scholarly journals VolcanoML

2021 ◽  
Vol 14 (11) ◽  
pp. 2167-2176
Author(s):  
Yang Li ◽  
Yu Shen ◽  
Wentao Zhang ◽  
Jiawei Jiang ◽  
Bolin Ding ◽  
...  
Keyword(s):  
Parameter Tuning ◽  
Building Blocks ◽  
Search Space ◽  
Database Systems ◽  
Execution Plan ◽  
Search Spaces ◽  
Systematic Exploration ◽  
Decomposition Strategies ◽  
Execution Model ◽  
The One

End-to-end AutoML has attracted intensive interests from both academia and industry, which automatically searches for ML pipelines in a space induced by feature engineering, algorithm/model selection, and hyper-parameter tuning. Existing AutoML systems, however, suffer from scalability issues when applying to application domains with large, high-dimensional search spaces. We present VOLCANOML, a scalable and extensible framework that facilitates systematic exploration of large AutoML search spaces. VOLCANOML introduces and implements basic building blocks that decompose a large search space into smaller ones, and allows users to utilize these building blocks to compose an execution plan for the AutoML problem at hand. VOLCANOML further supports a Volcano-style execution model - akin to the one supported by modern database systems - to execute the plan constructed. Our evaluation demonstrates that, not only does VOLCANOML raise the level of expressiveness for search space decomposition in AutoML, it also leads to actual findings of decomposition strategies that are significantly more efficient than the ones employed by state-of-the-art AutoML systems such as auto-sklearn.

scholarly journals Efficient exploratory clustering analyses in large-scale exploration processes

2021 ◽  
Author(s):  
Manuel Fritz ◽  
Michael Behringer ◽  
Dennis Tschechlov ◽  
Holger Schwarz
Keyword(s):  
Large Scale ◽  
Clustering Algorithm ◽  
Comprehensive Evaluation ◽  
State Of The Art ◽  
Clustering Algorithms ◽  
Search Space ◽  
Large Datasets ◽  
Search Spaces ◽  
Multiple Challenges ◽  
The One

AbstractClustering is a fundamental primitive in manifold applications. In order to achieve valuable results in exploratory clustering analyses, parameters of the clustering algorithm have to be set appropriately, which is a tremendous pitfall. We observe multiple challenges for large-scale exploration processes. On the one hand, they require specific methods to efficiently explore large parameter search spaces. On the other hand, they often exhibit large runtimes, in particular when large datasets are analyzed using clustering algorithms with super-polynomial runtimes, which repeatedly need to be executed within exploratory clustering analyses. We address these challenges as follows: First, we present LOG-Means and show that it provides estimates for the number of clusters in sublinear time regarding the defined search space, i.e., provably requiring less executions of a clustering algorithm than existing methods. Second, we demonstrate how to exploit fundamental characteristics of exploratory clustering analyses in order to significantly accelerate the (repetitive) execution of clustering algorithms on large datasets. Third, we show how these challenges can be tackled at the same time. To the best of our knowledge, this is the first work which simultaneously addresses the above-mentioned challenges. In our comprehensive evaluation, we unveil that our proposed methods significantly outperform state-of-the-art methods, thus especially supporting novice analysts for exploratory clustering analyses in large-scale exploration processes.

Decomposition strategies for configuration problems

2003 ◽  
Vol 17 (1) ◽  
pp. 51-73 ◽  
Author(s):  
DIEGO MAGRO ◽  
PIETRO TORASSO
Keyword(s):  
Search Space ◽  
Computational Effort ◽  
Decomposition Techniques ◽  
Test Bed ◽  
Search Spaces ◽  
Different Types ◽  
Decomposition Strategies ◽  
The Impact ◽  
Representation Formalism ◽  
Configuration Problem

