Showing 1 - 18 of 18

MASTERING LARGE DATASETS WITH PYTHON: PARALLELIZE AND DISTRIBUTE YOUR PYTHON CODE.
WOLOHAN, J. T.

This result is not available to guest users.
Login for full access.

Mastering Large Datasets with Python
Wolohan, John

RV-Syn: Rational and Verifiable Mathematical Reasoning Data Synthesis based on Structured Function Library
Wang, Jiapeng ; Jiang, Jinhao ; Zhang, Zhiqiang ; et al.

A Comprehensive Framework to Capture the Arcana of Neuroimaging Analysis
Close, Thomas G. ; Ward, Phillip G. D. ; Sforazzini, Francesco ; et al.
Neuroinformatics. :1-21

面向文科学生的AI 自然语言生成实验与教学设计. (Chinese)
姚诚伟 ; 陈春晖 ; 陈 梅
Experimental Technology & Management; Apr2024, Vol. 41 Issue 4, p177-184, 8p

PYTHON AND R: A SIDE-BY- SIDE EVALUATION FOR ANALYTICS EXCELLENCE
Rekha Raichal
ShodhKosh: Journal of Visual and Performing Arts. 5

PlotGen: Multi-Agent LLM-based Scientific Data Visualization via Multimodal Feedback
Goswami, Kanika ; Mathur, Puneet ; Rossi, Ryan ; et al.

