scholarly journals Improving Model-Based Genetic Programming for Symbolic Regression of Small Expressions

2020 ◽  
pp. 1-27 ◽  
Author(s):  
M. Virgolin ◽  
T. Alderliesten ◽  
C. Witteveen ◽  
P. A. N. Bosman
Keyword(s):  
Genetic Programming ◽  
Real World ◽  
Symbolic Regression ◽  
New Approach ◽  
Model Based ◽  
Real World Datasets ◽  
Linkage Learning ◽  
Optimal Mixing ◽  
Crucial Parameter

The Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) is a model-based EA framework that has been shown to perform well in several domains, including Genetic Programming (GP). Differently from traditional EAs where variation acts blindly, GOMEA learns a model of interdependencies within the genotype, that is, the linkage, to estimate what patterns to propagate. In this article, we study the role of Linkage Learning (LL) performed by GOMEA in Symbolic Regression (SR). We show that the non-uniformity in the distribution of the genotype in GP populations negatively biases LL, and propose a method to correct for this. We also propose approaches to improve LL when ephemeral random constants are used. Furthermore, we adapt a scheme of interleaving runs to alleviate the burden of tuning the population size, a crucial parameter for LL, to SR. We run experiments on 10 real-world datasets, enforcing a strict limitation on solution size, to enable interpretability. We find that the new LL method outperforms the standard one, and that GOMEA outperforms both traditional and semantic GP. We also find that the small solutions evolved by GOMEA are competitive with tuned decision trees, making GOMEA a promising new approach to SR.

scholarly journals Embedding Higher Education into a Real-World Lab: A Process-Oriented Analysis of Six Transdisciplinary Project Courses

2018 ◽  
Vol 10 (10) ◽  
pp. 3798 ◽  
Author(s):  
Richard Beecroft
Keyword(s):  
Higher Education ◽  
Real World ◽  
Social Practice ◽  
Vital Role ◽  
Lessons Learned ◽  
New Approach ◽  
Teaching Activities ◽  
Living Labs ◽  
Urban Lab

Since the early days of the emerging research format of Real-world Labs (RwLs), higher education plays a vital role in them. Examples have been presented on teaching activities in RwLs, but the reasons for and evidence of their inclusion stays limited. To start a systematic discussion on the embedding of higher education in RwLs, this paper presents the case of six Transdisciplinary Project Courses carried out in the RwL “District Future—Urban Lab” in Karlsruhe/Germany. The paper presents the discourses on the role of learning in RwLs and compares it to those on Transition Labs and Urban Living Labs. To offer a new approach to address this aspect, the paper introduces a social practice perspective to map out the interrelations between an RwL and higher education therein. The detailed analysis of the processes is used to identify the potential of the RwL to support learning. It shows that all dimensions of social practice can be identified in the interplay between Real-world Lab and Transdisciplinary Project Courses, even though to a very different degree and in different phases. The text closes with lessons learned for teaching project courses in RwLs and similar labs.

scholarly journals Improved Bounded Matrix Completion for Large-Scale Recommender Systems

2017 ◽  
Author(s):  
Huang Fang ◽  
Zhang Zhen ◽  
Yiqun Shao ◽  
Cho-Jui Hsieh
Keyword(s):  
Real World ◽  
Large Scale ◽  
Matrix Completion ◽  
Stationary Points ◽  
Original Matrix ◽  
New Approach ◽  
Completion Problem ◽  
Objective Value ◽  
Real World Datasets ◽  
Personalized Recommender System

Matrix completion is a widely used technique for personalized recommender system. In this paper, we focus on the idea of Bounded Matrix Completion (BMC) which imposes bounded constraint into the original matrix completion problem. It has been shown that BMC works well for several real world datasets, and an efficient coordinate descent solver called BMA has been proposed in~\cite{bma}. However, we observe that the BMA algorithm sometimes fails to converge to a stationary point, resulting in a relatively poor accuracy in those cases. To overcome this issue, we propose our new approach for solving BMC under the ADMM framework. The proposed algorithm is gauranteed to converge to stationary points. Experimental results on real world datasets show that our algorithm can reach a lower objective value, obtain a higher predict accuracy rate and have better scalability compared with BMA. We also present that our method outperforms the state-of-art standard matrix factorization in most cases.

