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Automatic Sampler Discovery via Probabilistic Programming and Approximate Bayesian Computation
[chapter]
2016
Lecture Notes in Computer Science
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Specifically, we learn the procedure code of samplers for one-dimensional distributions. ...
Our results are competive relative to state-of-the-art genetic programming methods and demonstrate that we can learn approximate and even exact samplers. ...
Figure 8 shows that PMCMC inference performance is similar to genetic programming. In contrast to genetic programming, PMCMC is statistically valid estimator of the target distribution. ...
doi:10.1007/978-3-319-41649-6_27
fatcat:3jbkfa2t7bhubph2h6t6wl4z6e
Observation of the cancer patient journey: a learning curve for Genetic Counsellors
2012
Hereditary Cancer in Clinical Practice
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However, in their training, genetic counsellors seldom have much exposure to the medical environments in which their clients receive their cancer treatment. ...
both consultations and medical procedures in their speciality area. ...
doi:10.1186/1897-4287-10-s2-a51
pmcid:PMC3326867
fatcat:siybyzaae5b47hliit34tmeyui
Policy Optimization by Genetic Distillation
[article]
2018
arXiv
pre-print
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Genetic algorithms have been widely used in many practical optimization problems. ...
GPO uses imitation learning for policy crossover in the state space and applies policy gradient methods for mutation. ...
The child policy is learned using a two-step procedure. A schematic of the methodology is shown in Figure 2 . ...
arXiv:1711.01012v2
fatcat:d3rvfngimzbozkbb4ykqe3r274
Probability-Enhanced Predictions in the Anticipatory Classifier System
[chapter]
2001
Lecture Notes in Computer Science
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A behavioral act in the ACS with all the involved learning procedures Similar to all LCSs, the ACS evolves a population of classi ers. ...
In order to be able to learn an internal environmental model, the ACS relies on a causality in successive perceptions of an environment. ...
doi:10.1007/3-540-44640-0_4
fatcat:lgmcebaprjclvf5dz7nij2ejtq
Japanese Quail's Genetic Background Modulates Effects of Chronic Stress on Emotional Reactivity but Not Spatial Learning
2012
PLoS ONE
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They were then trained in a T-maze for seven days and their spatial learning was tested. The chronic stress protocol had an impact on resting, preening and foraging in the home cage. ...
Chronic stress is known to enhance mammals' emotional reactivity and alters several of their cognitive functions, especially spatial learning. Few studies have investigated such effects in birds. ...
in novel environments [65] . ...
doi:10.1371/journal.pone.0047475
pmid:23071811
pmcid:PMC3469497
fatcat:dtb2ype4rzfwtcy7jc5j36vof4
Q-Learning Applied to Genetic Algorithm-Fuzzy Approach for On-Line Control in Autonomous Agents
2009
Journal of Intelligent Systems
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The optimization of the fuzzy rule-based system is performed by a combination of genetic algorithms and Q-learning, whereby an agent-based predicting machine with desired performance is achieved. ...
For illustrating the validity of the described technique in control applications, the approach is evaluated on the acrobot task. ...
The embodiment of an action selection procedure should be realized as an expression of the learning procedure in an anticipatory fashion, which considers environment dynamic and makes a prediction about ...
doi:10.1515/jisys.2009.18.1-2.1
fatcat:nfbvmoqhwfenjkkz65mbpzbot4
Application of Genetic Algorithms in Stock Market Simulation
2012
Procedia - Social and Behavioral Sciences
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Next point is to show, how can be this implementation of genetic algorithms used in learning process of simulation. ...
It is difficult to predict changes in prices of stocks because of ma ny parameters in behavioral algorithms. There is also problem with learning soft-skills because of many variables. ...
Holding shares is not considered in this model. Decision function is created by GP procedures and distribution of profits should mount to normal distribution. ...
doi:10.1016/j.sbspro.2012.06.619
fatcat:hnnerrr6fvdull53zkj4zwugkm
Transfer learning in genome-wide association studies with knockoffs
[article]
2021
arXiv
pre-print
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for, and efficiently learn from the genetic variation associated to diverse ancestries. ...
Finally, we apply these methods to analyze several phenotypes in the UK Biobank data set, demonstrating that transfer learning helps knockoffs discover more numerous associations in the data collected ...
