Luca Baldassarre

 

Research interests:

  • Model-based machine learning and compressive sensing
  • Convex and discrete optimization

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Biography 

Luca received a M.Sc. in Physics in 2006 and a PhD in Machine Learning in 2010 at the University of Genoa, Italy.

He then joined the Computer Science Department of University College London, UK,  to work with Prof. Massimiliano Pontil on structured sparsity models for machine learning and convex optimization.

He was a postdoc with the LIONS of Prof. Volkan Cevher at the Ecole Polytechnique Federale de Lausanne, Switzerland from September 2012 to November 2015.

Links
 
 

PUBLICATIONS

C. Aprile; K. Ture; L. Baldassarre; M. Shoaran; G. Yilmaz et al. : Adaptive Learning-Based Compressive Sampling for Low-power Wireless Implants; Ieee Transactions On Circuits And Systems I-Regular Papers. 2018-11-01. DOI : 10.1109/TCSI.2018.2853983.
C. Aprile; J. Wuthrich; L. Baldassarre; Y. Leblebici; V. Cevher : An area and power efficient on-the-fly LBCS transformation for implantable neuronal signal acquisition systems. 2018-01-01. 15th ACM International Conference on Computing Frontiers, Ischia, ITALY, May 08-10, 2018. p. 228-231. DOI : 10.1145/3203217.3203260.
C. Aprile; K. Ture; L. Baldassarre; M. Shoaran; G. Yilmaz et al. : Adaptive Learning-Based Compressive Sampling for Low-power Wireless Implants; IEEE Transactions on Circuits and Systems–I. 2018.
C. Aprile; J. Wüthrich; L. Baldassarre; Y. Leblebici; V. Cevher : An area and power efficient on-the-fly LBCS transformation for implantable neuronal signal acquisition systems. 2018. ACM International Conference on Computing Frontiers 2018, Ischia, Italy, May 8-10, 2018.
C. Aprile; J. Wüthrich; L. Baldassarre; Y. Leblebici; V. Cevher : DCT Learning-Based Hardware Design for Neural Signal Acquisition Systems. 2017. Computing Frontiers Conference 2017, Siena, Italy, May 15-17, 2017. p. 391-394. DOI : 10.1145/3075564.3078890.
V. Cevher; Y.-h. Li; I. Bogunovic; L. Baldassarre; J. Scarlett et al. ; Learning-based subsampling. US2017109650 . 2017.
A. Kyrillidis; B. Bah; R. Hasheminezhad; Q. Tran Dinh; L. Baldassarre et al. : Convex block-sparse linear regression with expanders - provably. 2016. The 19th International Conference on Artificial Intelligence and Statistics (AISTATS 2016), Cadiz, Spain, May 7-11, 2016.
C. Aprile; L. Baldassarre; V. Gupta; J. Yoo; M. Shoaran et al. : Learning-Based Near-Optimal Area-Power Trade-offs in Hardware Design for Neural Signal Acquisition. 2016. 26th edition of GLSVLSI, Boston, USA, May 18-20, 2016. p. 433-438. DOI : 10.1145/2902961.2903028.
L. Baldassarre; Y.-H. Li; J. Scarlett; B. Gözcü; I. Bogunovic et al. : Learning-Based Compressive Subsampling; IEEE Journal on Selected Topics in Signal Processing. 2016. DOI : 10.1109/Jstsp.2016.2548442.
L. Baldassarre; N. Bhan; V. Cevher; A. Kyrillidis : Group-Sparse Model Selection: Hardness and Relaxations; IEEE Transactions on Information Theory. 2016. DOI : 10.1109/TIT.2016.2602222.
L. Baldassarre; C. Aprile; M. Shoaran; Y. Leblebici; V. Cevher : Structured Sampling and Recovery of iEEG Signals. 2015. IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Cancun, Mexico, December 13-16, 2015.
B. Gözcü; L. Baldassarre; Q. Tran Dinh; C. Aprile; V. Cevher : A Primal-dual Framework For Mixtures Of Regularisers. 2015. 23rd European Signal Processing Conference (EUSIPCO 2015), Nice, France, August 31 - September 4 2015.
S. Satpathi; L. Baldassarre; V. Cevher : Sparse Group Covers and Greedy Tree Approximations. 2015. 2015 IEEE Internation Symposium on Information Theory, Hong Kong, China, June 14-19, 2015.
M. El Halabi; L. Baldassarre; V. Cevher : MAP Estimation for Bayesian Mixture Models with Submodular Priors. 2014. 2014 IEEE International Workshop on Machine Learning for signal processing, Reims, France, Sept 21-24, 2014.
B. Bah; L. Baldassarre; V. Cevher : Model-based Sketching and Recovery with Expanders. 2014. ACM-SIAM Symposium on Discrete Algorithms, Portland, Oregon, USA, January 5-7, 2014. p. 1529-1543. DOI : 10.1137/1.9781611973402.112.
N. Bhan; L. Baldassarre; V. Cevher : Tractability of interpretability via selection of group-sparse models. 2013. IEEE International Symposium on Information Theory Proceedings (ISIT), 2013, Istanbul, Turkey, July 7-13, 2013. DOI : 10.1109/ISIT.2013.6620384.
M. McCoy; V. Cevher; Q. Tran Dinh; A. Asaei; L. Baldassarre : Convexity in source separation: Models, geometry, and algorithms; Signal Processing Magazine, IEEE. 2013. DOI : 10.1109/MSP.2013.2296605.
S. Villa; S. Salzo; L. Baldassarre; A. Verri : Accelerated And Inexact Forward-Backward Algorithms; Siam Journal On Optimization. 2013. DOI : 10.1137/110844805.
M. El Halabi; L. Baldassarre; V. Cevher : To Convexify or Not? Regression with Clustering Penalties on Graphs. 2013. 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Saint Martin, France, December 15-18. 2013. p. 21-24. DOI : 10.1109/CAMSAP.2013.6713997.
N. Noceti; B. Caputo; C. Castellini; L. Baldassarre; A. Barla et al. : Towards a theoretical framework for learning multi-modal patterns for embodied agents. 2009. International Conference on Image Analysis and Processing.
M. Dorigo; V. Trianni; E. Sahin; R. Groß; T. H. Labella et al. : Evolving Self-Organizing Behaviors for a Swarm-bot; Autonomous Robots, special Issue on Swarm Robotics. 2004. DOI : 10.1023/B:AURO.0000033972.50769.1c.
M. Dorigo; E. Tuci; R. Groß; V. Trianni; T. H. Labella et al. : The SWARM-BOTS project. 2004. Swarm Robotics (SAB'2004), Santa Monica, CA, USA, July 17. p. 31-44.