Computación Evolutiva Descentralizada de Modelo Híbrido usando Blockchain y Prueba de Trabajo de Optimización
Consultor de tesis ; Pabón Burbano, María Constanza ; Bastidas Caicedo, Harvey Demian ; et al.
K. Stanley, "Evolving Neural Networks through Augmenting Topologies," Evolutionary Computation, vol. 10 , no. 2, pp. 99-127 , 2002.; L. Wu, "Magnetic Resonance Brain Image Classification by an Improved Artificial Bee Colony Algorithm," Progress in Electromagnetics Research, vol. 116, pp. 65-79 , 2011.; J. Kennedy and R. Eberhart, "Particle Swarm Optimization," in Proceedings of IEEE International Conference on Neural Networks, 1995.; M. Wa, "Genetic Algorithm and its application to Big Data Analysis," International Journal of Scientific & Engineering Research,, vol. 5, no. 1, 2014.; P. Verbancsics, "Classifying Maritime Vessels from Satellite Imagery with HyperNEAT," in Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference - GECCO Companion, New York, USA, 2015.; Y.-J. Gong, "Distributed evolutionary algorithms and their models: A survey of the state-of-the-art.," Applied Soft Computing, 2015.; J. Lienig, "A parallel genetic algorithm for performance-driven VLSI routing," IEEE Trans. Evol. Comput, vol. 1, no. 1, pp. 29-39, 1997.; H. Piereval, "Distributed evolutionary algorithms for simulation optimization," IEEE Trans Sys. Man. Cybern. , vol. 30, no. 1, pp. 15-24, 2000.; K.C.Tan, "Automating the drug-sheduling of cancer chemotherapy via evolutionary computation," Artif.Intellig.Med., vol. 25, no. 2, pp. 169-185, 2002.; J. Creput, "Automatic mesh generation for mobile network dimensioning using evolutionary approach," Evol.Comput, vol. 9, no. 1, pp. 18-30, 2005.; J.Liu, "An evolutionary autonomous agents approach to image feature extraction.," IEEE Trans. Evol. Comput., vol. 1, no. 2, pp. 141-158, 1997.; M. Epitropakis, "Hardware-friendly higher-order neural network training using distributed evolutionary algorithms.," Appl. Soft. comput. , vol. 10, no. 2, pp. 398-408, 2010.; L. Kattan, "Distributed evolutionary estimation of of dynamic traffic origin/destination," in 13th IEEE Conference on Intelligent Transport Systems, 2010.; J. Noyima, "Ensemble classifier design by parallel implementation of genetic fuzzy rule selection for large datasets.," in IEEE Congress on Evolutionary Computation, 2010.; F. Rainville, "DEAP: A Python Framework for Evolutionary Algorithms," in GECCO, 2012.; M. Linder, "Grid computing in Matlab for solving evolutionary algorithms," in Technical Computing Bratislava, Bratislava, 2012.; J. Kennedy and R. Eberhart, "Particle Swarm Optimization," in Proceedings of IEEE International Conference on Neural Networks. , 1995.; D. D. Karaboga, "An Idea Based On Honey Bee Swarm for Numerical Optimization," Erciyes University, 2005.; M. Dorigo, "Distributed Optimization by Ant Colonies," in Première conférence européenne sur la vie artificielle, Paris, France, 1991.; C. Huang, "A hybrid stock selection model using genetic algorithms and support vector regression," Applied Soft Computing, vol. 12, p. 807–81, 2012.; E. Levy, "Genetic algorithms and deep learning for automatic painter classification," in conference on Genetic and evolutionary computation - GECCO ’14 , New York, New York, USA, 2014.; E. Levy, "Genetic algorithms and deep learning for automatic painter classification," in Proceedings of the 2014 conference on Genetic and evolutionary computation - GECCO ’14 , New York, New York, USA, 2014.; S. Whiteson, "Evolutionary Function Approximation for Reinforcement Learning," Journal of Machine Learning Research, vol. 8, pp. 877-917, 2006.; R. B. Greve, "Evolving Neural Turing Machines for Reward-based Learning," in Genetic and Evolutionary Computation Conference (GECCO), Denver, Colorado, USA, 2016.; A. Santoro, "One-shot Learning with Memory-Augmented Neural Networks," Cornell University , Ithaca, NY, USA, 2016.; D. Izzo, "The generalized isalnd model," Studies in Computational Intelligence, vol. 415, pp. 151-169, 2012.; G. Folino, "P-CAGE: An Environment for Evolutionary Computation in Peer-to-Peer Systems," in European Conference on Genetic Programming, Berlin, 2006.; A. L. Ian Scriven, "Decentralised distributed multiple objective particle swarm optimisation using peer to peer networks," in IEEE World Congress on Evolutionary Computation, 2008. CEC 2008, 2008.; A. L. C. Fernando Silva, "odNEAT: An Algorithm for Decentralised Online Evolution of Robotic Controllers," Evolutionary Computation , vol. 23, no. 3, pp. 421-449, 2015.; D. Jakobović, "ECF - Evolutionary Computation Framework," University of Zagreb,; M. A. García-Sánchez P., "A Methodology to Develop Service Oriented Evolutionary Algorithms," Intelligent Distributed Computing VIII, vol. 570, 2015.; S. Cahon, "ParadisEO: A Framework for the Reusable Design of Parallel and Distributed Metaheuristics," Journal of Heuristics, vol. 10, no. 3, pp. 357-380, 2004.; D. R. White, "Software review: the ECJ toolkit," Genetic Programming and Evolvable Machines, vol. 13, no. 1, pp. 65-67, 2011.; M. G. Arenas, "A Framework for Distributed Evolutionary Algorithms," Lecture Notes on Computer Science, vol. 2439, pp. 665-675, 2002.; J. L. J. Laredo, "Resilience to churn of a peer-to-peer evolutionary algorithm," International Journal of High Performance Systems Architecture, vol. 1, no. 4, pp. 260-268, 2008.; C. Rohrs, "Query Routing for the Gnutella Network," Lime Wire LLC, 2002.; R. Fielding, "Chapter 5: Representational State Transfer (REST)," in Architectural Styles and the Design of Network-based Software Architectures, Irvine, Ca, University of California, 2000.; P. C. R. K. Len Bass, Software Architecture in Practice - Second Edition, Addison Wesley, 2003.; S. Nakamoto, "Bitcoin: A Peer-to-Peer Electronic Cash Syste," bitcoin.org, vol. Retrieved 28 April 2016.; H. C. M. Kalodner, "An empirical study of Namecoin and lessons for decentralized namespace design," in Workshop on the oconomics of information security, Delft, The Netherlands, 2015.; D. Carboni, "Feedback based Reputation on top of the Bitcoin Blockchain," Retrieved from; E. Foundation, "Ethereum's white paper," Ethereum Foundation, 2014.; G. N. O. Zyskind, "Decentralizing Privacy: Using Blockchain to Protect Personal Data," IEEE Security and Privacy Workshops , p. 180–184, 2015.; S. Nakamoto, "Bitcoin: A Peer-to-Peer Electronic Cash System," in Web. bitcoin.org. Retrieved 28 April 2014, 2008.; S. King, "Primecoin: Cryptocurrency with Prime Number Proof-of-Work," 2013 .; A. R. Marshall Ball, "Proofs of Useful Work," Cryptology ePrint Archive, 2017.; R. A. G. Barto, Reinforcement Learning: An Introduction, Cambridge, Massachusetts: The MIT Press, 2005.; M. S. J. Moody, "Learning to trade via direct reinforcement," IEEE Transactions on Neural Networks, vol. 12, no. 4,, 2001; C. WATKINS, "Q,-Learning," Machine Learning, vol. 8, 1992.; R. M. Kenneth O. Stanley, "Efficient Reinforcement Learning through Evolving Neural Network Topologies," in Genetic and Evolutionary Computation Conference , San Francisco, CA, 2002.; C. Igel, "Neuroevolution for reinforcement learning using evolution strategies," in Congress on Evolutionary Computation, 2003.; V. Heidrich-Meisner, "Neuroevolution strategies for episodic reinforcement learning," Journal of Algorithms, vol. 64, no. 4, pp. 152-168, 2009.; D. Lessin, "Open-ended behavioral complexity for evolved virtual creatures," in 15th annual conference on Genetic and evolutionary computation, Amsterdam, The Netherlands, 2013.; G. B. a. V. Cheung, "OpenAI Gym," Arxiv, vol. arXiv:1606.01540, 2016.; N. G. L. Iker Zamora, "Extending the OpenAI Gym for robotics: a toolkit for reinforcement learning using ROS and Gazebo," Whitepaper, 2016.; A. H. David Silver, "Mastering the game of Go with deep neural networks and tree 62 search," Nature, vol. 529, no. 7587, pp. 484-489, 2016.; K. K. Volodymyr Mnih, "Human-level control through deep reinforcement learning," Nature, vol. 518, no. 7540, pp. 529-533, 2015.; U. B. o. E. Analysis, "U.S. INTERNATIONAL TRADE IN GOODS AND SERVICES - December 2013," U.S. Department of Commerce, Washington, DC 20230, 2013.; E. Department, "Triennial Central Bank Survey of foreign exchange and OTC derivatives markets in 2016," Bank For International Settlements, Basel, Switzerland,; Investopedia, "Forex Broker Definition,"; Investopedia, "Margin Call Definition,"; Investopedia, "What is a Spread,"; Investopedia, "Leverage Definition,"; A. P. CHABOUD, "Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market," Journal of the American Finance Association, vol. 69, no. 5, p. 2045–2084 , 201.; M. A. H. Dempster, "An automated FX trading system using adaptive reinforcement learning," Expert Systems with Applications, vol. 30, no. 3, pp. 543-552, 2006.; HistData.com, "Free Forex Historical Data Repository,"; R. T. Fielding, "Chapter 5: Representational State Transfer (REST)," in Architectural Styles and the Design of Network-based Software Architectures, Irvine, University of California, 2000.; H. W. Group, " SOAP: Simple Object Access Protocol," [Online]. Available:; e. a. Don Box, "Simple Object Access Protocol (SOAP) 1.1," W3C, 8 May 2000. [Online]. Available:; J.-R. W. Group, "JSON-RPC 2.0 Specification," JSON-RPC Working Group, 04 01 2013. [Online]. Available:; R. Mikkulainen and J. e. a. Liang, "Evolving Deep Neural Netwokrs," eprint arXiv:1703.00548, 2017.; Reponame:Vitela: Repositorio Institucional PUJ; Instname:Pontificia Universidad Javeriana Cali

