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Black-Box Optimization Revisited: Improving Algorithm Selection Wizards through Massive Benchmarking [article]

Laurent Meunier, Herilalaina Rakotoarison, Pak Kan Wong, Baptiste Roziere, Jeremy Rapin, Olivier Teytaud, Antoine Moreau, Carola Doerr
2021 arXiv   pre-print
We demonstrate the advantages of such a broad collection by deriving from it Automated Black Box Optimizer (ABBO), a general-purpose algorithm selection wizard.  ...  Existing studies in black-box optimization for machine learning suffer from low generalizability, caused by a typically selective choice of problem instances used for training and testing different optimization  ...  A New Algorithm Selection Wizard: NGOpt8 Black-box optimization is sometimes dominated by evolutionary computation.  ... 
arXiv:2010.04542v3 fatcat:fdpq6w66pzbrxipzb4fxd54zza

Table of Contents

2022 IEEE Transactions on Evolutionary Computation  
Deb 476 Black-Box Optimization Revisited: Improving Algorithm Selection Wizards Through Massive Benchmarking . . . . . . . . . . . . . . . . . .  ...  Yao 431 Evolutionary Multitasking for Feature Selection in High-Dimensional Classification via Particle Swarm Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/tevc.2022.3173385 fatcat:qrxmson5ivaxni7wb4hkxi7lfy

HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements

Baoqing Cai, Yu Liu, Ce Zhang, Guangyu Zhang, Ke Zhou, Li Liu, Chunhua Li, Bin Cheng, Jie Yang, Jiashu Xing
2022 Proceedings of the 2022 International Conference on Management of Data  
The key feature of HUNTER is a hybrid architecture, which uses samples generated by Genetic Algorithm to warm-start the finer grained exploration of deep reinforcement learning.  ...  Extensive trials on CDB with public and real-world workloads demonstrate that, given the same time budget and resources, HUNTER improves performance and considerably * Baoqing Cai and Yu Liu contribute  ...  This exciting collection of research mostly models the database tuning problem as a black-box optimization problem -given X the search space of all possible configurations and 𝑈 the performance function  ... 
doi:10.1145/3514221.3517882 fatcat:nxhyrobupjhzvlo5rry6olhzvy

Emergent Solutions to High-Dimensional Multitask Reinforcement Learning

Stephen Kelly, Malcolm I. Heywood
2018 Evolutionary Computation  
Algorithms that learn through environmental interaction and delayed rewards, or reinforcement learning (RL), increasingly face the challenge of scaling to dynamic, highdimensional, and partially observable  ...  In this work, we propose a framework based on genetic programming which adaptively complexifies policies through interaction with the task.  ...  Black diamonds denote the most complex cases, with text indicating the cumulative number of operations required to train each algorithm up to that point.  ... 
doi:10.1162/evco_a_00232 pmid:29932363 fatcat:zzjrozykcrg4hlhdi2ejdalmje

The Democratization of Artificial Intelligence [chapter]

Andreas Sudmann
2019 The Democratization of Artificial Intelligence  
Stokel-Walker, Chris (2019): Feeding algorithms is a full-time job. BBC (http:// ternets-new-stars) [Last access 24.4.2019].  ...  His research focuses on the history and theory of digital media, especially the kogi(sti)cs of database technologies, big data, and algorithmic environments as well as on media of knowledge production  ...  Net Politics in the Era of Learning Algorithms" in Bochum, September 2018 led by Andreas Sudmann and with the members of the ITEA3 project "Industrial-grade Verification and Validation of Evolving Systems  ... 
doi:10.1515/9783839447192-001 fatcat:7yjb2m5p7jdt7dvkpzsuttbvf4


Frank Ulrich
2016 Ph.d.-serien for Det Teknisk-Naturvidenskabelige Fakultet, Aalborg Universitet  
Karlstown went from a period of the mobile technology idea being relatively stable, "black boxed", and rejected to see it remerge from its "black box" state in a neoteric form, changing human actors' perspective  ...  Hence, ideas stay "black boxed" until human actors enact them once again due to new input .  ...  Through this unit of analysis, we gain new insights into creative information systems artifacts, how new artifact components can be theorized, and ultimately, how artifacts can be improved.  ... 
doi:10.5278/ fatcat:l7h4zscgnbel3pxe7ipagbjnra

Message from the general chair

Benjamin C. Lee
2015 2015 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)  
We believe that this model selection approach can be applied to more sophisticated tagging algorithms and improve their robustness even further.  ...  is close to that given by the optimal solution of the exact algorithm.  ... 
doi:10.1109/ispass.2015.7095776 dblp:conf/ispass/Lee15 fatcat:ehbed6nl6barfgs6pzwcvwxria