The paper introduces and discusses the notion of decomposition of a configuration problem within the framework of a structured logical approach. The paper describes under which conditions a given configuration problem can be decomposed into a set of noninteracting subproblems and how to exploit such a decomposition, both for improving the performance of the configurator and for supporting interactive configuration. Different kinds of decomposition are considered, but all of them exploit, as much as possible, the explicit representation of the partonomic relations in thelanguage, a KL-One like representation formalism augmented with constraints for expressing complex interrole relations. The paper introduces a notion of boundness among constraints, which is used for formally specifying different types of decomposition. One decomposition strategy aims at singling out the components and subcomponents that are directly related to the constraints put by the user's requirements; the configurator exploits such decomposition by first configuring that portion of the product and then configuring the parts that are not related to the user's requirements. Another decomposition strategy verifies whether the set of constraints for the product to be configured can be split into a set of noninteracting problems. In such a case the configurator solves the configuration problem by splitting the whole search space into a set of smaller search spaces. Different combinations of these two decomposition techniques are considered, and the impact of the decomposition strategies on the performance of the configurator is evaluated via a set of experiments using the configuration of computer systems as a test bed. The results of the experiments show a significant reduction of the computational effort (both in terms of number of backtrackings and in CPU time) when decomposition strategies are used.

scholarly journals A novel approach to the computation of one-loop three- and four-point functions: I. The real mass case

2019 ◽  
Vol 2019 (11) ◽  
Author(s):  
J Ph Guillet ◽  
E Pilon ◽  
Y Shimizu ◽  
M S Zidi
Keyword(s):  
Building Blocks ◽  
The Real ◽  
Alternative Method ◽  
Novel Approach ◽  
Reduction Methods ◽  
Real Mass ◽  
Novel Method ◽  
Algebraic Reduction ◽  
The One ◽  
Mass Case

Abstract This article is the first of a series of three presenting an alternative method of computing the one-loop scalar integrals. This novel method enjoys a couple of interesting features as compared with the method closely following ’t Hooft and Veltman adopted previously. It directly proceeds in terms of the quantities driving algebraic reduction methods. It applies to the three-point functions and, in a similar way, to the four-point functions. It also extends to complex masses without much complication. Lastly, it extends to kinematics more general than that of the physical, e.g., collider processes relevant at one loop. This last feature may be useful when considering the application of this method beyond one loop using generalized one-loop integrals as building blocks.

scholarly journals Blood Coagulation Algorithm: A Novel Bio-Inspired Meta-Heuristic Algorithm for Global Optimization

Mathematics ◽  
2021 ◽  
Vol 9 (23) ◽  
pp. 3011
Author(s):  
Drishti Yadav
Keyword(s):  
Blood Coagulation ◽  
Heuristic Algorithms ◽  
Cooperative Behavior ◽  
Real Life ◽  
Search Space ◽  
Population Based ◽  
Test Analysis ◽  
Search Spaces ◽  
Consistent Performance ◽  
The Comparative Study

This paper introduces a novel population-based bio-inspired meta-heuristic optimization algorithm, called Blood Coagulation Algorithm (BCA). BCA derives inspiration from the process of blood coagulation in the human body. The underlying concepts and ideas behind the proposed algorithm are the cooperative behavior of thrombocytes and their intelligent strategy of clot formation. These behaviors are modeled and utilized to underscore intensification and diversification in a given search space. A comparison with various state-of-the-art meta-heuristic algorithms over a test suite of 23 renowned benchmark functions reflects the efficiency of BCA. An extensive investigation is conducted to analyze the performance, convergence behavior and computational complexity of BCA. The comparative study and statistical test analysis demonstrate that BCA offers very competitive and statistically significant results compared to other eminent meta-heuristic algorithms. Experimental results also show the consistent performance of BCA in high dimensional search spaces. Furthermore, we demonstrate the applicability of BCA on real-world applications by solving several real-life engineering problems.

scholarly journals A systematic design approach for objectifying Building with Nature solutions

2021 ◽  
Vol 7 ◽  
pp. 29-50
Author(s):  
Mindert De Vries ◽  
Mark Van Koningsveld ◽  
Stefan Aarninkhof ◽  
Huib De Vriend
Keyword(s):  
Building Blocks ◽  
Hydraulic Engineering ◽  
Systematic Design ◽  
The Social ◽  
Building With Nature ◽  
Engineering Designs ◽  
Hydraulic Infrastructure ◽  
Crucial Information ◽  
Development Phases ◽  
The One

