Fast optimization of Multithreshold Entropy Linear Classifier

Multithreshold Entropy Linear Classifier (MELC) is a density based model which searches for a linear projection maximizing the Cauchy-Schwarz Divergence of dataset kernel density estimation. Despite its good empirical results, one of its drawbacks is the optimization speed. In this paper we analyze how one can speed it up through solving an approximate problem. We analyze two methods, both similar to the approximate solutions of the Kernel Density Estimation querying and provide adaptive schemes for selecting a crucial parameters based on user-specified acceptable error. Furthermore we show how one can exploit well known conjugate gradients and L-BFGS optimizers despite the fact that the original optimization problem should be solved on the sphere. All above methods and modifications are tested on 10 real life datasets from UCI repository to confirm their practical usability.Comment: Presented at Theoretical Foundations of Machine Learning 2015 (http://tfml.gmum.net), final version published in Schedae Informaticae Journa

A Study Of Factors That Influence Partnerships Between Universities And Nonprofit Organizations

This study examined factors that influence partnerships between universities and nonprofit organizations. Specifically, the study examined how nonprofit leaders characterize “effective” University-Nonprofit Partnerships; strategies that nonprofit leaders have employed to develop effective relationships with universities; and barriers that nonprofit-leaders perceive as inhibiting these partnerships. The study utilized qualitative analyses to learn strategies that have contributed to effective University-Nonprofit Partnerships, to recognize barriers to these partnerships, and to identify strategies for overcoming the barriers. The study examined the experiences of seven nonprofit leaders who had worked in partnership with universities. The results of this study show evidence that while University-Nonprofit Partnerships are effective avenues through which to respond to issues affecting both universities and nonprofits, this kind of partnership does not effortlessly come into being. These partnerships are particularly influenced by mutual trust and clear communication. Also impacting the effectiveness of the partnerships is a shared vision that recognizes and values the needs of each partner. Recommendations for future research, based on inconsistencies in the literature compared to the information provided by the interview participants, are provided in Chapter 5

PUVA Induced Bullous Pemphigoid in a Patient with Psoriasis

Letter to the editor - no abstract available</p