METAMORPHOSES OF THE POSTMODERN DISCOURSEAND CURRENT CHALLENGES NEOMODERNISM

2019 ◽  
Author(s):  
Yu.V. IRKHIN
Keyword(s):  
World Politics ◽  
New Approach ◽  
Postmodern Theory ◽  
The World ◽  
Conservative Values

The article analyzes the problems, achievements and contradictions in the genesis of the contemporary postmodern discourse. The author has carried out complex research, systematized and showed the main features and differences of postmodernism and metamodernism, as well as the role of neoliberal values in their development. The author has considered a new approach to the study of society and politics: neomodernist discourse with the dominant conservative values, opposing postmodern theory, methodology and practice he has identified the features of neomodernism: historicism, patriotism and healthy nationalism, populism, transactionalismn and realism in the world politics.

Monitoring the marine environment for small round structured viruses (SRSVS): a new approach to combating the transmission of these viruses by molluscan shellfish

1998 ◽  
Vol 38 (12) ◽  
pp. 51-56 ◽  
Author(s):  
K. Henshilwood ◽  
J. Green ◽  
D. N. Lees
Keyword(s):  
Enteric Virus ◽  
Winter Period ◽  
Rt Pcr ◽  
Cloning And Sequencing ◽  
New Approach ◽  
Human Enteric Virus ◽  
Different Strains ◽  
The Uk ◽  
Public Health Protection

This study investigates human enteric virus contamination of a shellfish harvesting area. Samples were analysed over a 14-month period for Small Round Structured Viruses (SRSVs) using a previously developed nested RT-PCR. A clear seasonal difference was observed with the largest numbers of positive samples obtained during the winter period (October to March). This data concurs with the known winter association of gastroenteric illness due to oyster consumption in the UK and also with the majority of the outbreaks associated with shellfish harvested from this area during the study period. RT-PCR positive amplicons were further characterised by cloning and sequencing. Sequence analysis of the positive samples identified eleven SRSV strains, of both Genogroup I and Genogroup II, occurring throughout the study period. Many shellfish samples contained a mixture of strains with a few samples containing up to three different strains with both Genogroups represented. The observed common occurrence of strain mixtures may have implications for the role of shellfish as a vector for dissemination of SRSV strains. These results show that nested RT-PCR can identify SRSV contamination in shellfish harvesting areas. Virus monitoring of shellfish harvesting areas by specialist laboratories using RT-PCR is a possible approach to combating the transmission of SRSVs by molluscan shellfish and could potentially offer significantly enhanced levels of public health protection.

Lattice Thermal Conductivity Modelling of a Diatomic Nanoscale Material

2020 ◽  
Vol 10 (5) ◽  
pp. 602-609
Author(s):  
Adil H. Awad
Keyword(s):  
Thermal Conductivity ◽  
Lattice Thermal Conductivity ◽  
Phonon Scattering ◽  
Correction Term ◽  
Nanoscale Material ◽  
New Approach ◽  
Two Samples ◽  
Conductivity Modelling ◽  
Callaway Model

Introduction: A new approach for expressing the lattice thermal conductivity of diatomic nanoscale materials is developed. Methods: The lattice thermal conductivity of two samples of GaAs nanobeam at 4-100K is calculated on the basis of monatomic dispersion relation. Phonons are scattered by nanobeam boundaries, point defects and other phonons via normal and Umklapp processes. Methods: A comparative study of the results of the present analysis and those obtained using Callaway formula is performed. We clearly demonstrate the importance of the utilised scattering mechanisms in lattice thermal conductivity by addressing the separate role of the phonon scattering relaxation rate. The formulas derived from the correction term are also presented, and their difference from Callaway model is evident. Furthermore their percentage contribution is sufficiently small to be neglected in calculating lattice thermal conductivity. Conclusion: Our model is successfully used to correlate the predicted lattice thermal conductivity with that of the experimental observation.

