The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform
Leonardo Vanneschi - One of the best experts on this subject based on the ideXlab platform.
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NK landscapes difficulty and Negative Slope Coefficient: How Sampling Influences the Results
arXiv: Artificial Intelligence, 2011Co-Authors: Leonardo Vanneschi, Sébastien Verel, Philippe Collard, Marco TomassiniAbstract:Negative Slope Coefficient is an indicator of problem hardness that has been introduced in 2004 and that has returned promising results on a large set of problems. It is based on the concept of fitness cloud and works by partitioning the cloud into a number of bins representing as many different regions of the fitness landscape. The measure is calculated by joining the bins centroids by segments and summing all their negative Slopes. In this paper, for the first time, we point out a potential problem of the Negative Slope Coefficient: we study its value for different instances of the well known NK-landscapes and we show how this indicator is dramatically influenced by the minimum number of points contained into a bin. Successively, we formally justify this behavior of the Negative Slope Coefficient and we discuss pros and cons of this measure.
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limitations of the fitness proportional negative Slope Coefficient as a difficulty measure
Genetic and Evolutionary Computation Conference, 2009Co-Authors: Leonardo Vanneschi, Andrea Valsecchi, Riccardo PoliAbstract:Fitness-Proportional Negative Slope Coefficient is a fitness landscapes measure that has recently been introduced as a potential indicator of problem hardness for optimisation. It is inspired to an older measure, the Negative Slope Coefficient, and it has been theoretically modelled. Preliminary experiments have suggested that it may be a good predictor of problem hardness. However, this measure has not undergone any convincing and comprehensive empirical testing. Our objective is to fill this gap. So, we perform empirical tests using a large set of invertible functions of unitation. We find that while this measure may correctly predict the degree of evolvability of a landscape, this does not necessarily correlate with the difficulty of problems. Some landscapes may show, for example, limited evolvability and yet be easy to solve because either solutions are already present in the initial population or the computational resources provided exceed evolvability obstacles. Or it may be impossible to solve them irrespective of their evolvability simply because they are far too vast for the computational resources provided. These situations are hardly captured by the Fitness-Proportional Negative Slope Coefficient.
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EvoWorkshops - NK Landscapes Difficulty and Negative Slope Coefficient: How Sampling Influences the Results
Lecture Notes in Computer Science, 2009Co-Authors: Leonardo Vanneschi, Sébastien Verel, Marco Tomassini, Philippe CollardAbstract:Negative Slope Coefficient is an indicator of problem hardness that has been introduced in 2004 and that has returned promising results on a large set of problems. It is based on the concept of fitness cloud and works by partitioning the cloud into a number of bins representing as many different regions of the fitness landscape. The measure is calculated by joining the bins centroids by segments and summing all their negative Slopes. In this paper, for the first time, we point out a potential problem of the Negative Slope Coefficient: we study its value for different instances of the well known NK-landscapes and we show how this indicator is dramatically influenced by the minimum number of points contained in a bin. Successively, we formally justify this behavior of the Negative Slope Coefficient and we discuss pros and cons of this measure.
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GECCO - Limitations of the fitness-proportional negative Slope Coefficient as a difficulty measure
Proceedings of the 11th Annual conference on Genetic and evolutionary computation - GECCO '09, 2009Co-Authors: Leonardo Vanneschi, Andrea Valsecchi, Riccardo PoliAbstract:Fitness-Proportional Negative Slope Coefficient is a fitness landscapes measure that has recently been introduced as a potential indicator of problem hardness for optimisation. It is inspired to an older measure, the Negative Slope Coefficient, and it has been theoretically modelled. Preliminary experiments have suggested that it may be a good predictor of problem hardness. However, this measure has not undergone any convincing and comprehensive empirical testing. Our objective is to fill this gap. So, we perform empirical tests using a large set of invertible functions of unitation. We find that while this measure may correctly predict the degree of evolvability of a landscape, this does not necessarily correlate with the difficulty of problems. Some landscapes may show, for example, limited evolvability and yet be easy to solve because either solutions are already present in the initial population or the computational resources provided exceed evolvability obstacles. Or it may be impossible to solve them irrespective of their evolvability simply because they are far too vast for the computational resources provided. These situations are hardly captured by the Fitness-Proportional Negative Slope Coefficient.
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negative Slope Coefficient and the difficulty of random 3 sat instances
Lecture Notes in Computer Science, 2008Co-Authors: Marco Tomassini, Leonardo VanneschiAbstract:In this paper we present an empirical study of the Negative Slope Coefficient (NSC) hardness statistic to characterize the difficulty of 3-SAT fitness landscapes for randomly generated problem instances. NSC correctly classifies problem instances with a low ratio of clauses to variables as easy, while instances with a ratio close to the critical point are classified as hard, as expected. Together with previous results on many different problems and fitness landscapes, the present results confirm that NSC is a useful and reliable indicator of problem difficulty.