The three transfer learning methods introduced in Section 2 are implemented and compared with the results of the vanilla knockoffs procedure. ...
arXiv:2108.08813v1
fatcat:vvkxdnaykfeq5lce5xzqn637eq
Selection of important variables by statistical learning in genome-wide association analysis
2009
BMC Proceedings
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Several statistical learning methods seem quite promising in this context. ...
The complexity of such analysis is multiplied when one has to consider interaction effects, be they among the genetic variations (G × G) or with environment risk factors (G × E). ...
Acknowledgements This research is supported in part by an NIH grant HL091028 and an AHA grant 0855626G. The Genetic Analysis Workshops are supported by NIH grant R01 GM031575. We thank Dr. ...
doi:10.1186/1753-6561-3-s7-s70
pmid:20018065
pmcid:PMC2795972
fatcat:tubcmuq5xfayboazupgoyf3qby
Space Radiation Alters Genotype–Phenotype Correlations in Fear Learning and Memory Tests
2018
Frontiers in Genetics
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Changes in the environment can alter genotype-phenotype relationships. ...
stability of the genetic component of fear learning and memory-related measures. ...
Robert Hitzemann, Department of Behavioral Neuroscience, OHSU, for providing the HS/Npt mice for breeding the mice used in this study. ...
doi:10.3389/fgene.2018.00404
pmid:30356920
pmcid:PMC6190902
fatcat:tvwwv4xcajdnvabmljx3fqodk4
Rule acquisition for cognitive agents by using estimation of distribution algorithms
2010
International Journal of Knowledge Engineering and Soft Data Paradigms
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In general, learning mechanisms are equipped for such agents in order to realize intellgent behaviors. ...
In this paper, we propose a new Estimation of Distribution Algorithms (EDAs) which can acquire effective rules for cognitive agents. ...
General calculation procedure of Estimation of Distribution Algorithms briefly introduced in IV. EDA-CRF proposed in V. ...
doi:10.1504/ijkesdp.2010.035905
fatcat:fdh4zkrecrcxzm7x4o25dsjkl4
A Novel Evolutionary Algorithm for Solving Static Data Allocation Problem in Distributed Database Systems
2010
2010 Second International Conference on Network Applications, Protocols and Services
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In this paper an approximate algorithm has been proposed. This algorithm is a hybrid evolutionary algorithm obtained from combining object migration learning automata and genetic algorithm. ...
transfer cost incurred in executing the queries. ...
LEARNING AUTOMATA AND GENETIC ALGORITHMS Learning automata are adaptive decision-making devices operating on unknown random environments. ...
doi:10.1109/netapps.2010.10
fatcat:yq3mku2nk5he7o63fgwe25gr5y
Accuracy of Genomic Prediction in Switchgrass ( Panicum virgatum L.) Improved by Accounting for Linkage Disequilibrium
2016
G3: Genes, Genomes, Genetics
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We evaluated prediction procedures that varied not only by learning schemes and prediction models, but also by the way the data were preprocessed to account for redundancy in marker information. ...
Genomic selection (GS) is an attractive technology to generate rapid genetic gains in switchgrass, and meet the goals of a substantial displacement of petroleum use with biofuels in the near future. ...
This research was funded in part by the following agencies and organizations: the ...
doi:10.1534/g3.115.024950
pmid:26869619
pmcid:PMC4825640
fatcat:3brf3mjhdrdbjizoglrg57m2wy
APRIORI BASED MACHINE LEARNING IN POWER DISTRIBUTION NETWORK
2018
International Journal of Advanced Research in Computer Science
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This paper proposed Apriori based machine learning algorithm to predict the loads and schedule it in the optimum way. ...
This imbalance in loads at different phases of system affects tool utilization, voltage ranges system stability and security .The comprehensive review has shown that the use of machine learning in not ...
Power distribution network in hetrogenous environment
Table I . ...
doi:10.26483/ijarcs.v9i2.5679
fatcat:2qej3tte5jgorckn4lyppe3t6m
Analyze Effects of the Genetic Programming-Based Emergence Engineering in Trustiness of Engineering Solutions
2015
International Journal of Computer Applications
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In self-organization filed, Emergence Engineering is a new idea in software engineering scope which aims at setting up emergent phenomena in categories of individuals in order to extract those phenomena ...
In this paper we analyze the effects of the clarification of the behavioral explanation in terms of trustiness of the solutions. ...
We divided them in two procedure.
Election Procedure In this challenge, one agent is elected as "commander" and all agents accordant to this choice is the distributed nature. ...
doi:10.5120/19986-1943
fatcat:v3lrp5yxabewxfccflghzi6p7q
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