Advanced Python Programming
Lanaro, Dr. Gabriele ; Nguyen, Quan ; Kasampalis, Sakis ; et al.

Advanced Python Programming
Nguyen, Quan ; Nguyen, Quan ; Kasampalis, Sakis ; et al.

Advanced Machine Learning with Python
Hearty, John ; Hearty, John ; Hearty, John ; et al.

Learning Google BigQuery
Haridass, Thirukkumaran ; Brown, Eric ; Haridass, Thirukkumaran ; et al.

Mastering Apache Cassandra 3.x
Aaron Ploetz ; Tejaswi Malepati Nishant Neeraj ; Aaron Ploetz ; et al.
2018

Mastering Apache Cassandra 3.x
Aaron Ploetz ; Tejaswi Malepati Nishant Neeraj ; Aaron Ploetz ; et al.
2018

Mastering Apache Cassandra 3.x
Aaron Ploetz ; Tejaswi Malepati Nishant Neeraj ; Aaron Ploetz ; et al.
2018

Mastering Apache Cassandra 3.x
Aaron Ploetz ; Tejaswi Malepati Nishant Neeraj ; Aaron Ploetz ; et al.
2018

Identifying resource-rational heuristics for risky choice.
Krueger, Paul M. ; Callaway, Frederick ; Gul, Sayan ; et al.
Psychol Rev