# Publications

# Books

**B002** - Donzellini, G. and Oneto, L. and Ponta, D. and Anguita. D., Springer, Introduction to Digital Systems Design, 2018.

**B001** - Donzellini, G. and Oneto, L. and Ponta, D. and Anguita. D., Springer, Introduzione al Progetto di Sistemi Digitali, 2017.

# Book Chapters

**BC005** - Oneto, L. and Fumeo, E. and Clerico, C. and Canepa, R. and Papa, F. and Dambra, C. and Mazzino, N. and Anguita. D., Innovative Applications of Big Data in the Railway Industry, Kohli, S. and Senthil, A. V. and Easton, J. M. and Roberts, C., IGI Global, Big Data Analytics for Train Delay Prediction: A case study in the Italian Railway Network, 2017.

**BC004** - Oneto, L. and Reyes-Ortiz, J. L. and Anguita, D., Adaptive Mobile Computing: Advances in Processing of Mobile Data Set, Migliardi, M. and Merlo, A. and Al-Haj Baddar, S., Elsevier, Constraint-Aware Data Analysis on Mobile Devices, 2017.

**BC003** - Coraddu, A. and Oneto, L. and Baldi, F. and Anguita, D., Soft Computing for Sustainability Science. Serie Studies In Fuzziness and Soft Computing, Cruz, C., Springer, Vessels Fuel Consumption: a Data Analytics Perspective to Sustainability, 2016.

**BC002** - Oneto, L. and Ridella, S. and Anguita, D., Quantum Inspired Computational intelligence: Research and Applications, Bhattacharyya, S. and Malik, U. and Dutta, P., Morgan Kaufmann, Elsevier, Quantum Computing and Supervised Machine Learning: Training, Model Selection and Error Estimation, 2016.

**BC001** - Bisio, F. and Oneto, L. and Cambria, E., Sentiment Analysis in Social Networks, Pozzi, F. A. and Fersini, E. and Messina, E. and Liu, B., Elsevier, Sentic computing for social network analysis, 2016.

# Journals

**J034** - Cipollini, F. and Oneto, L. and Coraddu, A. and Murphy, A. J. and Anguita, D., Reliability Engineering & System Safety, -, -, Condition-Based Maintenance of Naval Propulsion Systems: Data Analysis with Minimal Feedback., -, 2018.

**J033** - Aiolli, F. and Biehl, M. and Oneto, L., Neurocomputing, -, -, Advances in artificial neural networks, machine learning and computational intelligence, -, 2018.

**J032** - Oneto, L., WIREs Data Mining and Knowledge Discovery, -, -, Model Selection and Error Estimation Without the Agonizing Pain, -, 2018.

**J031** - Cipollini, F. and Oneto, L. and Coraddu, A and Murphy, A. J. and Anguita, D., Ocean Engineering, -, -, Condition-Based Maintenance of Naval Propulsion Systems with Supervised Data Analysis, -, 2018.[J030]Oneto, L. and Navarin, N. and Donini, M. and Ridella, S. and Sperduti, A. and Aiolli, F. and Anguita, D., IEEE Transactions on Neural Networks and Learning Systems, -, -, Learning with Kernels: A Local Rademacher Complexity-based Analysis with Application to Graph Kernels, -, 2018.

**J029** - Oneto, L. and Cipollini, F. and Ridella, S. and Anguita, D., Neurocomputing, -, -, Randomized Learning: Generalization Performance of Old and New Theoretically Grounded Algorithms, -, 2018.

**J028** - Aonzo, S. and Merlo, A. and Migliardi, M. and Oneto, L. and Palmieri, F., IEEE Transactions on Sustainable Computing, -, -, Low-Resource Footprint, Data-Driven Malware Detection on Android, -, 2017.

**J027** - Oneto, L. and Navarin, N. and Sperduti, A. and Anguita, D., Neural Processing Letters, -, -, Multilayer Graph Node Kernels: Stacking while Maintaining Convexity, -, 2017.

