Enrique Alba
Artificial Intelligence · IEEE Transactions on Evolutionary Computation · 2002–2020
A researcher in the Science corpus: 18 papers; trusts 139 researchers and is trusted by 46 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 120 citations into it; #6,012 of 35,345 by trust here, #8,999 by citations
- Computational Theory and Mathematics — 56 citations into it; #1,877 of 12,182 by trust here, #2,015 by citations
- Computer Vision and Pattern Recognition — 33 citations into it; #12,704 of 21,575 by trust here, #19,310 by citations
- Model Architectures — 30 citations into it
- Optimization & Training — 23 citations into it
- Electrical and Electronic Engineering — 22 citations into it
- Management Science and Operations Research — 21 citations into it; #6,245 of 11,946 by trust here, #10,392 by citations
- Neural Architecture Search & AutoML — 16 citations into it
Whom Enrique Alba trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Andrés Camero
- Yoshua Bengio
- Diederik P. Kingma
- Geoffrey E. Hinton
- Kalyanmoy Deb
- Erick Cantú-Paz
- Yann LeCun
- Jamal Toutouh
- Thomas Bäck
- John H. Holland
Who trusts Enrique Alba overall
- Andrés Camero
- Jamal Toutouh
- C. Anderson‐Cook
- Gaurav Dhiman
- Kanchan Rajwar
- Gabriel Luque
- Christian Blum
- Yue-jiao Gong
- S. Kumar
- Tansel Dökeroğlu
Papers from Enrique Alba's perspective
Ordered by how strongly the researchers Enrique Alba trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- SMPSO: A new PSO-based metaheuristic for multi-objective optimization (2009) — 653 citations
- MOCell: A cellular genetic algorithm for multiobjective optimization (2009) — 309 citations
- Parallel metaheuristics: recent advances and new trends (2012) — 300 citations
- AbYSS: Adapting Scatter Search to Multiobjective Optimization (2008) — 302 citations
- The exploration/exploitation tradeoff in dynamic cellular genetic algorithms (2005) — 426 citations
- The jMetal framework for multi-objective optimization: Design and architecture (2010) — 295 citations
- BIN-CT: Urban Waste Collection based in Predicting the Container Fill Level (2018) — 44 citations
- A comparison of PSO and GA approaches for gene selection and classification of microarray data (2007) — 25 citations
- Bayesian Neural Architecture Search using A Training-Free Performance Metric (2020) — 28 citations
- A Specialized Evolutionary Strategy Using Mean Absolute Error Random Sampling to Design Recurrent Neural Networks (2019) — 16 citations
- Waste generation prediction under uncertainty in smart cities through deep neuroevolution (2019) — 14 citations
- Random error sampling-based recurrent neural network architecture optimization (2019) — 25 citations
- Smart City and information technology: A review (2019) — 360 citations
- Evolutionary Deep Learning for Car Park Occupancy Prediction in Smart Cities (2018) — 102 citations
- Low-Cost Recurrent Neural Network Expected Performance Evaluation (2018) — 20 citations
- DLOPT: Deep Learning Optimization Library (2018) — 9 citations
- Parallel Metaheuristics: A New Class of Algorithms (2005) — 631 citations
- Parallelism and evolutionary algorithms (2002) — 866 citations