Ronald Benner - One of the best experts on this subject based on the ideXlab platform.
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the spectral Slope Coefficient of chromophoric dissolved organic matter s275 295 as a tracer of terrigenous dissolved organic carbon in river influenced ocean margins
Limnology and Oceanography, 2012Co-Authors: Cédric G. Fichot, Ronald BennerAbstract:The present study demonstrates that the spectral Slope Coefficient of chromophoric dissolved organic matter (CDOM) between 275 nm and 295 nm (S275–295) can be used as a tracer of the percent terrigenous dissolved organic carbon (%tDOC) in river-influenced ocean margins, where rivers exert an important control on carbon dynamics and CO2 fluxes. Absorption Coefficients of CDOM and concentrations of dissolved organic carbon (DOC) and dissolved lignin were measured on a seasonal basis in the Mississippi and Atchafalaya rivers and in surface waters of the northern Gulf of Mexico (NGoM). A strong, linear relationship between lignin concentrations and CDOM absorption Coefficients indicated lignin is an important chromophore in this environment. The dual nature of lignin as an important chromophore in CDOM and as a terrigenous component of DOC facilitated development of the tracer. The applicability of the tracer relies on the existence of a strong, nonlinear relationship between S275–295 and the DOC-normalized lignin yield in rivers and along the freshwater– marine continuum in the NGoM. Physical mixing and the effects of photodegradation on S275–295 and dissolved lignin were largely responsible for maintaining this relationship, suggesting the tracer is applicable to surface waters of most river-influenced ocean margins. The spectral Slope Coefficient (S275–295) provides new capabilities to trace tDOC on synoptic scales of relevance to ocean margins and represents an important tool for improving ocean carbon budgets. The key processes controlling carbon transformations in ocean margins remain poorly quantified, thereby limiting our understanding of how the coastal ocean affects the ocean carbon cycle and atmospheric CO2. Ocean margins account for , 10% of the global ocean surface area but
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The spectral Slope Coefficient of chromophoric dissolved organic matter (S275–295) as a tracer of terrigenous dissolved organic carbon in river‐influenced ocean margins
Limnology and Oceanography, 2012Co-Authors: Cédric G. Fichot, Ronald BennerAbstract:The present study demonstrates that the spectral Slope Coefficient of chromophoric dissolved organic matter (CDOM) between 275 nm and 295 nm (S275–295) can be used as a tracer of the percent terrigenous dissolved organic carbon (%tDOC) in river-influenced ocean margins, where rivers exert an important control on carbon dynamics and CO2 fluxes. Absorption Coefficients of CDOM and concentrations of dissolved organic carbon (DOC) and dissolved lignin were measured on a seasonal basis in the Mississippi and Atchafalaya rivers and in surface waters of the northern Gulf of Mexico (NGoM). A strong, linear relationship between lignin concentrations and CDOM absorption Coefficients indicated lignin is an important chromophore in this environment. The dual nature of lignin as an important chromophore in CDOM and as a terrigenous component of DOC facilitated development of the tracer. The applicability of the tracer relies on the existence of a strong, nonlinear relationship between S275–295 and the DOC-normalized lignin yield in rivers and along the freshwater– marine continuum in the NGoM. Physical mixing and the effects of photodegradation on S275–295 and dissolved lignin were largely responsible for maintaining this relationship, suggesting the tracer is applicable to surface waters of most river-influenced ocean margins. The spectral Slope Coefficient (S275–295) provides new capabilities to trace tDOC on synoptic scales of relevance to ocean margins and represents an important tool for improving ocean carbon budgets. The key processes controlling carbon transformations in ocean margins remain poorly quantified, thereby limiting our understanding of how the coastal ocean affects the ocean carbon cycle and atmospheric CO2. Ocean margins account for , 10% of the global ocean surface area but
Cédric G. Fichot - One of the best experts on this subject based on the ideXlab platform.
