| Large-scale wearable data reveal digital phenotypes for daily-life stress detection E Smets, E Rios Velazquez, G Schiavone, I Chakroun, E D’Hondt, ... NPJ digital medicine 1 (1), 67, 2018 | 142 | 2018 |
| Reducing thread divergence in a GPU‐accelerated branch‐and‐bound algorithm I Chakroun, M Mezmaz, N Melab, A Bendjoudi Concurrency and Computation: Practice and Experience 25 (8), 1121-1136, 2013 | 61 | 2013 |
| Combining multi-core and GPU computing for solving combinatorial optimization problems I Chakroun, N Melab, M Mezmaz, D Tuyttens Journal of Parallel and Distributed Computing 73 (12), 1563-1577, 2013 | 57 | 2013 |
| A GPU-accelerated branch-and-bound algorithm for the flow-shop scheduling problem N Melab, I Chakroun, M Mezmaz, D Tuyttens 2012 IEEE International Conference on Cluster Computing, 10-17, 2012 | 45 | 2012 |
| Distributed Bayesian probabilistic matrix factorization T Vander Aa, I Chakroun, T Haber Procedia Computer Science 108, 1030-1039, 2017 | 31 | 2017 |
| SW-SGD: the sliding window stochastic gradient descent algorithm I Chakroun, T Haber, TJ Ashby Procedia Computer Science 108, 2318-2322, 2017 | 26 | 2017 |
| An adaptative multi-GPU based branch-and-bound. a case study: the flow-shop scheduling problem I Chakroun, N Melab 2012 IEEE 14th International Conference on High Performance Computing and …, 2012 | 22 | 2012 |
| Operator-level gpu-accelerated branch and bound algorithms I Chakroun, N Melab Procedia Computer Science 18, 280-289, 2013 | 19 | 2013 |
| Graphics processing unit‐accelerated bounding for branch‐and‐bound applied to a permutation problem using data access optimization N Melab, I Chakroun, A Bendjoudi Concurrency and Computation: Practice and Experience 26 (16), 2667-2683, 2014 | 16 | 2014 |
| Identifying and evaluating barriers for the implementation of machine learning in the intensive care unit E D’Hondt, TJ Ashby, I Chakroun, T Koninckx, R Wuyts Communications Medicine 2 (1), 162, 2022 | 13 | 2022 |
| Towards a heterogeneous and adaptive parallel Branch-and-Bound algorithm I Chakroun, N Melab Journal of Computer and System Sciences 81 (1), 72-84, 2015 | 13 | 2015 |
| Exashark: A scalable hybrid array kit for exascale simulation I Chakroun, T Vander Aa, B De Fraine, T Haber, R Wuyts, W Demeuter Proceedings of the Symposium on High Performance Computing, 41-48, 2015 | 10 | 2015 |
| Parallel heterogeneous Branch and Bound algorithms for multi-core and multi-GPU environments I Chakroun Université des Sciences et Technologie de Lille-Lille I, 2013 | 10 | 2013 |
| Reducing Thread Divergence in GPU-based B&B Applied to the Flow-shop problem I Chakroun, A Bendjoudi, N Melab Parallel Processing and Applied Mathematics: 9th International Conference …, 2012 | 9 | 2012 |
| Large-scale wearable data reveal digital phenotypes for daily-life stress detection. Npj Digital Medicine, 1 (1), 67 E Smets, E Rios Velazquez, G Schiavone, I Chakroun, E D’Hondt, ... | 7 | 2018 |
| Synergy between parallel computing, optimization and simulation N Melab, J Gmys, P Korosec, I Chakroun Journal of computational science 44, 101168, 2020 | 5 | 2020 |
| Large-scale wearable data reveal digital phenotypes for daily-life stress detection, npj Digital Medicine E Smets, ER Velazquez, G Schiavone, I Chakroun, E D'Hondt, ... Article, 2018 | 5 | 2018 |
| Using Unsupervised Machine Learning for Plasma Etching Endpoint Detection. I Chakroun, TJ Ashby, S Das, S Halder, R Wuyts, W Verachtert ICPRAM, 273-279, 2020 | 4 | 2020 |
| SMURFF: a High-Performance Framework for Matrix Factorization TV Aa, I Chakroun, TJ Ashby, J Simm, A Arany, Y Moreau, TL Van, ... arXiv preprint arXiv:1904.02514, 2019 | 4 | 2019 |
| Guidelines for enhancing data locality in selected machine learning algorithms I Chakroun, TV Aa, TJ Ashby Intelligent Data Analysis 23 (5), 1003-1020, 2019 | 4 | 2019 |