Hydraulic engineering infrastructure is supposed to keep functioning for many years and is likely to interfere with both the natural and the social environment at various scales. Due to its long life-cycle, hydraulic infrastructure is bound to face changing environmental conditions as well as changes in societal views on acceptable solutions. This implies that sustainability and adaptability are/should be important attributes of the design, the development and operation of hydraulic engineering infrastructure. Sustainability and adaptability are central to the Building with Nature (BwN) approach. Although nature-based design philosophies, such as BwN, have found broad support, a key issue that inhibits a wider mainstream implementation is the lack of a method to objectify BwN concepts. With objectifying, we mean turning the implicit into an explicit engineerable ‘object’, on the one hand, and specifying clear design ‘objectives’, on the other. This paper proposes the “Frame of Reference” approach as a method to systematically transform BwN concepts into functionally specified engineering designs. It aids the rationalisation of BwN concepts and facilitates the transfer of crucial information between project development phases, which benefits the uptake, acceptance and eventually the successful realisation of BwN solutions. It includes an iterative approach that is well suited for assessing status changes of naturally dynamic living building blocks of BwN solutions. The applicability of the approach is shown for a case that has been realised in the Netherlands. Although the example is Dutch, the method, as such, is generically applicable.

scholarly journals THE ONE WHO MADE THE LOCK ALSO MADE THE KEY

2020 ◽  
Vol 23 (45) ◽  
pp. 34-48
Author(s):  
James Martel
Keyword(s):  
Thomas Hobbes ◽  
State Power ◽  
Building Blocks ◽  
Human Community ◽  
The One ◽  
Made In ◽  
The Way

In this essay, I look at the way that Thomas Hobbes offers not only the building blocks for state power and sovereignty (as he is so famous for doing) but also a basis by which to resist those very things. Even as Hobbes constructs a vast and awe inspiring network of sovereign forms of authority, he shows how those forms are produced, in a sense, out of thin air. Hobbes’ understanding of language as a series of decisions that are made in ways that render the sovereign’s own decision derivative, as well as his understanding of theology as offering us a vision of a human community who must collectively decide on things in the absence of God’s ongoing instruction both serve to undermine and expose the emptiness of sovereign pronouncements. In this way, Hobbes can be read as a radical theorist and a theorist of resisting the very encryption that he is at the same time responsible for theorizing and producing.

scholarly journals Bicluster CC Algoritm Analysis to Identify Patterns of Food Insecurity in Indonesia

2020 ◽  
Vol 17 (2) ◽  
pp. 325-338
Author(s):  
Raditya Novidianto ◽  
Rini Irfani
Keyword(s):  
Food Insecurity ◽  
Agricultural Sector ◽  
Parameter Tuning ◽  
Mean Square ◽  
Calorie Consumption ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
The Mean ◽  
Best Parameter ◽  
The One

Indonesia is known as an agricultural country. This means that most of the population work in the agricultural sector related to food. However, food insecurity still occurs in Indonesia. With the COVID-19 pandemic, the Food and Agriculture Organization (FAO) stated that there was a threat of food scarcity which had an impact on food insecurity conditions. This would undermine the second goal of the SDGs, which is to end hunger and create sustainable agriculture. The purpose of this study was to determine the spatial pattern of food insecurity in each province in Indonesia using the bicluster method. The data used are data from Susenas and Sakernas by BPS in 2019. Several studies show that the bicluster method with the CC algorithm shows that each province group has a different characteristic pattern. In the bicluster approach, the researcher runs parameter tuning to select the best parameter based on the Mean Square Residual in Volume (MSR / V). The CC algorithm tries to get a bicluster with a low MSR value, therefore the best parameter is the one that produces the smallest MSR / V value, in this study the smallest MSR / V is 0,01737 with δ = 0,01. The application of the CC biclustering algorithm to the food insecurity structure in Indonesia results in 5 bicluster. Bicluster 1 consists of 15 provinces with 8 variables, Bicluster 2 consists of 10 provinces with 5 variables, Bicluster 3 consists of 3 provinces with 7 variables, Bicluster 4 consists of 4 provinces with 4 variables and Bicluster 5 consists of 2 provinces with 5 variables. Biculster 4 represents a cluster of food insecurity areas with the characteristics of the bicluster P0, P1, P2 and calorie consumption of less than 1400 KKAL.

scholarly journals Scaling Up AND/OR Abstraction Sampling

2020 ◽  
Author(s):  
Kalev Kask ◽  
Bobak Pezeshki ◽  
Filjor Broka ◽  
Alexander Ihler ◽  
Rina Dechter
Keyword(s):  
Importance Sampling ◽  
State Of The Art ◽  
Empirical Evaluation ◽  
Search Space ◽  
Scaling Up ◽  
Sampling Scheme ◽  
Search Spaces

