World Ethic Forum Conference Proceedings

World Ethics Forum conference proceedings : the joint conference of The International Institute for Public Ethics (IIPE) and The World Bank : leadership, ethics and integrity in public life : 9-11 April 2006, Keble College, University of Oxford UK /

Accommodating serendipity in the active studio

This paper presents a series of ongoing experiments to facilitate serendipity in the design studio through a diversity of delivery modes. These experiments are conducted in a second year architectural design studio, and include physical, dramatic and musical performance. The act of designing is always exploratory, always seeking an unknown resolution, and the ability to see and capture the value in the unexpected is a critical aspect of such creative design practice. Engaging with the unexpected is however a difficult ability to develop in students. Just how can a student be schooled in such abilities when the challenge and the context are unforeseeable? How can students be offered meaningful feedback about an issue that cannot be predicted, when feedback comes in the form of extrinsic assessment from a tutor? This project establishes a number of student activities that seek to provide intrinsic feedback from the activity itself. Further to this, the project seeks to heighten student engagement with the project through physical expression and performance: utilising more of the students’ senses than just vision and hearing. Diana Laurillard’s theories of conversational frameworks (2002) are used to interrogate the act of dramatic performance as an act of learning, with particular reference to the serendipitous activities of design. Such interrogation highlights the feedback mechanisms that facilitate intrinsic feedback and fast, if not instantaneous, cycles of learning. The physical act of performance itself provides a learning experience that is not replicable in other modes of delivery. Student feedback data and independent assessment of project outcomes are used to assess the success of this studio model.

Implicit online learning

Online learning algorithms have recently risen to prominence due to their strong theoretical guarantees and an increasing number of practical applications for large-scale data analysis problems. In this paper, we analyze a class of online learning algorithms based on fixed potentials and nonlinearized losses, which yields algorithms with implicit update rules. We show how to efficiently compute these updates, and we prove regret bounds for the algorithms. We apply our formulation to several special cases where our approach has benefits over existing online learning methods. In particular, we provide improved algorithms and bounds for the online metric learning problem, and show improved robustness for online linear prediction problems. Results over a variety of data sets demonstrate the advantages of our framework.

Faculty of Built Environment and Engineering Design Theme Conference 2008 Conference Proceedings

Proceedings of the Design Theme Postgraduate Student Conference, held 10th September 2008 at Queensland University of Technology.