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2020 – today
- 2024
[j43]Alex Beeson, Giovanni Montana
:
Balancing policy constraint and ensemble size in uncertainty-based offline reinforcement learning. Mach. Learn. 113(1): 443-488 (2024)- [j42]Charles A. Hepburn, Giovanni Montana:
Model-based trajectory stitching for improved behavioural cloning and its applications. Mach. Learn. 113(2): 647-674 (2024) - [j41]Mianchu Wang, Yue Jin, Giovanni Montana:
Goal-conditioned offline reinforcement learning through state space partitioning. Mach. Learn. 113(5): 2435-2465 (2024) - [j40]Mianchu Wang, Rui Yang, Xi Chen, Hao Sun, Meng Fang, Giovanni Montana:
GOPlan: Goal-conditioned Offline Reinforcement Learning by Planning with Learned Models. Trans. Mach. Learn. Res. 2024 (2024) - [c35]Sharlin Utke, Jeremie Houssineau, Giovanni Montana:
Embracing Relational Reasoning in Multi-Agent Actor-Critic. AAMAS 2024: 2525-2527 - [c34]Yuanyi Zhu, Maria Liakata, Giovanni Montana:
A Multi-Task Transformer Model for Fine-grained Labelling of Chest X-Ray Reports. LREC/COLING 2024: 862-875 - [c33]David Ireland, Giovanni Montana:
REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes. ICLR 2024 - [i43]David Ireland, Giovanni Montana:
REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes. CoRR abs/2401.08850 (2024) - [i42]Charles A. Hepburn, Yue Jin, Giovanni Montana:
State-Constrained Offline Reinforcement Learning. CoRR abs/2405.14374 (2024) - 2023
- [j39]Emanuele Pesce, Giovanni Montana:
Learning multi-agent coordination through connectivity-driven communication. Mach. Learn. 112(2): 483-514 (2023) - [j38]Adam R. Brentnall, Emma C. Atakpa, Harry Hill, Ruggiero Santeramo, Celeste Damiani, Jack Cuzick, Giovanni Montana, Stephen W. Duffy:
An optimization framework to guide the choice of thresholds for risk-based cancer screening. npj Digit. Medicine 6 (2023) - [j37]Mingqi Gao, Jungong Han, Feng Zheng, James J. Q. Yu, Giovanni Montana:
Video Object Segmentation using Point-based Memory Network. Pattern Recognit. 134: 109073 (2023) - [j36]Mingqi Gao, Jinyu Yang, Jungong Han, Ke Lu, Feng Zheng, Giovanni Montana:
Decoupling Multimodal Transformers for Referring Video Object Segmentation. IEEE Trans. Circuits Syst. Video Technol. 33(9): 4518-4528 (2023) - [j35]Nick Byrne, James R. Clough, Israel Valverde, Giovanni Montana, Andrew P. King:
A Persistent Homology-Based Topological Loss for CNN-Based Multiclass Segmentation of CMR. IEEE Trans. Medical Imaging 42(1): 3-14 (2023) - [c32]George Watkins, Giovanni Montana, Jürgen Branke:
Generating a Graph Colouring Heuristic with Deep Q-Learning and Graph Neural Networks. LION 2023: 491-505 - [i41]Mianchu Wang, Yue Jin, Giovanni Montana:
Goal-conditioned Offline Reinforcement Learning through State Space Partitioning. CoRR abs/2303.09367 (2023) - [i40]Alex Beeson, Giovanni Montana:
Balancing policy constraint and ensemble size in uncertainty-based offline reinforcement learning. CoRR abs/2303.14716 (2023) - [i39]George Watkins, Giovanni Montana, Jürgen Branke:
Generating a Graph Colouring Heuristic with Deep Q-Learning and Graph Neural Networks. CoRR abs/2304.04051 (2023) - 2022
- [j34]Ozsel Kilinc, Giovanni Montana:
Reinforcement learning for robotic manipulation using simulated locomotion demonstrations. Mach. Learn. 111(2): 465-486 (2022) - [c31]David Ireland, Giovanni Montana:
LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation. ICML 2022: 9622-9638 - [c30]Matthew MacPherson, Keerthini Muthuswamy, Ashik Amlani, Charles Hutchinson, Vicky Goh, Giovanni Montana:
Assessing the Performance of Automated Prediction and Ranking of Patient Age from Chest X-rays Against Clinicians. MICCAI (8) 2022: 255-265 - [i38]David Ireland, Giovanni Montana:
LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation. CoRR abs/2205.10106 (2022) - [i37]Matthew MacPherson, Keerthini Muthuswamy, Ashik Amlani, Charles Hutchinson, Vicky Goh, Giovanni Montana:
Assessing the Performance of Automated Prediction and Ranking of Patient Age from Chest X-rays Against Clinicians. CoRR abs/2207.01302 (2022) - [i36]Charles A. Hepburn, Giovanni Montana:
Model-based Trajectory Stitching for Improved Offline Reinforcement Learning. CoRR abs/2211.11603 (2022) - [i35]Alex Beeson, Giovanni Montana:
Improving TD3-BC: Relaxed Policy Constraint for Offline Learning and Stable Online Fine-Tuning. CoRR abs/2211.11802 (2022) - [i34]Charles A. Hepburn, Giovanni Montana:
Model-based trajectory stitching for improved behavioural cloning and its applications. CoRR abs/2212.04280 (2022) - 2021
- [c29]Henry Charlesworth, Giovanni Montana:
Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement Learning. ICML 2021: 1496-1506 - [i33]Aydan Gasimova, Giovanni Montana, Daniel Rueckert:
Automated Knee X-ray Report Generation. CoRR abs/2105.10702 (2021) - [i32]Nick Byrne, James R. Clough, Isra Valverde, Giovanni Montana, Andrew P. King:
A persistent homology-based topological loss for CNN-based multi-class segmentation of CMR. CoRR abs/2107.12689 (2021) - 2020
- [j33]Emanuele Pesce, Giovanni Montana:
Improving coordination in small-scale multi-agent deep reinforcement learning through memory-driven communication. Mach. Learn. 109(9-10): 1727-1747 (2020) - [j32]Nicoló Savioli, Enrico Grisan, Silvia Visentin, Erich Cosmi, Giovanni Montana, Pablo Lamata:
Real-time diameter of the fetal aorta from ultrasound. Neural Comput. Appl. 32(11): 6735-6744 (2020) - [c28]Nick Byrne, James R. Clough, Giovanni Montana, Andrew P. King:
A Persistent Homology-Based Topological Loss Function for Multi-class CNN Segmentation of Cardiac MRI. M&Ms and EMIDEC/STACOM@MICCAI 2020: 3-13 - [c27]Ksenia Sokolova, Gareth J. Barker, Giovanni Montana:
Convolutional neural-network-based ordinal regression for brain age prediction from MRI scans. Medical Imaging: Image Processing 2020: 113132B - [c26]Henry Charlesworth, Giovanni Montana:
PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals. NeurIPS 2020 - [i31]Emanuele Pesce, Giovanni Montana:
Connectivity-driven Communication in Multi-agent Reinforcement Learning through Diffusion Processes on Graphs. CoRR abs/2002.05233 (2020) - [i30]Saad Mohamad, Giovanni Montana:
Adaptive Experience Selection for Policy Gradient. CoRR abs/2002.06946 (2020) - [i29]Henry Charlesworth, Giovanni Montana:
PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals. CoRR abs/2006.00900 (2020) - [i28]Ozsel Kilinc, Giovanni Montana:
Follow the Object: Curriculum Learning for Manipulation Tasks with Imagined Goals. CoRR abs/2008.02066 (2020) - [i27]Nick Byrne, James R. Clough, Giovanni Montana, Andrew P. King:
A persistent homology-based topological loss function for multi-class CNN segmentation of cardiac MRI. CoRR abs/2008.09585 (2020) - [i26]Henry Charlesworth, Giovanni Montana:
Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement Learning. CoRR abs/2009.05104 (2020)
2010 – 2019
- 2019
- [j31]Emanuele Pesce, Samuel Withey, Petros-Pavlos Ypsilantis, Robert Bakewell, Vicky Goh, Giovanni Montana:
Learning to detect chest radiographs containing pulmonary lesions using visual attention networks. Medical Image Anal. 53: 26-38 (2019) - [c25]Briti Gangopadhyay, Siddartha Khastgir, Sumanta Dey, Pallab Dasgupta, Giovanni Montana, Paul A. Jennings:
