15 papers · ranked by Valyu relevance
Paul Flowers, Gabriele Vojt, Maria Pothoulaki, Fiona Mapp + 4 more
The overall appearance of the sample return envelope and its contents raised some concerns for participants. These related primarily to the perceived stigma of STIs and BBVs and concomitant perceptions that postal staff may not handle the return envelope correctly. Participants also outlined some barriers in relation…
Amaryllis Mavragani, Delphine Rahib, Gregory Sallabank, Rob Stephenson + 3 more
'Rob Stephenson' 'Monica Gandhi' 'Leland Merrill' 'Akshay Sharma'] Background Self-collection of specimens at home and their return by mail might help reduce some of the barriers to HIV and bacterial sexually transmitted infection (STI) screening encountered by gay, bisexual, and other men who have sex with men…
Chia-Lin Lin, Pei-Chi Huang, Simone Graessle, Christoph Grathwol + 20 more
Results of scientific work in chemistry can usually be obtained in the form of materials and data. A big step towards transparency and reproducibility of the scientific work can be gained if scientists publish their data in a FAIR (Findable, Accessible, Interoperable, Reusable) manner in research data repositories.…
Yoko Chino, Toshimichi Onuma, Taro Ito, Akiko Shinagawa + 4 more
'Tetsuji Kurokawa' 'Makoto Orisaka' 'Yoshio Yoshida' 'Edward J. Pavlik'] Background: The increasing trend of cervical cancer in women in their 20s in Japan is largely attributable to the low rate of cervical cancer screening. This study aimed to assess the usefulness of human papillomavirus (HPV) self-sampling among…
Harry Mead, Clarissa Costen, Bruno Lacerda, Nick Hawes
When optimising for conditional value at risk (CVaR) using policy gradients (PG), current methods rely on discarding a large proportion of trajectories, resulting in poor sample efficiency. We propose a reformulation of the CVaR optimisation problem by capping the total return of trajectories used in training, rather…
Peng Liu, Yanyan Zheng
In econophysics, the analysis of the return distribution of a financial asset using statistical physics methods is a long-standing and important issue. This paper systematically conducts an analysis of composite index 1 min datasets over a 17-year period (2005-2021) for both the Shanghai and Shenzhen stock exchanges.…
Alberto Sandoval, Javier Márquez, Ignacio Cervera, Stefan Cristian Gherghina
'Stefan Cristian Gherghina'] This work uses long-term operating accruals, rather than current, as an accounting measure to identify major anomalies. Past and abundant accounting and financial literature associates anomalies with problems of reliability and assigns lower reliability to long-term operating accruals than…
Yongming Qu, Biyue Dai
Return-to-baseline is an important method to impute missing values or unobserved potential outcomes when certain hypothetical strategies are used to handle intercurrent events in clinical trials. Current return-to-baseline approaches seen in literature and in practice inflate the variability of the "complete" dataset…
Matteo Smerlak
Returns distributions are heavy-tailed across asset classes. In this note, I examine the implications of this stylized fact for the joint statistics of performance and risk-adjusted return. Using both synthetic and real data, I show that the Sharpe ratio does not increase monotonically with performance: in a sample of…
Rodrigo Gonçalves Novais, Peter Wanke, Jorge Antunes, Yong Tan + 2 more
'Philip Broadbridge' 'Stanisław Drożdż'] This paper describes a new model for portfolio optimization (PO), using entropy and mutual information instead of variance and covariance as measurements of risk. We also compare the performance in and out of sample of the original Markowitz model against the proposed model and…
Brett Daley, Martha White, Marlos C. Machado
Multistep returns, such as n-step returns and λ-returns, are commonly used to improve the sample efficiency of reinforcement learning (RL) methods. The variance of the multistep returns becomes the limiting factor in their length; looking too far into the future increases variance and reverses the benefits of multistep…
Authors not listed
Solving optimization problems, especially for nonlinear and constrained systems, is a challenge. Decades of specialized algorithms have been developed for general and special cases of root finding, minimization (including constraints), for parameter estimation, and mapping connected spaces. These approaches typically…
Charlie S. Burlingham, Naveen Sendhilnathan, Oleg Komogortsev, T. Scott Murdison + 1 more
People coordinate their eye, head, and body movements to gather information from a dynamic environment while maximizing reward and minimizing biomechanical and energetic costs. Such natural behavior is not possible in a laboratory setting where the head and body are usually restrained and the tasks and stimuli used…
Javad Aminian-Dehkordi, Mohammad Mofrad
Sparse, irregular longitudinal metabolomic sampling fundamentally constrains which dynamical properties of gut metabolism can be robustly inferred from observational data. We develop an effective landscape inference framework to characterize these identifiability limits while quantifying aspects of metabolic resilience…
Gilles Zumbach
For long term investments, model portfolios are defined at the level of indexes, a setup known as Strategic Asset Allocation (SAA). The possible outcomes at a scale of a few decades can be obtained by Monte Carlo simulations, resulting in a probability density for the possible portfolio values at the investment…