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the spectral Slope Coefficient of chromophoric dissolved organic matter s275 295 as a tracer of terrigenous dissolved organic carbon in river influenced ocean margins
Limnology and Oceanography, 2012Co-Authors: Cédric G. Fichot, Ronald BennerAbstract:The present study demonstrates that the spectral Slope Coefficient of chromophoric dissolved organic matter (CDOM) between 275 nm and 295 nm (S275–295) can be used as a tracer of the percent terrigenous dissolved organic carbon (%tDOC) in river-influenced ocean margins, where rivers exert an important control on carbon dynamics and CO2 fluxes. Absorption Coefficients of CDOM and concentrations of dissolved organic carbon (DOC) and dissolved lignin were measured on a seasonal basis in the Mississippi and Atchafalaya rivers and in surface waters of the northern Gulf of Mexico (NGoM). A strong, linear relationship between lignin concentrations and CDOM absorption Coefficients indicated lignin is an important chromophore in this environment. The dual nature of lignin as an important chromophore in CDOM and as a terrigenous component of DOC facilitated development of the tracer. The applicability of the tracer relies on the existence of a strong, nonlinear relationship between S275–295 and the DOC-normalized lignin yield in rivers and along the freshwater– marine continuum in the NGoM. Physical mixing and the effects of photodegradation on S275–295 and dissolved lignin were largely responsible for maintaining this relationship, suggesting the tracer is applicable to surface waters of most river-influenced ocean margins. The spectral Slope Coefficient (S275–295) provides new capabilities to trace tDOC on synoptic scales of relevance to ocean margins and represents an important tool for improving ocean carbon budgets. The key processes controlling carbon transformations in ocean margins remain poorly quantified, thereby limiting our understanding of how the coastal ocean affects the ocean carbon cycle and atmospheric CO2. Ocean margins account for , 10% of the global ocean surface area but
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The spectral Slope Coefficient of chromophoric dissolved organic matter (S275–295) as a tracer of terrigenous dissolved organic carbon in river‐influenced ocean margins
Limnology and Oceanography, 2012Co-Authors: Cédric G. Fichot, Ronald BennerAbstract:The present study demonstrates that the spectral Slope Coefficient of chromophoric dissolved organic matter (CDOM) between 275 nm and 295 nm (S275–295) can be used as a tracer of the percent terrigenous dissolved organic carbon (%tDOC) in river-influenced ocean margins, where rivers exert an important control on carbon dynamics and CO2 fluxes. Absorption Coefficients of CDOM and concentrations of dissolved organic carbon (DOC) and dissolved lignin were measured on a seasonal basis in the Mississippi and Atchafalaya rivers and in surface waters of the northern Gulf of Mexico (NGoM). A strong, linear relationship between lignin concentrations and CDOM absorption Coefficients indicated lignin is an important chromophore in this environment. The dual nature of lignin as an important chromophore in CDOM and as a terrigenous component of DOC facilitated development of the tracer. The applicability of the tracer relies on the existence of a strong, nonlinear relationship between S275–295 and the DOC-normalized lignin yield in rivers and along the freshwater– marine continuum in the NGoM. Physical mixing and the effects of photodegradation on S275–295 and dissolved lignin were largely responsible for maintaining this relationship, suggesting the tracer is applicable to surface waters of most river-influenced ocean margins. The spectral Slope Coefficient (S275–295) provides new capabilities to trace tDOC on synoptic scales of relevance to ocean margins and represents an important tool for improving ocean carbon budgets. The key processes controlling carbon transformations in ocean margins remain poorly quantified, thereby limiting our understanding of how the coastal ocean affects the ocean carbon cycle and atmospheric CO2. Ocean margins account for , 10% of the global ocean surface area but
Marco Tomassini - One of the best experts on this subject based on the ideXlab platform.
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NK landscapes difficulty and Negative Slope Coefficient: How Sampling Influences the Results
arXiv: Artificial Intelligence, 2011Co-Authors: Leonardo Vanneschi, Sébastien Verel, Philippe Collard, Marco TomassiniAbstract:Negative Slope Coefficient is an indicator of problem hardness that has been introduced in 2004 and that has returned promising results on a large set of problems. It is based on the concept of fitness cloud and works by partitioning the cloud into a number of bins representing as many different regions of the fitness landscape. The measure is calculated by joining the bins centroids by segments and summing all their negative Slopes. In this paper, for the first time, we point out a potential problem of the Negative Slope Coefficient: we study its value for different instances of the well known NK-landscapes and we show how this indicator is dramatically influenced by the minimum number of points contained into a bin. Successively, we formally justify this behavior of the Negative Slope Coefficient and we discuss pros and cons of this measure.
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EvoWorkshops - NK Landscapes Difficulty and Negative Slope Coefficient: How Sampling Influences the Results
Lecture Notes in Computer Science, 2009Co-Authors: Leonardo Vanneschi, Sébastien Verel, Marco Tomassini, Philippe CollardAbstract:Negative Slope Coefficient is an indicator of problem hardness that has been introduced in 2004 and that has returned promising results on a large set of problems. It is based on the concept of fitness cloud and works by partitioning the cloud into a number of bins representing as many different regions of the fitness landscape. The measure is calculated by joining the bins centroids by segments and summing all their negative Slopes. In this paper, for the first time, we point out a potential problem of the Negative Slope Coefficient: we study its value for different instances of the well known NK-landscapes and we show how this indicator is dramatically influenced by the minimum number of points contained in a bin. Successively, we formally justify this behavior of the Negative Slope Coefficient and we discuss pros and cons of this measure.