Intertheatricality and Propaganda

2017 ◽  
Author(s):  
Laurence Publicover
Keyword(s):  
Early Modern ◽  
Real World ◽  
The Political ◽  
Merchant Of Venice ◽  
The Merchant Of Venice ◽  
Political Background ◽  
Controversial Nature

This chapter analyses the ways in which the collaborative drama The Travels of the Three English Brothers defends the Sherley brothers’ real-world political endeavours across Europe and Persia through its intertheatrical negotiations. Explaining the political background of those endeavours and their controversial nature, it illustrates how the playwrights liken the Sherleys to the heroes of dramas that had been popular on the early modern stage over the preceding twenty years, in particular Tamburlaine and The Merchant of Venice. It also examines the significance of Francis Beaumont’s specific parody, in The Knight of the Burning Pestle, of an episode in Travels in which the Persian Sophy acts as godfather to the child of Robert Sherley. The chapter concludes with a discussion of the role of playing companies in shaping dramatic output.

scholarly journals Assessing social preferences in reimbursement negotiations for new Pharmaceuticals in Oncology: an experimental design to analyse willingness to pay and willingness to accept

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Dominik J. Wettstein ◽  
Stefan Boes
Keyword(s):  
Willingness To Pay ◽  
Real World ◽  
Cognitive Biases ◽  
Social Preferences ◽  
Standard Of Care ◽  
Added Value ◽  
Amazon Mechanical Turk ◽  
Patient Organisation ◽  
Patient Benefit

Abstract Background Price negotiations for specialty pharmaceuticals take place in a complex market setting. The determination of the added value of new treatments and the related societal willingness to pay are of increasing importance in policy reform debates. From a behavioural economics perspective, potential cognitive biases and other-regarding concerns affecting outcomes of reimbursement negotiations are of interest. An experimental setting to investigate social preferences in reimbursement negotiations for novel, oncology pharmaceuticals was used. Of interest were differences in social preferences caused by incremental changes of the patient outcome. Methods An online experiment was conducted in two separate runs (n = 202, n = 404) on the Amazon Mechanical Turk (MTurk) platform. Populations were split into two (run one) and four (run two) equally sized treatment groups for hypothetical reimbursement decisions. Participants were randomly assigned to the role of a public price regulator for pharmaceuticals (buyer) or a representative of a pharmaceutical company (seller). In run two, role groups were further split into two different price magnitude framings (“real world” vs unconverted “real payoff” prices). Decisions had real monetary effects on other participants (in the role of premium payers or investors) and via charitable donations to a patient organisation (patient benefit). Results 56 (run one) and 59 (run two) percent of participants stated strictly monotone preferences for incremental patient benefit. The mean incremental cost-effectiveness ratio (ICER) against standard of care (SoC) was higher than the initial ICER of the SoC against no care. Regulators stated lower reservation prices in the “real world” prices group compared to their colleagues in the unconverted payoff group. No price group showed any reluctance to trade. Overall, regulators rated the relevance of the patient for their decision higher and the relevance of their own role lower compared to sellers. Conclusions The price magnitude of current oncology treatments affects stated preferences for incremental survival, and assigned responsibilities lead to different opinions on the relevance of affected stakeholders. The design is useful to further assess effects of reimbursement negotiations on societal outcomes like affordability (cost) or availability (access) of new pharmaceuticals and test behavioural policy interventions.

Time-Efficient Ensemble Learning with Sample Exchange for Edge Computing

2021 ◽  
Vol 21 (3) ◽  
pp. 1-17
Author(s):  
Wu Chen ◽  
Yong Yu ◽  
Keke Gai ◽  
Jiamou Liu ◽  
Kim-Kwang Raymond Choo
Keyword(s):  
Ensemble Learning ◽  
Real World ◽  
Interaction Mechanism ◽  
Training Model ◽  
Edge Computing ◽  
Learning Techniques ◽  
Multi Agent ◽  
Real World Datasets ◽  
Entire Dataset ◽  
Exchange Data

In existing ensemble learning algorithms (e.g., random forest), each base learner’s model needs the entire dataset for sampling and training. However, this may not be practical in many real-world applications, and it incurs additional computational costs. To achieve better efficiency, we propose a decentralized framework: Multi-Agent Ensemble. The framework leverages edge computing to facilitate ensemble learning techniques by focusing on the balancing of access restrictions (small sub-dataset) and accuracy enhancement. Specifically, network edge nodes (learners) are utilized to model classifications and predictions in our framework. Data is then distributed to multiple base learners who exchange data via an interaction mechanism to achieve improved prediction. The proposed approach relies on a training model rather than conventional centralized learning. Findings from the experimental evaluations using 20 real-world datasets suggest that Multi-Agent Ensemble outperforms other ensemble approaches in terms of accuracy even though the base learners require fewer samples (i.e., significant reduction in computation costs).

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