Hyperparameter Importance Across Datasets

With the advent of automated machine learning, automated hyperparameter optimization methods are by now routinely used in data mining. However, this progress is not yet matched by equal progress on automatic analyses that yield information beyond performance-optimizing hyperparameter settings. In this work, we aim to answer the following two questions: Given an algorithm, what are generally its most important hyperparameters, and what are typically good values for these? We present methodology and a framework to answer these questions based on meta-learning across many datasets. We apply this methodology using the experimental meta-data available on OpenML to determine the most important hyperparameters of support vector machines, random forests and Adaboost, and to infer priors for all their hyperparameters. The results, obtained fully automatically, provide a quantitative basis to focus efforts in both manual algorithm design and in automated hyperparameter optimization. The conducted experiments confirm that the hyperparameters selected by the proposed method are indeed the most important ones and that the obtained priors also lead to statistically significant improvements in hyperparameter optimization.Comment: \c{opyright} 2018. Copyright is held by the owner/author(s). Publication rights licensed to ACM. This is the author's version of the work. It is posted here for your personal use, not for redistribution. The definitive Version of Record was published in Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Minin

On-Off Intermittency in Time Series of Spontaneous Paroxysmal Activity in Rats with Genetic Absence Epilepsy

Dynamic behavior of complex neuronal ensembles is a topic comprising a streamline of current researches worldwide. In this article we study the behavior manifested by epileptic brain, in the case of spontaneous non-convulsive paroxysmal activity. For this purpose we analyzed archived long-term recording of paroxysmal activity in animals genetically susceptible to absence epilepsy, namely WAG/Rij rats. We first report that the brain activity alternated between normal states and epilepsy paroxysms is the on-off intermittency phenomenon which has been observed and studied earlier in the different nonlinear systems.Comment: 11 pages, 6 figure

Circus-specific extension of the International Olympic Committee consensus statement: Methods for recording and reporting of epidemiological data on injury and illness in sport 2020

Indepth knowledge of injury and illness epidemiology in circus arts is lacking. Comparing results across studies is difficult due to inconsistent methods and definitions. In 2020, the International Olympic Committee (IOC) consensus group proposed a standard method for recording and reporting epidemiological data on injuries and illnesses in sports and stated that sport-specific extension statements are needed to capture the context of each sport. This is the circus-specific extension to be used with the IOC consensus statement. International circus arts researchers in injury and illness epidemiology and performing arts medicine formed a consensus working group. Consensus statement development included a review of literature, creation of an initial draft by the working group, feedback from external reviewers, integration of feedback into the second draft and a consensus on the final document. This consensus statement contains circus-specific information on (1) injury definitions and characteristics; (2) measures of severity and exposure, with recommendations for calculating the incidence and prevalence; (3) a healthcare practitioner report form; (4) a self-report form capturing health complaints with training and performance exposure; and (5) a demographic, health history and circus experience intake questionnaire. This guideline facilitates comparing results across studies and enables combining data sets on injuries in circus arts. This guideline informs circus-specific injury prevention, rehabilitation, and risk management to improve the performance and health of circus artists

Goniotomy for Non-Infectious Uveitic Glaucoma in Children

Secondary glaucoma is still a blinding complication in childhood uveitis, for which most commonly used surgical interventions (trabeculectomy or glaucoma drainage implant) involve multiple re-interventions and/or complications postoperatively. The goniotomy procedure has never been investigated in the current era, in which patients with pediatric uveitis receive biologics as immunosuppressive therapy for a prolonged period, with potential implications for the outcome. The purpose of the study is to evaluate the efficacy and safety of a goniotomy procedure in pediatric non-infectious uveitis in a retrospective, multicenter case series. The primary outcomes were the postoperative intraocular pressure (IOP), number of IOP-lowering medications, and success rate. Postoperative success was defined as 6 ≤ IOP ≤ 21 mmHg, without major complications or re-interventions. Fifteen eyes of ten children were included. Median age of the included patients at goniotomy was 7 years; median follow-up was 59 months. Median (interquartile range) IOP before surgery was 30 (26–34) mmHg with 4 (3–4) IOP-lowering medications. At 1, 2, and 5 years after goniotomy, median IOP was 15, 14, and 15 mmHg with 2 (0–2), 1 (0–2), and 0 (0–2) medications, respectively (p &lt; 0.001 postoperatively versus preoperatively for all timepoints). Success rate was 100%, 93%, and 80% after 1, 2, and 5 years, respectively. There were no significant changes in visual acuity and uveitis activity or its treatment, and there were no major complications. Our results show that the goniotomy is an effective and safe surgery for children with uveitic glaucoma.</p