Generalized Boosting Algorithms for Convex Optimization

Boosting is a popular way to derive powerful learners from simpler hypothesis classes. Following previous work (Mason et al., 1999; Friedman, 2000) on general boosting frameworks, we analyze gradient-based descent algorithms for boosting with respect to any convex objective and introduce a new measure of weak learner performance into this setting which generalizes existing work. We present the weak to strong learning guarantees for the existing gradient boosting work for strongly-smooth, strongly-convex objectives under this new measure of performance, and also demonstrate that this work fails for non-smooth objectives. To address this issue, we present new algorithms which extend this boosting approach to arbitrary convex loss functions and give corresponding weak to strong convergence results. In addition, we demonstrate experimental results that support our analysis and demonstrate the need for the new algorithms we present.Comment: Extended version of paper presented at the International Conference on Machine Learning, 2011. 9 pages + appendix with proof

The majority-party disadvantage: revising theories of legislative organization

Dominant theories of legislative organization in the U.S. rest on the notion that the majority party arranges legislative matters to enhance its electoral fortunes. Yet, we find little evidence for a short-term electoral advantage for the majority party in U.S. state legislatures. Furthermore, there appears to be a pronounced downstream majority-party disadvantage. To establish these findings, we propose a technique for aggregating the results of close elections to obtain as-if random variation in majority-party status. We argue that the results from this approach are consistent with a phenomenon of inter-temporal balancing, which we link to other forms of partisan balancing in U.S. elections. The article thus necessitates revisions to our theories of legislative organization, offers new arguments for balancing theories, and lays out an empirical technique for studying the effects of majority-party status in legislative contexts

You don't know what's around the corner: A qualitative study of professional footballers in England facing career-transition

Career transition in sport is a rapidly growing area within the field of sport psychology. Interest in this area has been fuelled by the need for an increased number of professional athletes seeking support and assistance during transition from sport. However, whilst research in this field has focused in on a wide range of sports, specific research on retirement in professional football has been limited. Because of this it is argued that current research may fail to consider specific issues associated with the transition from professional football. Therefore, in an attempt to add to the existing body of research the current study aimed to provide an in-depth insight into how professional footballers understand their ‘lived-world’ during exit from their sport. A total of eight former professional footballers, who were at the time experiencing the possibility of career-transition, were interviewed in two separate focus group discussions. The interviews were analysed using interpretive phenomenological analysis (IPA). The key findings from the research show that a lack of control over their lives, lack of pre-planning and preparation for retirement as well as support and ability to seek it led professional footballers to experience heightened levels of anxiety, uncertainty and fear for their futures as well as an unexpected sense of rejection during career transition. These findings have implications for support organisations and those interested in the life-long welfare of professional footballers. It is proposed that an emphasis on pre-planning and preparation, provisions of support and encouraging help-seeking may aid professional footballers during the process out of their sport

Kinematics of the Broad Line Region in M81

A new model is presented which explains the origin of the broad emission lines observed in the LINER/Seyfert nucleus of M81 in terms of a steady state spherically symmetric inflow, amounting to 1 x 10^-5 Msun/yr, which is sufficient to explain the luminosity of the AGN. The emitting volume has an outer radius of ~1 pc, making it the largest broad line region yet to be measured, and it contains a total mass of ~ 5 x 10^-2 Msun of dense, ~ 10^8 cm^-3, ionized gas, leading to a very low filling factor of ~ 5 x 10^-9. The fact that the BLR in M81 is so large may explain why the AGN is unable to sustain the ionization seen there. Thus, the AGN in M81 is not simply a scaled down quasar.Comment: Accepted for Publication in ApJ 7/21/0

Under-dominance constrains the evolution of negative autoregulation in diploids

Regulatory networks have evolved to allow gene expression to rapidly track changes in the environment as well as to buffer perturbations and maintain cellular homeostasis in the absence of change. Theoretical work and empirical investigation in Escherichia coli have shown that negative autoregulation confers both rapid response times and reduced intrinsic noise, which is reflected in the fact that almost half of Escherichia coli transcription factors are negatively autoregulated. However, negative autoregulation is exceedingly rare amongst the transcription factors of Saccharomyces cerevisiae. This difference is all the more surprising because E. coli and S. cerevisiae otherwise have remarkably similar profiles of network motifs. In this study we first show that regulatory interactions amongst the transcription factors of Drosophila melanogaster and humans have a similar dearth of negative autoregulation to that seen in S. cerevisiae. We then present a model demonstrating that this fundamental difference in the noise reduction strategies used amongst species can be explained by constraints on the evolution of negative autoregulation in diploids. We show that regulatory interactions between pairs of homologous genes within the same cell can lead to under-dominance - mutations which result in stronger autoregulation, and decrease noise in homozygotes, paradoxically can cause increased noise in heterozygotes. This severely limits a diploid's ability to evolve negative autoregulation as a noise reduction mechanism. Our work offers a simple and general explanation for a previously unexplained difference between the regulatory architectures of E. coli and yeast, Drosophila and humans. It also demonstrates that the effects of diploidy in gene networks can have counter-intuitive consequences that may profoundly influence the course of evolution