Filters








6,732 Hits in 4.1 sec

A Survey on Semantics in Automated Data Science [article]

Udayan Khurana and Kavitha Srinivas and Horst Samulowitz
2022 arXiv   pre-print
In this paper we discuss important shortcomings of current automated data science solutions and machine learning.  ...  In recent years, we have witnessed a surge in tools and techniques for automated machine learning.  ...  More interestingly, the approach presented in [Bhowan et al., 2013] uses multi-objective genetic programming to evolve a set of accurate and diverse models via biasing the fitness function accordingly  ... 
arXiv:2205.08018v1 fatcat:2rrsqvcl65hsdf7qztc5lfau2q

AI Descartes: Combining Data and Theory for Derivable Scientific Discovery [article]

Cristina Cornelio, Sanjeeb Dash, Vernon Austel, Tyler Josephson, Joao Goncalves, Kenneth Clarkson, Nimrod Megiddo, Bachir El Khadir, Lior Horesh
2021 arXiv   pre-print
We envision that this combination will enable derivable discovery of fundamental laws of science.  ...  In contrast, machine-learning algorithms automate the construction of accurate data-driven models while consuming large amounts of data.  ...  Department of Energy (DOE), Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences (DE-FG02-17ER16362), as well as startup funding from the University of Maryland,  ... 
arXiv:2109.01634v2 fatcat:ycemjaygo5bknjaqp4upopxjtu

Current State and Challenges of Automatic Planning in Web Service Composition [article]

Sleiman Rabah and Dan Ni and Payam Jahanshahi and Luis Felipe Guzman
2011 arXiv   pre-print
This first gives a definition of Web Service Composition and the motivation and goal of it. It then explores into why we need automated Web Service Compositions and formally defines the domains.  ...  Techniques and solutions are proposed by the papers we surveyed to solve the current difficulty of automated Web Service Composition.  ...  ACKNOWLEDGEMENTS The inclusion of images and examples from external sources is only for non-commercial educational purposes, and their use is hereby acknowledged.  ... 
arXiv:1107.1932v1 fatcat:ge7tgp76qzayzjmvq7aujqf7f4

AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity [article]

Silviu-Marian Udrescu, Andrew Tan, Jiahai Feng, Orisvaldo Neto, Tailin Wu, Max Tegmark
2020 arXiv   pre-print
We develop a method for discovering generalized symmetries (arbitrary modularity in the computational graph of a formula) from gradient properties of a neural network fit.  ...  It improves on the previous state-of-the-art by typically being orders of magnitude more robust toward noise and bad data, and also by discovering many formulas that stumped previous methods.  ...  Traditionally, it has relied on human intuition, leading to the discovery of some of the most famous formulas in science.  ... 
arXiv:2006.10782v2 fatcat:qrd3xywvabfrnd4abvnxnc7mka

Reverse Engineering of Option Pricing: An AI Application

Bodo Herzog, Sufyan Osamah
2019 International Journal of Financial Studies  
It circumvents the limitations of finance theory, among others strong assumptions and numerical approximations under the Black–Scholes model.  ...  We utilize artificial intelligence in order to numerically compute the prices of options. The data consist of more than 5000 call- and put-options from the German stock market.  ...  Thus, there is a pressing scientific application of our reverse engineering methodology in finance. Our goal is to find option pricing formulas by employing the method of genetic programming.  ... 
doi:10.3390/ijfs7040068 fatcat:vbupubrabfhc5jb2n6q6t5g7ra

Collision-Free Composite ?3–Splines Generation for Nonholonomic Mobile Robots by Parallel Variable-Length Genetic Algorithm

Jiun-Hau Wei, Jing-Sin Liu
2008 2008 International Conference on Computational Intelligence for Modelling Control & Automation  
Based on the variable-length genetic algorithm implemented in the architecture of island parallel genetic algorithm (IPGA), the path planner automatically selects the number and locations of a sequence  ...  A G 3 -continuous path planner for wheeled nonholonomic mobile robots is presented, where the path is a composite curve composed of a number of η 3 -splines segments.  ...  Numerical techniques are devised to solve the problems in different context.  ... 
doi:10.1109/cimca.2008.200 dblp:conf/cimca/WeiL08 fatcat:sthfydjcgnbs7jzbm63bgnyyxy

Search-Based Software Testing: Past, Present and Future

Phil McMinn
2011 2011 IEEE Fourth International Conference on Software Testing, Verification and Validation Workshops  
Search-Based Software Testing is the use of a meta-heuristic optimizing search technique, such as a Genetic Algorithm, to automate or partially automate a testing task; for example the automatic generation  ...  of test data.  ...  Automated Oracles via Testability Transformation Another way in which transformation may be utilized is to produce alternative versions of a program that can be used to check the original.  ... 
doi:10.1109/icstw.2011.100 dblp:conf/icst/McMinn11 fatcat:o233spip6nfiletm4r6z6je6sa

Universal Differential Equations for Scientific Machine Learning [article]

