Candidate working set strategy based SMO algorithm in support vector machine

Sequential minimal optimization (SMO) is quite an efficient algorithm for training the support vector machine. The most important step of this algorithm is the selection of the working set, which greatly affects the training speed. The feasible direction strategy for the working set selection can decrease the objective function, however, may augment to the total calculation for selecting the working set in each of the iteration. In this paper, a new candidate working set (CWS) Strategy is presented considering the cost on the working set selection and cache performance. This new strategy can select several greatest violating samples from Cache as the iterative working sets for the next several optimizing steps, which can improve the efficiency of the kernel cache usage and reduce the computational cost related to the working set selection. The results of the theory analysis and experiments demonstrate that the proposed method can reduce the training time, especially on the large-scale datasets.     

Collaborative Practitioner Research: A Case of Lesson Study in a Small Jewish School

ABSTRACT

Lesson study is a form of professional development where a group of teachers identifies a problem of practice on which they would like to make progress in their teaching. Over an extended period of time, the teachers study the topic and plan a lesson together. One member then teaches the lesson while the others observe; the group reflects afterwards on student learning. The cycle repeats, building teachers’ professional knowledge and their shared views of pedagogy over time. In this article, we argue that lesson study is a collaborative form of practitioner research and we show how this is so by sharing an example of a lesson study cycle conducted in a synagogue school.     

Exploring the educational aspirations–expectations gap in eighth grade students: implications for educational interventions and school reform

Over the past three decades, more and more students are expressing a desire to attend college, yet for many members of disenfranchised groups, this goal is often not attained. While many factors contribute to these disparities, research has shown that students begin adjusting their expectations (what they think they can achieve) for the future in relation to their idealised aspirations (what they would like to achieve). The current study explores this gap among 207 eighth grade students from two urban middle schools. Using the School Attitude Assessment Survey-Revised, three factors were found to predict expectations which matched student aspirations. These factors were academic motivation and self-regulating behaviours, academic self-perception and attitudes towards teachers. Implications for educational interventions and school reform are discussed.