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negative Slope Coefficient and the difficulty of random 3 sat instances
Lecture Notes in Computer Science, 2008Co-Authors: Marco Tomassini, Leonardo VanneschiAbstract:In this paper we present an empirical study of the Negative Slope Coefficient (NSC) hardness statistic to characterize the difficulty of 3-SAT fitness landscapes for randomly generated problem instances. NSC correctly classifies problem instances with a low ratio of clauses to variables as easy, while instances with a ratio close to the critical point are classified as hard, as expected. Together with previous results on many different problems and fitness landscapes, the present results confirm that NSC is a useful and reliable indicator of problem difficulty.
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EvoWorkshops - Negative Slope Coefficient and the difficulty of random 3-SAT instances
Lecture Notes in Computer Science, 2008Co-Authors: Marco Tomassini, Leonardo VanneschiAbstract:In this paper we present an empirical study of the Negative Slope Coefficient (NSC) hardness statistic to characterize the difficulty of 3-SAT fitness landscapes for randomly generated problem instances. NSC correctly classifies problem instances with a low ratio of clauses to variables as easy, while instances with a ratio close to the critical point are classified as hard, as expected. Together with previous results on many different problems and fitness landscapes, the present results confirm that NSC is a useful and reliable indicator of problem difficulty.
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A Comprehensive View of Fitness Landscapes with Neutrality and Fitness Clouds
2007Co-Authors: Leonardo Vanneschi, Sébastien Verel, Philippe Collard, Marco Tomassini, Yuri Pirola, Giancarlo MauriAbstract:We define a set of measures that capture some different aspects of neutrality in evolutionary algorithms fitness landscapes from a qualitative point of view. If considered all together, these measures offer a rather complete picture of the characteristics of fitness landscapes bound to neutrality and may be used as broad indicators of problem hardness. We compare the results returned by these measures with the ones of negative Slope Coefficient, a quantitative measure of problem hardness that has been recently defined and with success rate statistics on a well known genetic programming benchmark: the multiplexer problem. In order to efficaciously study the search space, we use a sampling technique that has recently been introduced and we show its suitability on this problem.
Shailesh Bihari - One of the best experts on this subject based on the ideXlab platform.
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Dose-Dependent Effects of Statins for Patients with Aneurysmal Subarachnoid Hemorrhage: Meta-Regression Analysis
World Neurosurgery, 2018Co-Authors: Shivesh Prakash, Santosh Poonnoose, Shailesh BihariAbstract:Objective The study uses meta-regression analysis to quantify the dose-dependent effects of statin pharmacotherapy on vasospasm, delayed ischemic neurologic deficits (DIND), and mortality in aneurysmal subarachnoid hemorrhage. Methods Prospective, retrospective observational studies, and randomized controlled trials (RCTs) were retrieved by a systematic database search. Summary estimates were expressed as absolute risk (AR) for a given statin dose or control (placebo). Meta-regression using inverse variance weighting and robust variance estimation was performed to assess the effect of statin dose on transformed AR in a random effects model. Dose-dependence of predicted AR with 95% confidence interval (CI) was recovered by using Miller's Freeman–Tukey inverse. Results The database search and study selection criteria yielded 18 studies (2594 patients) for analysis. These included 12 RCTs, 4 retrospective observational studies, and 2 prospective observational studies. Twelve studies investigated simvastatin, whereas the remaining studies investigated atorvastatin, pravastatin, or pitavastatin, with simvastatin-equivalent doses ranging from 20 to 80 mg. Meta-regression revealed dose-dependent reductions in Freeman–Tukey-transformed AR of vasospasm (Slope Coefficient −0.00404, 95% CI −0.00720 to −0.00087; P = 0.0321), DIND (Slope Coefficient −0.00316, 95% CI −0.00586 to −0.00047; P = 0.0392), and mortality (Slope Coefficient −0.00345, 95% CI −0.00623 to −0.00067; P = 0.0352). Conclusions The present meta-regression provides weak evidence for dose-dependent reductions in vasospasm, DIND and mortality associated with acute statin use after aneurysmal subarachnoid hemorrhage. However, the analysis was limited by substantial heterogeneity among individual studies. Greater dosing strategies are a potential consideration for future RCTs.