Abstraction Sampling (AS) is a recently introduced enhancement of Importance Sampling that exploits stratification by using a notion of abstractions: groupings of similar nodes into abstract states. It was previously shown that AS performs particularly well when sampling over an AND/OR search space; however, existing schemes were limited to ``proper'' abstractions in order to ensure unbiasedness, severely hindering scalability. In this paper, we introduce AOAS, a new Abstraction Sampling scheme on AND/OR search spaces that allow more flexible use of abstractions by circumventing the properness requirement. We analyze the properties of this new algorithm and, in an extensive empirical evaluation on five benchmarks, over 480 problems, and comparing against other state of the art algorithms, illustrate AOAS's properties and show that it provides a far more powerful and competitive Abstraction Sampling framework.

scholarly journals Minimization in Cooperative Response to Failing Database Queries

1997 ◽  
Vol 06 (02) ◽  
pp. 95-149 ◽  
Author(s):  
Parke Godfrey
Keyword(s):  
Optimal Algorithm ◽  
Simple Algorithm ◽  
Search Space ◽  
Database Systems ◽  
Identification Problems ◽  
Database Queries ◽  
The Past ◽  
Cause Of Failure ◽  
Algorithmic Approaches ◽  
Answer Set

When a query fails, it is more cooperative to identify the cause of failure, rather than just to report the empty answer set. When there is not a cause per se for the query's failure, it is then worthwhile to report the part of the query which failed. To identify a Minimal Failing Subquery (MFS) of the query is the best way to do this. (This MFS is not unique; there may be many of them.) Likewise, to identify a Maximal Succeeding Subquery (XSS) can help a user to recast a new query that leads to a non-empty answer set. Database systems do not provide the functionality of these types of cooperative responses. This may be, in part, because algorithmic approaches to finding the MFSs and the XSSs to a failing query are not obvious. The search space of subqueries is large. Despite work on MFSs in the past, the algorithmic complexity of these identification problems had remained uncharted. This paper shows the complexity profile of MFS and XSS identification. It is shown that there exists a simple algorithm for finding an MFS or an XSS by asking N subsequent queries, in which N is the length of the query. To find more MFSs (or XSSs) can be hard. It is shown that to find N MFSs (or XSSs) is NP-hard. To find k MFSs (or XSSs), for a fixed k, remains polynomial. An optimal algorithm for enumerating MFSs and XSSs, ISHMAEL, is developed and presented. The algorithm has ideal performance in enumeration, finding the first answers quickly, and only decaying toward intractability in a predictable manner as further answers are found. The complexity results and the algorithmic approaches given in this paper should allow for the construction of cooperative facilities which identify MFSs and XSSs for database systems. These results are relevant to a number of problems outside of databases too, and may find further application.

Global Path Planning for Full-Area Coverage Robotic Systems by Employing an Active Genetic Algorithm

2011 ◽  
Vol 328-330 ◽  
pp. 1881-1886
Author(s):  
Cen Zeng ◽  
Qiang Zhang ◽  
Xiao Peng Wei
Keyword(s):  
Genetic Algorithm ◽  
Path Planning ◽  
High Performance ◽  
Search Space ◽  
Area Coverage ◽  
Robotic Systems ◽  
Genetic Operators ◽  
A Algorithm ◽  
Coverage Path Planning ◽  
Search Spaces

Genetic algorithm (GA), a kind of global and probabilistic optimization algorithms with high performance, have been paid broad attentions by researchers world wide and plentiful achievements have been made.This paper presents a algorithm to develop the path planning into a given search space using GA in the order of full-area coverage and the obstacle avoiding automatically. Specific genetic operators (such as selection, crossover, mutation) are introduced, and especially the handling of exceptional situations is described in detail. After that, an active genetic algorithm is introduced which allows to overcome the drawbacks of the earlier version of Full-area coverage path planning algorithms.The comparison between some of the well-known algorithms and genetic algorithm is demonstrated in this paper. our path-planning genetic algorithm yields the best performance on the flexibility and the coverage. This meets the needs of polygon obstacles. For full-area coverage path-planning, a genotype that is able to address the more complicated search spaces.

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