Identification of Test Cases for Automated Driving Systems Using Bayesian Optimization. ITSC 2019: 1961-1967 - [c24]Nick Byrne, James R. Clough, Isra Valverde, Giovanni Montana, Andrew P. King:
Topology-Preserving Augmentation for CNN-Based Segmentation of Congenital Heart Defects from 3D Paediatric CMR. SUSI/PIPPI@MICCAI 2019: 181-188 - [i25]Emanuele Pesce, Giovanni Montana:
Improving Coordination in Multi-Agent Deep Reinforcement Learning through Memory-driven Communication. CoRR abs/1901.03887 (2019) - [i24]Zhana Kuncheva, Giovanni Montana:
Spectral Multi-scale Community Detection in Temporal Networks with an Application. CoRR abs/1901.10521 (2019) - [i23]Yang Hu, Giovanni Montana:
Skill Transfer in Deep Reinforcement Learning under Morphological Heterogeneity. CoRR abs/1908.05265 (2019) - [i22]Nick Byrne, James R. Clough, Isra Valverde, Giovanni Montana, Andrew P. King:
Topology-preserving augmentation for CNN-based segmentation of congenital heart defects from 3D paediatric CMR. CoRR abs/1908.08870 (2019) - [i21]Ozsel Kilinc, Yang Hu, Giovanni Montana:
Reinforcement Learning for Robotic Manipulation using Simulated Locomotion Demonstrations. CoRR abs/1910.07294 (2019) - 2018
- [j30]Dimosthenis Tsagkrasoulis, Giovanni Montana:
Random forest regression for manifold-valued responses. Pattern Recognit. Lett. 101: 6-13 (2018) - [j29]Ricardo Pio Monti, Christoforos Anagnostopoulos, Giovanni Montana:
Adaptive regularization for Lasso models in the context of nonstationary data streams. Stat. Anal. Data Min. 11(5): 237-247 (2018) - [c23]Nicoló Savioli, Silvia Visentin, Erich Cosmi, Enrico Grisan, Pablo Lamata, Giovanni Montana:
Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound. ICANN (2) 2018: 148-157 - [c22]Nicoló Savioli, Giovanni Montana, Pablo Lamata:
V-FCNN: Volumetric Fully Convolution Neural Network for Automatic Atrial Segmentation. STACOM@MICCAI 2018: 273-281 - [c21]Ruggiero Santeramo, Samuel Withey, Giovanni Montana:
Longitudinal Detection of Radiological Abnormalities with Time-Modulated LSTM. DLMIA/ML-CDS@MICCAI 2018: 326-333 - [c20]Mauro Annarumma, Giovanni Montana:
Deep metric learning for multi-labelled radiographs. SAC 2018: 34-37 - [c19]Nicoló Savioli, Miguel Silva Vieira, Pablo Lamata, Giovanni Montana:
Automated Segmentation on the Entire Cardiac Cycle Using a Deep Learning Work - Flow. SNAMS 2018: 153-158 - [i20]Nicoló Savioli, Silvia Visentin, Erich Cosmi, Enrico Grisan, Pablo Lamata, Giovanni Montana:
Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound. CoRR abs/1807.04056 (2018) - [i19]Ruggiero Santeramo, Samuel Withey, Giovanni Montana:
Longitudinal detection of radiological abnormalities with time-modulated LSTM. CoRR abs/1807.06144 (2018) - [i18]Nicoló Savioli, Giovanni Montana, Pablo Lamata:
V-FCNN: Volumetric Fully Convolution Neural Network For Automatic Atrial Segmentation. CoRR abs/1808.01944 (2018) - [i17]Nicoló Savioli, Miguel S. Vieira, Pablo Lamata, Giovanni Montana:
Automated segmentation on the entire cardiac cycle using a deep learning work-flow. CoRR abs/1809.01015 (2018) - [i16]Nicoló Savioli, Miguel Silva Vieira, Pablo Lamata, Giovanni Montana:
A Generative Adversarial Model for Right Ventricle Segmentation. CoRR abs/1810.03969 (2018) - [i15]Ozsel Kilinc, Giovanni Montana:
Multi-agent Deep Reinforcement Learning with Extremely Noisy Observations. CoRR abs/1812.00922 (2018) - 2017
- [j28]Ricardo Pio Monti, Romy Lorenz, Peter Hellyer, Robert Leech, Christoforos Anagnostopoulos, Giovanni Montana:
Decoding Time-Varying Functional Connectivity Networks via Linear Graph Embedding Methods. Frontiers Comput. Neurosci. 11: 14 (2017) - [j27]James H. Cole, Rudra P. K. Poudel, Dimosthenis Tsagkrasoulis, Matthan W. A. Caan, Claire J. Steves, Tim D. Spector, Giovanni Montana:
Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker. NeuroImage 163: 115-124 (2017) - [c18]Zhana Kuncheva, Giovanni Montana:
Multi-scale Community Detection in Temporal Networks Using Spectral Graph Wavelets. PAP@PKDD/ECML 2017: 139-154 - [c17]Zhana Kuncheva, Michelle L. Krishnan, Giovanni Montana:
Exploring Brain Transcriptomic Patterns: A Topological Analysis Using Spatial Expression Networks. PSB 2017: 70-81 - [i14]Petros-Pavlos Ypsilantis, Giovanni Montana:
Learning what to look in chest X-rays with a recurrent visual attention model. CoRR abs/1701.06452 (2017) - [i13]Zhana Kuncheva, Giovanni Montana:
Multi-scale Community Detection in Temporal Networks Using Spectral Graph Wavelets. CoRR abs/1708.04060 (2017) - [i12]Emanuele Pesce, Petros-Pavlos Ypsilantis, Samuel Withey, Robert Bakewell, Vicky Goh, Giovanni Montana:
Learning to detect chest radiographs containing lung nodules using visual attention networks. CoRR abs/1712.00996 (2017) - [i11]Mauro Annarumma, Giovanni Montana:
Deep metric learning for multi-labelled radiographs. CoRR abs/1712.07682 (2017) - 2016
- [j26]Michael W. Berry, Jung Jin Lee, Giovanni Montana, Stefan Van Aelst, Ruben H. Zamar:
Special Issue on Advances in Data Mining and Robust Statistics. Comput. Stat. Data Anal. 93: 388-389 (2016) - [j25]Romy Lorenz, Ricardo Pio Monti, Inês R. Violante, Christoforos Anagnostopoulos, Aldo A. Faisal, Giovanni Montana, Robert Leech:
The Automatic Neuroscientist: A framework for optimizing experimental design with closed-loop real-time fMRI. NeuroImage 129: 320-334 (2016) - [j24]Ai Wern Chung, Markus Schirmer, Michelle L. Krishnan, Gareth Ball, Paul Aljabar, A. David Edwards, Giovanni Montana:
Characterising brain network topologies: A dynamic analysis approach using heat kernels. NeuroImage 141: 490-501 (2016) - [c16]Savelie Cornegruta, Robert Bakewell, Samuel Withey, Giovanni Montana:
Modelling Radiological Language with Bidirectional Long Short-Term Memory Networks. Louhi@EMNLP 2016: 17-27 - [c15]Rudra P. K. Poudel, Pablo Lamata, Giovanni Montana:
Recurrent Fully Convolutional Neural Networks for Multi-slice MRI Cardiac Segmentation. RAMBO+HVSMR@MICCAI 2016: 83-94 - [c14]Ai Wern Chung, Emanuele Pesce, Ricardo Pio Monti, Giovanni Montana:
Classifying HCP task-fMRI networks using heat kernels. PRNI 2016: 1-4 - [c13]Romy Lorenz, Ricardo Pio Monti, Adam Hampshire, Yury Koush, Christoforos Anagnostopoulos, Aldo A. Faisal, David J. Sharp, Giovanni Montana, Robert Leech, Inês R. Violante:
Towards tailoring non-invasive brain stimulation using real-time fMRI and Bayesian optimization. PRNI 2016: 1-4 - [c12]Ricardo Pio Monti, Romy Lorenz, Robert Leech, Christoforos Anagnostopoulos, Giovanni Montana:
Text-mining the neurosynth corpus using deep boltzmann machines. PRNI 2016: 1-4 - [c11]Zi Wang, Vyacheslav Karolis, Chiara Nosarti, Giovanni Montana:
Studying the brain from adolescence to adulthood through sparse multi-view matrix factorisations. PRNI 2016: 1-4 - [i10]Ricardo Pio Monti, Romy Lorenz, Robert Leech, Christoforos Anagnostopoulos, Giovanni Montana:
Text-mining the NeuroSynth corpus using Deep Boltzmann Machines. CoRR abs/1605.00223 (2016) - [i9]Zi Wang, Vyacheslav Karolis, Chiara Nosarti, Giovanni Montana:
Studying the brain from adolescence to adulthood through sparse multi-view matrix factorisations. CoRR abs/1605.02560 (2016) - [i8]Rudra P. K. Poudel, Pablo Lamata, Giovanni Montana:
