Luca Baldassarre

Orcid: 0000-0002-8050-2048

According to our database1, Luca Baldassarre authored at least 31 papers between 2008 and 2018.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2018
Adaptive Learning-Based Compressive Sampling for Low-power Wireless Implants.
IEEE Trans. Circuits Syst. I Regul. Pap., 2018

An area and power efficient on-the-fly LBCS transformation for implantable neuronal signal acquisition systems.
Proceedings of the 15th ACM International Conference on Computing Frontiers, 2018

2017
DCT Learning-Based Hardware Design for Neural Signal Acquisition Systems.
Proceedings of the Computing Frontiers Conference, 2017

2016
Group-Sparse Model Selection: Hardness and Relaxations.
IEEE Trans. Inf. Theory, 2016

Learning-Based Compressive Subsampling.
IEEE J. Sel. Top. Signal Process., 2016

Learning-Based Near-Optimal Area-Power Trade-offs in Hardware Design for Neural Signal Acquisition.
Proceedings of the 26th edition on Great Lakes Symposium on VLSI, 2016

Convex Block-sparse Linear Regression with Expanders - Provably.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Structured Sparsity: Discrete and Convex approaches.
CoRR, 2015

Sparse group covers and greedy tree approximations.
Proceedings of the IEEE International Symposium on Information Theory, 2015

A primal-dual framework for mixtures of regularizers.
Proceedings of the 23rd European Signal Processing Conference, 2015

Structured sampling and recovery of iEEG signals.
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

2014
Convexity in Source Separation : Models, geometry, and algorithms.
IEEE Signal Process. Mag., 2014

Model-based Sketching and Recovery with Expanders.
Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014

Map estimation for Bayesian mixture models with submodular priors.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

2013
Accelerated and Inexact Forward-Backward Algorithms.
SIAM J. Optim., 2013

Group-Sparse Model Selection: Hardness and Relaxations
CoRR, 2013

Localizing and Comparing Weight Maps Generated from Linear Kernel Machine Learning Models.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

Tractability of interpretability via selection of group-sparse models.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

To convexify or not? Regression with clustering penalties on graphs.
Proceedings of the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2013

On Sparsity Inducing Regularization Methods for Machine Learning.
Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

2012
Multi-output learning via spectral filtering.
Mach. Learn., 2012

A General Framework for Structured Sparsity via Proximal Optimization.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Optimal Computational Trade-Off of Inexact Proximal Methods
CoRR, 2012

Conditional mean embeddings as regressors - supplementary
CoRR, 2012

Structured Sparsity Models for Brain Decoding from fMRI Data.
Proceedings of the Second International Workshop on Pattern Recognition in NeuroImaging, 2012

Conditional mean embeddings as regressors.
Proceedings of the 29th International Conference on Machine Learning, 2012

Modelling transition dynamics in MDPs with RKHS embeddings.
Proceedings of the 29th International Conference on Machine Learning, 2012

2010
Vector Field Learning via Spectral Filtering.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Learning how to grasp objects.
Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010

2009
Towards a Theoretical Framework for Learning Multi-modal Patterns for Embodied Agents.
Proceedings of the Image Analysis and Processing, 2009

2008
Vector valued regression for iron overload estimation.
Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008


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