Christopher Rackauckas, Yingbo Ma, Julius Martensen, Collin Warner, Kirill Zubov, Rohit Supekar, Dominic Skinner, Ali Ramadhan, Alan Edelman
2021 arXiv   pre-print
This funnels the wide variety of SciML applications into a core set of training mechanisms which are highly optimized, stabilized for stiff equations, and compatible with distributed parallelism and GPU  ...  We demonstrate the generality of the software tooling to handle stochasticity, delays, and implicit constraints.  ...  Evolution- ary modeling of systems of ordinary differential equations with genetic programming. Genetic Programming and Evolvable Machines, 1(4):309- 337, 2000. [76] Khalid Raza and Rafat Parveen.  ... 
arXiv:2001.04385v4 fatcat:megacwjw2fbwxkwcnxw7wploia

Computer algebra in the life sciences

Michael P. Barnett
2002 ACM SIGSAM Bulletin  
mathematical methods that are used, (4) mentions the benefits of CA, and (5) suggests some topics for future work.  ...  This note (1) provides references to recent work that applies computer algebra (CA) to the life sciences, (2) cites literature that explains the biological background of each application, (3) states the  ...  Krandick of Drexel University for asking the question that got this survey started, and to M. Miller of the University of South Carolina for numerous additions to the draft.  ... 
doi:10.1145/641239.641242 fatcat:binjpnwk3ngkpbvl4e2rjxwy5q

2021 Index IEEE Transactions on Automation Science and Engineering Vol. 18

2021 IEEE Transactions on Automation Science and Engineering  
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  ., +, TASE July 2021 1064-1073 Discovery and Quality Evaluation of Software Component Behavioral Mod-Automated 3-D Deformation of a Soft Object Using a Continuum Robot.  ...  ., +, TASE April 2021 398-400 Approximation algorithms Wafer Defect Inspection Optimization With Partial Coverage-A Numerical Approach.  ... 
doi:10.1109/tase.2021.3120615 fatcat:ybfn4kfdvjfipbty7z3mocjjci

Improving Trust in Composite eServices Via Run-Time Participants Testing [chapter]

Flavio Corradini, Francesco De Angelis, Andrea Polini, Alberto Polzonetti
2008 Lecture Notes in Computer Science  
perceived system misbehavior. e-Services often handle personal and sensible data, therefore trust on the behavior of the system becomes of primary importance.  ...  In this paper, focusing on run-time composition of e-services, we provide an approach that reduces the possibility that the system will fail as consequence of interoperability issues among runtime discovered  ...  Numerous attempts try to overcome these drawbacks automating the generation of these kind of data.  ... 
doi:10.1007/978-3-540-85204-9_24 fatcat:zj56yschvnghzjxdgck5xrwvwa

The Spiral Discovery Network as an Automated General-Purpose Optimization Tool

Adam B. Csapo
2018 Complexity  
In this paper, a neural network-based formulation of SDM is proposed together with a set of automatic update rules that makes it suitable for both semiautomated and automated forms of optimization.  ...  The behavior of the generalized SDM model, referred to as the Spiral Discovery Network (SDN), and its applicability to nondifferentiable nonconvex optimization problems are elucidated through simulation  ...  Conclusions In this paper, an extended, automated variant of the Spiral Discovery Method is proposed.  ... 
doi:10.1155/2018/1947250 fatcat:pc2mmuxi4jgwfdqpl3lukas32i

Ingeneue: A versatile tool for reconstituting genetic networks, with examples from the segment polarity network

Eli Meir, Edwin M. Munro, Garrett M. Odell, George Von Dassow
2002 Journal of Experimental Zoology  
Our software program Ingeneue, written in Java, lets the user quickly turn a map of a genetic network into a dynamical model consisting of a set of ordinary differential equations.  ...  Here we describe a software tool for synthesizing molecular genetic data into models of genetic networks.  ...  DeLill Nasser, program director in genetics at NSF.  ... 
doi:10.1002/jez.10187 pmid:12362430 fatcat:u4nih2u5abdfzgrmjlhw3j2faq

A Preliminary Review of Influential Works in Data-Driven Discovery [article]

Mark Stalzer, Chris Mentzel
2015 arXiv   pre-print
The Gordon and Betty Moore Foundation ran an Investigator Competition as part of its Data-Driven Discovery Initiative in 2014.  ...  We received about 1,100 applications and each applicant had the opportunity to list up to five influential works in the general field of "Big Data" for scientific discovery.  ...  Program and its (former) Chief Program Officer, Vicki Chandler.  ... 
arXiv:1503.08776v2 fatcat:2pemwbwirbhfbktdjbhy5dffa4

Computational model discovery with reinforcement learning [article]

Maxime Bassenne, Adrián Lozano-Durán
2019 arXiv   pre-print
specificity of the solver at hand such as its numerics.  ...  In this report, we provide a high-level description of the model discovery framework with reinforcement learning.  ...  -D. acknowledges the support of NASA under grant No. NNX15AU93A and of ONR under grant No. N00014-16-S-BA10. We thank Irwan Bello for useful discussions.  ... 
arXiv:2001.00008v1 fatcat:arkrzsn22fdujnvijdu3ambrhm
« Previous Showing results 1 — 15 out of 6,732 results