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Mikel Luján
- > Home > Persons > Mikel Luján
Publications
- 2023
- [i20]Danny Wood, Tingting Mu, Andrew M. Webb, Henry W. J. Reeve, Mikel Luján, Gavin Brown:
A Unified Theory of Diversity in Ensemble Learning. CoRR abs/2301.03962 (2023) - [i19]Konstantinos Iordanou, Timothy Atkinson, Emre Ozer, Jedrzej Kufel, John Biggs, Gavin Brown, Mikel Luján:
Tiny Classifier Circuits: Evolving Accelerators for Tabular Data. CoRR abs/2303.00031 (2023) - 2022
- [c117]Edoardo Manino, Danilo S. Carvalho, Yi Dong, Julia Rozanova, Xidan Song, Mustafa A. Mustafa, André Freitas, Gavin Brown, Mikel Luján, Xiaowei Huang, Lucas C. Cordeiro:
EnnCore: End-to-End Conceptual Guarding of Neural Architectures. SafeAI@AAAI 2022 - 2020
- [c108]Andrew M. Webb, Charles Reynolds, Wenlin Chen, Henry W. J. Reeve, Dan-Andrei Iliescu, Mikel Luján, Gavin Brown:
To Ensemble or Not Ensemble: When Does End-to-End Training Fail? ECML/PKDD (3) 2020: 109-123 - 2019
- [c89]Andrew M. Webb, Gavin Brown, Mikel Luján:
ORB-SLAM-CNN: Lessons in Adding Semantic Map Construction to Feature-Based SLAM. TAROS (1) 2019: 221-235 - [i13]Andrew M. Webb, Charles Reynolds, Dan-Andrei Iliescu, Henry W. J. Reeve, Mikel Luján, Gavin Brown:
Joint Training of Neural Network Ensembles. CoRR abs/1902.04422 (2019) - 2017
- [j27]Konstantinos Sechidis, Matthew Sperrin, Emily Petherick, Mikel Luján, Gavin Brown:
Dealing with under-reported variables: An information theoretic solution. Int. J. Approx. Reason. 85: 159-177 (2017) - [c81]James Clarkson, Christos Kotselidis, Gavin Brown, Mikel Luján:
Boosting Java Performance Using GPGPUs. ARCS 2017: 59-70 - 2016
- [j18]Paraskevas Yiapanis, Gavin Brown, Mikel Luján:
Compiler-Driven Software Speculation for Thread-Level Parallelism. ACM Trans. Program. Lang. Syst. 38(2): 5:1-5:45 (2016) - 2015
- [c59]Anthony Kleerekoper, Michael Pappas, Adam Craig Pocock, Gavin Brown, Mikel Luján:
A scalable implementation of information theoretic feature selection for high dimensional data. IEEE BigData 2015: 339-346 - [i4]James Clarkson, Christos Kotselidis, Gavin Brown, Mikel Luján:
Boosting Java Performance using GPGPUs. CoRR abs/1508.06791 (2015) - 2013
- [j11]Paraskevas Yiapanis, Demian Rosas-Ham, Gavin Brown, Mikel Luján:
Optimizing software runtime systems for speculative parallelization. ACM Trans. Archit. Code Optim. 9(4): 39:1-39:27 (2013) - [c47]Anthony Kleerekoper, Mikel Luján, Gavin Brown:
Exploring sketches for probability estimation with sublinear memory. IEEE BigData 2013: 79-86 - 2012
- [j9]Gavin Brown, Adam Craig Pocock, Ming-Jie Zhao, Mikel Luján:
Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection. J. Mach. Learn. Res. 13: 27-66 (2012) - [c36]Adam Craig Pocock, Mikel Luján, Gavin Brown:
Informative Priors for Markov Blanket Discovery. AISTATS 2012: 905-913 - 2011
- [c35]Jeremy Singer, George Kovoor, Gavin Brown, Mikel Luján:
Garbage collection auto-tuning for Java mapreduce on multi-cores. ISMM 2011: 109-118 - 2010
- [c30]Nikolas Ioannou, Jeremy Singer, Salman Khan, Polychronis Xekalakis, Paraskevas Yiapanis, Adam Craig Pocock, Gavin Brown, Mikel Luján, Ian Watson, Marcelo Cintra:
Toward a more accurate understanding of the limits of the TLS execution paradigm. IISWC 2010: 1-12 - [c27]Jeremy Singer, Richard E. Jones, Gavin Brown, Mikel Luján:
The economics of garbage collection. ISMM 2010: 103-112 - [c26]Adam Craig Pocock, Paraskevas Yiapanis, Jeremy Singer, Mikel Luján, Gavin Brown:
Online Non-stationary Boosting. MCS 2010: 205-214 - 2009
- [c20]Jeremy Singer, Gavin Brown, Mikel Luján, Adam Craig Pocock, Paraskevas Yiapanis:
Fundamental Nano-Patterns to Characterize and Classify Java Methods. LDTA 2009: 191-204 - 2007
- [c7]Jeremy Singer, Gavin Brown, Mikel Luján, Ian Watson:
Towards intelligent analysis techniques for object pretenuring. PPPJ 2007: 203-208
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