Stochastic Variance Reduction Methods for Saddle-Point Problems

We consider convex-concave saddle-point problems where the objective functions may be split in many components, and extend recent stochastic variance reduction methods (such as SVRG or SAGA) to provide the first large-scale linearly convergent algorithms for this class of problems which is common in machine learning. While the algorithmic extension is straightforward, it comes with challenges and opportunities: (a) the convex minimization analysis does not apply and we use the notion of monotone operators to prove convergence, showing in particular that the same algorithm applies to a larger class of problems, such as variational inequalities, (b) there are two notions of splits, in terms of functions, or in terms of partial derivatives, (c) the split does need to be done with convex-concave terms, (d) non-uniform sampling is key to an efficient algorithm, both in theory and practice, and (e) these incremental algorithms can be easily accelerated using a simple extension of the "catalyst" framework, leading to an algorithm which is always superior to accelerated batch algorithms.Comment: Neural Information Processing Systems (NIPS), 2016, Barcelona, Spai

Protection of intellectual property rights an Indian perspective

The objective of this paper is to provide an overview of the Indian Innovation System, IPR system and other related activities such as Judicial System, Enforcement System, and Academic Institutions etc. The paper is based on the existing data and relates those data and results to the India’s Intellectual Property Rights System, Innovation, Research and Development. This paper focus on the recent reforms in IPR laws to achieve a legal framework for protecting IPR that is comparable to that of most developed nations. As a part Information Technology, three major IT organizations focus on innovation and research discussed in addition to an overview about major multinational companies’ research initiatives in India

Learning Experience of Small Farmers in Sugarcane Cultivation

The effective learning experience can be had effective learning situations provided by a skillful instructor who knows what he wants, who has the materials to accomplish his goals and the skills to use them effectively. The study was conducted in Cuddalore district of Tamil Nadu. A total number of ten sugarcane technologies with technical units were selected for the study. The result of the study small farmers possessed low level of learning experience. The learning experience may be further enhanced by majority of the small farmers to prefer personal localite channels for getting information

Estimating Footfall From Passive Wi-Fi Signals: Case Study with Smart Street Sensor Project

Measuring the distribution and dynamics of the population at granular level both spatially and temporally is crucial for understanding the structure and function of the built environment. In this era of big data, there have been numerous attempts to undertake this using the preponderance of unstructured, passive and incidental digital data which are generated from day-to-day human activities. In attempts to collect, analyse and link these widely available datasets at a massive scale, it is easy to put the privacy of the study subjects at risk. This research looks at one such data source - Wi-Fi probe requests generated by mobile devices - in detail, and processes it into granular, long-term information on number of people on the retail high streets of the United Kingdom (UK). Though this is not the first study to use this data source, the thesis specifically targets and tackles the uncertainties introduced in recent years by the implementation of features designed to protect the privacy of the users of Wi-Fi enabled mobile devices. This research starts with the design and implementation of multiple experiments to examine Wi-Fi probe requests in detail, then later describes the development of a data collection methodology to collect multiple sets of probe requests at locations across London. The thesis also details the uses of these datasets, along with the massive dataset generated by the ‘Smart Street Sensor’ project, to devise novel data cleaning and processing methodologies which result in the generation of a high quality dataset which describes the volume of people on UK retail high streets with a granularity of 5 minute intervals since August 2015 across 1000 locations (approx.) in 115 towns. This thesis also describes the compilation of a bespoke ‘Medium data toolkit’ for processing Wi-Fi probe requests (or indeed any other data with a similar size and complexity). Finally, the thesis demonstrates the value and possible applications of such footfall information through a series of case studies. By successfully avoiding the use of any personally identifiable information, the research undertaken for this thesis also demonstrates that it is feasible to prioritise the privacy of users while still deriving detailed and meaningful insights from the data generated by the users

Violence towards Nurses

oai:ojs.pkp.sfu.ca:article/3Background: Although nurses worldwide are experienced violence in their workplace, how nurses experiences violence in India remains unclear. Objectives: The objectives of this study were to (1) determine the occurrence of violence towards nurses. (2) compare the physical and verbal violence towards nurses. (3)find the association between the violence and selected variables.Methods: A descriptive survey design Setting: National mental health and neuro science hospital (A), Bangalore, Karnataka, India. Participants: Purposive sampling technique was used which includes the nurses (1) working in Hospital A, (2) having minimum 6 (Six) months of experience. (3) who were available during data collection. (4) who were willing to participate in the study. majority i.e. 165 (92.2%) of the subjects are females and 14 (7.8%) are males, data further show that 147 (82.1%) subjects are staff nurses. A validated and reliable self administered questionnaire developed by the investigator was administered from 24th April 2006 to 25th May 2006.Results: Majority i.e. 156 (87.2%) of subjects experience violence, out of that 1O2 (57%) subjects experienced mild violence, whereas 23 subjects i.e. 12.8% never experienced violence, and fifty four (30.2%) experience moderate violence. The mean verbal violence score (5.40) is apparently higher than the mean physical violence score (1.55).Conclusion: These results suggest that nurses need to be trained in therapeutic communication and nonviolence self-defence techniques