Spatiotemporal enabled Content-based Image Retrieval

Mariana Belgiu, Martin Sudmanns, Tiede Dirk, Andrea Baraldi, Stefan Lang
2016 International Conference on GIScience Short Paper Proceedings  
algorithms.  ...  One of the key issues of all deployment optimization algorithms is accurate estimation of the coverage of an individual sensor.  ...  We are confident that our experiments will efficiently learn the optimal parameters, and thus improve the estimation accuracy of the interpolation model, helping us to definitively establish more accurate  ... 
doi:10.21433/b311729295dw fatcat:fulw4pw3kfh5nmfzcsy3pkisvm

Demand management for planned care: a realist synthesis

Ray Pawson, Joanne Greenhalgh, Cathy Brennan
2016 Health Services and Delivery Research  
The final chapter offers practitioners some guidance on how they might 'think through' all of the interdependencies, which bring demand and capacity into equilibrium.  ...  A close analysis of the implementation of different configurations of demand management interventions in different local contexts using mixed methods would be valuable to understand the processes through  ...  Acknowledgements Contributions of authors Ray Pawson, Joanne Greenhalgh and Cathy Brennan conducted the searches, selected and reviewed the papers, conducted the synthesis and wrote the report.  ... 
doi:10.3310/hsdr04020 fatcat:pxolwdnkp5hfbgi5uopmt7sdtm

Great Expectations: Unsupervised Inference of Suspense, Surprise and Salience in Storytelling [article]

David Wilmot
2022 arXiv   pre-print
Progress is swift in improving self-supervised systems.  ...  In follow-up work, the insights could help improve computer models for tasks such as automatic story writing and assistance for writing, summarising or editing stories.  ...  When the boxing club in Rocky is mentioned, the representation could capture the grotty atmosphere of the club through similar photos of boxing but also bars, casinos and other seedier nightlife locations  ... 
arXiv:2206.09708v1 fatcat:k4oefywyxvgn5gdtedyvr5mbpi

A New Paradigm in Brain Inspired Lifelong Machine Learning for Data Intensive Environments

Balasuriya Kankanamalage Nawaratne
Thereby, considering both accuracy and computation complexity, optimal values for SF were selected.  ...  The algorithmic development is demonstrated using a series of experiments with benchmark datasets.  ... 
doi:10.26181/60c05c2637515 fatcat:f4h4ld5gyjavzmkpp4gulm44uu

Liprotides: a New Class of Protein Lipid-Complexes

Jannik N. Pedersen, Henriette Kristina S. Frislev, Jan S. Pedersen, Daniel E. Otzen
2016 Biophysical Journal  
Examples of user science enabled and improved by these developments will also be presented.  ...  Many ATSAS programs have online interfaces that can be accessed through a web-browser [5].  ...  They include (i) more advanced data reduction algorithms (ii) improved confidence assessment in the optimized model parameters and (iii) a flexible plug-in system for custom user-provided models.  ... 
doi:10.1016/j.bpj.2015.11.3085 fatcat:eqeeb47atfc4lisnurb25n55gu

Workload Modelling and Elasticity Management of Data-Intensive Systems [article]

Ali Reza Khoshkbar Foroushha, University, The Australian National, University, The Australian National
Efficiently and effectively processing large volume of data (often at high velocity) using an optimal mix of data-intensive systems (e.g., batch processing, stream processing, NoSQL) is the key step in  ...  methodology investigates and develops these techniques and tools by significantly extending the well known formal mod-els available from other disciplines of computer science including machine learning, optimization  ...  White-box and Black-box Approaches System performance modelling and prediction techniques broadly use either whitebox, black-box, or combination of both approaches.  ... 
doi:10.25911/5d514439629c1 fatcat:wqc7ysigqjenhalej3m3drodga

1 Keynote address by Nobel Laureate Phillip A. Sharp the 21st century opened with a revolution in RNA biology

Phillip A. Sharp
2015 Journal of Biomolecular Structure and Dynamics  
Long non-coding RNAs regulate the expression of genes through both cis and trans mechanisms and provide organization to the nucleus.  ...  Toward improved description of DNA backbone: Revisiting epsilon and zeta torsion force field parameters. Journal of Chemical Theory and Computation, 9, 2339-2354. V. Ananyan*, Nelli H.  ...  The structures were refined using protein preparation wizard Maestro v9.8.  ... 
doi:10.1080/07391102.2015.1032624 fatcat:w7iil7k3ize77bjkthcyi52ohy

The 49th Congress of the European Society for Surgical Research May 21-24, 2014, Budapest, Hungary: Abstracts

2014 European Surgical Research  
In Group-C, however, it was improved up to 67.4% (p<0.01).  ...  Immunohistochemistry with CD42b antibody revealed platelet aggregation in sinusoid in Group-B, which was improved by rADAMTS13 supplementation.  ...  Aim of the current study was to investigate the optimal postconditioning algorithm in a rat model of intestinal IR.  ... 
doi:10.1159/000363269 pmid:24854186 fatcat:ofafa5cf4vhknamsraqekjznpy
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