Recurrent Fully Convolutional Neural Networks for Multi-slice MRI Cardiac Segmentation. CoRR abs/1608.03974 (2016) - [i7]Savelie Cornegruta, Robert Bakewell, Samuel Withey, Giovanni Montana:
Modelling Radiological Language with Bidirectional Long Short-Term Memory Networks. CoRR abs/1609.08409 (2016) - [i6]Petros-Pavlos Ypsilantis, Giovanni Montana:
Recurrent Convolutional Networks for Pulmonary Nodule Detection in CT Imaging. CoRR abs/1609.09143 (2016) - [i5]Ricardo Pio Monti, Christoforos Anagnostopoulos, Giovanni Montana:
A framework for adaptive regularization in streaming Lasso models. CoRR abs/1610.09127 (2016) - [i4]James H. Cole, Rudra P. K. Poudel, Dimosthenis Tsagkrasoulis, Matthan W. A. Caan, Claire J. Steves, Tim D. Spector, Giovanni Montana:
Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker. CoRR abs/1612.02572 (2016) - 2015
- [j23]Zi Wang, Wei Yuan, Giovanni Montana:
Sparse multi-view matrix factorization: a multivariate approach to multiple tissue comparisons. Bioinform. 31(19): 3163-3171 (2015) - [j22]Da Ruan, Alastair Young, Giovanni Montana:
Differential analysis of biological networks. BMC Bioinform. 16: 327:1-327:13 (2015) - [c10]Zhana Kuncheva, Giovanni Montana:
Community Detection in Multiplex Networks using Locally Adaptive Random Walks. ASONAM 2015: 1308-1315 - [c9]Alexandre de Brébisson, Giovanni Montana:
Deep neural networks for anatomical brain segmentation. CVPR Workshops 2015: 20-28 - [c8]Eva Janousová, Daniel Schwarz, Giovanni Montana, Tomás Kaspárek:
Brain image classification based on automated morphometry and penalised linear discriminant analysis with resampling. FedCSIS 2015: 263-268 - [c7]Adrien Payan, Giovanni Montana:
Predicting Alzheimer's Disease - A Neuroimaging Study with 3D Convolutional Neural Networks. ICPRAM (2) 2015: 355-362 - [c6]Ricardo Pio Monti, Romy Lorenz, Peter Hellyer, Robert Leech, Christoforos Anagnostopoulos, Giovanni Montana:
Graph Embeddings of Dynamic Functional Connectivity Reveal Discriminative Patterns of Task Engagement in HCP Data. PRNI 2015: 1-4 - [i3]Alexandre de Brébisson, Giovanni Montana:
Deep Neural Networks for Anatomical Brain Segmentation. CoRR abs/1502.02445 (2015) - [i2]Adrien Payan, Giovanni Montana:
Predicting Alzheimer's disease: a neuroimaging study with 3D convolutional neural networks. CoRR abs/1502.02506 (2015) - [i1]Zhana Kuncheva, Giovanni Montana:
Community detection in multiplex networks using locally adaptive random walks. CoRR abs/1507.01890 (2015) - 2014
- [j21]Zi Wang, Edward W. J. Curry, Giovanni Montana:
Network-guided regression for detecting associations between DNA methylation and gene expression. Bioinform. 30(19): 2693-2701 (2014) - [j20]Alberto Cozzini, Ajay Jasra, Giovanni Montana, Adam Persing:
A Bayesian mixture of lasso regressions with t-errors. Comput. Stat. Data Anal. 77: 84-97 (2014) - [j19]Brian McWilliams, Giovanni Montana:
Subspace clustering of high-dimensional data: a predictive approach. Data Min. Knowl. Discov. 28(3): 736-772 (2014) - [j18]Ricardo Pio Monti, Peter Hellyer, David J. Sharp, Robert Leech, Christoforos Anagnostopoulos, Giovanni Montana:
Estimating time-varying brain connectivity networks from functional MRI time series. NeuroImage 103: 427-443 (2014) - [j17]Christopher Minas, Giovanni Montana:
Distance-Based Analysis of Variance: Approximate Inference. Stat. Anal. Data Min. 7(6): 450-470 (2014) - 2013
- [j16]Christopher Minas, Edward W. J. Curry, Giovanni Montana:
A distance-based test of association between paired heterogeneous genomic data. Bioinform. 29(20): 2555-2563 (2013) - [j15]Yue Wang, Wilson Wen Bin Goh, Limsoon Wong, Giovanni Montana:
Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes. BMC Bioinform. 14(S-16): S6 (2013) - [j14]Alberto Cozzini, Ajay Jasra, Giovanni Montana:
Model-Based Clustering with gene Ranking using penalized Mixtures of heavy-tailed Distributions. J. Bioinform. Comput. Biol. 11(3) (2013) - 2012
- [j13]Maria Vounou, Eva Janousová, Robin Wolz, Jason L. Stein, Paul M. Thompson, Daniel Rueckert, Giovanni Montana:
Sparse reduced-rank regression detects genetic associations with voxel-wise longitudinal phenotypes in Alzheimer's disease. NeuroImage 60(1): 700-716 (2012) - [j12]Matt Silver, Eva Janousová, Xue Hua, Paul M. Thompson, Giovanni Montana:
Identification of gene pathways implicated in Alzheimer's disease using longitudinal imaging phenotypes with sparse regression. NeuroImage 63(3): 1681-1694 (2012) - [j11]Brian McWilliams, Giovanni Montana:
Multi-view predictive partitioning in high dimensions. Stat. Anal. Data Min. 5(4): 304-321 (2012) - [c5]Maurice Berk, Giovanni Montana:
A Skew-t-Normal Multi-level Reduced-Rank Functional PCA Model for the Analysis of Replicated Genomics Time Course Data. IDA 2012: 56-66 - 2011
- [j10]Maurice Berk, Timothy M. D. Ebbels, Giovanni Montana:
A statistical framework for biomarker discovery in metabolomic time course data. Bioinform. 27(14): 1979-1985 (2011) - [j9]Christopher Minas, Simon J. Waddell, Giovanni Montana:
Distance-based differential analysis of gene curves. Bioinform. 27(22): 3135-3141 (2011) - [j8]Kostas Triantafyllopoulos, Giovanni Montana:
Dynamic modeling of mean-reverting spreads for statistical arbitrage. Comput. Manag. Sci. 8(1-2): 23-49 (2011) - [j7]Matt Silver, Giovanni Montana, Thomas E. Nichols:
False positives in neuroimaging genetics using voxel-based morphometry data. NeuroImage 54(2): 992-1000 (2011) - [c4]Brian McWilliams, Giovanni Montana:
Predictive Subspace Clustering. ICMLA (1) 2011: 247-252 - [c3]Eva Janousová, Maria Vounou, Robin Wolz, Katherine R. Gray, Daniel Rueckert, Giovanni Montana:
Fast Brain-Wide Search of Highly Discriminative Regions in Medical Images: an Application to Alzheimers Disease. MIUA 2011: 17-22 - 2010
- [j6]Maria Vounou, Thomas E. Nichols, Giovanni Montana:
Discovering genetic associations with high-dimensional neuroimaging phenotypes: A sparse reduced-rank regression approach. NeuroImage 53(3): 1147-1159 (2010) - [j5]Brian McWilliams, Giovanni Montana:
Sparse partial least squares regression for on-line variable selection with multivariate data streams. Stat. Anal. Data Min. 3(3): 170-193 (2010)
2000 – 2009
- 2009
- [j4]Giovanni Montana, Kostas Triantafyllopoulos, Theodoros Tsagaris:
Flexible least squares for temporal data mining and statistical arbitrage. Expert Syst. Appl. 36(2): 2819-2830 (2009) - 2008
- [c2]Giovanni Montana, Francesco Parrella:
Learning to Trade with Incremental Support Vector Regression Experts. HAIS 2008: 591-598 - [c1]Giovanni Montana, Kostas Triantafyllopoulos, Theodoros Tsagaris:
Data stream mining for market-neutral algorithmic trading. SAC 2008: 966-970 - 2007
- [j3]Giovanni Montana, Clive J. Hoggart:
Statistical software for gene mapping by admixture linkage disequilibrium. Briefings Bioinform. 8(6): 393-395 (2007) - 2006
- [j2]Giovanni Montana:
Statistical methods in genetics. Briefings Bioinform. 7(3): 297-308 (2006) - 2005
- [j1]Giovanni Montana:
HapSim: a simulation tool for generating haplotype data with pre-specified allele frequencies and LD coefficients. Bioinform. 21(23): 4309-4311 (2005)
Coauthor Index
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