtained without oversimplifying the model of the underlying dynamical process. Evaluation of the proposed framework with competing approaches is conducted in three sets of experiments: dimensionality reduction and reconstruction using synthetic time series, video synthesis using a dynamic texture database, and human motion synthesis, classification and tracking on a benchmark data set. In all experiments, the proposed approach provides superior performance.