**J026** - Oneto, L. and Fumeo, E. and Clerico, C. and Canepa, R. and Papa, F. and Dambra, C. and Mazzino, N. and Anguita. D., Big Data Research, -, -, Train Delay Prediction Systems: a Big Data Analytics Perspective, -, 2017.

**J025** - Oneto, L. and Fumeo, E. and Clerico, C. and Canepa, R. and Papa, F. and Dambra, C. and Mazzino, N. and Anguita. D., IEEE Transactions on Systems, Man and Cybernetics: Systems, -, -, Dynamic Delay Predictions for Large-Scale Railway Networks: Deep and Shallow Extreme Learning Machines Tuned via Thresholdout, -, 2017.

**J024** - Oneto, L. and Navarin, N. and Donini, M. and Sperduti, A. and Aiolli, F. and Anguita, D., Neurocomputing, -, 4-16 - Measuring the Expressivity of Graph Kernels through Statistical Learning Theory, 268 - 2017.

**J023** - Oneto, L. and Laureri, F. and Robba, M. and Delfino, F. and Anguita, D., IEEE System Journal, -, -, Data-Driven Photovoltaic Power Production Nowcasting and Forecasting for Polygeneration Microgrids, -, 2017.

**J022** - Oneto, L. and Ridella, S. and Anguita, D., Pattern Recognition Letters, -, 31-38 - Differential privacy and generalization: Sharper bounds with applications, 89 - 2017.

**J021** - Coraddu, A. Oneto, L. and Baldi, F. and Anguita, D., Ocean Engineering, -, 351-370, Vessels Fuel Consumption Forecast and Trim Optimisation: a Data Analytics Perspective, 130, 2017.[J020]Oneto, L. and Bisio, F. and Cambria, E. and Anguita, D., Cognitive Computation, 2 - 259-274 - SLT-Based ELM for Big Social Data Analysis, 9 - 2017.

**J019** - Oneto, L. and Bisio, F. and Cambria, E. and Anguita, D., Cognitive Computation, 1 - 18-42 - Semi-supervised Learning for Affective Common-Sense Reasoning, 9 - 2017.

**J018** - Oneto, L. and Bisio, F. and Cambria, E. and Anguita, D., IEEE Computational Intelligence Magazine, 3 - 45-55 - Statistical Learning Theory and ELM for Big Social Data Analysis, 11 - 2016.

**J017** - Oneto, L. and Anguita, D. and Ridella, S., Pattern Recognition Letters, -, 200-207 - PAC-bayesian analysis of distribution dependent priors: Tighter risk bounds and stability analysis, 80, 2016.

**J016** - Oneto, L. and Anguita, D. and Ridella, S., Neural Networks, -, 62-75 - A local Vapnik-Chervonenkis complexity, 82 - 2016.

**J015** - Oneto, L. and Ridella, S. and Anguita, D., Machine Learning, 1 - 103-136 - Tikhonov, Ivanov and Morozov regularization for support vector machine learning, 103 - 2015.

**J014** - Oneto, L. and Ridella, S. and Anguita, D., ACM Transaction on Embedded Computing, 2 - 23:1-23:29 - Learning Hardware-Friendly Classifiers through Algorithmic Stability, 15 - 2016.

**J013** - Vahdat, M. and Oneto, L. and Anguita, D. and Funk, M. and Rauterberg, M., Neurocomputing, -, 14-28 - Can Machine Learning explain Human Learning?, 192 - 2016.

**J012** - Reyes-Ortiz, J. L. and Oneto, L. and Sama, A. and Parra, X. and Anguita, D., Neurocomputing, -, 754-767 - Transition-Aware Human Activity Recognition Using Smartphones, 171 - 2016.

**J011** - Oneto, L. and Ghio, A. and Ridella, S. and Anguita, D., Neural Processing Letters, 2 - 567-602 - Global Rademacher Complexity Bounds: From Slow to Fast Convergence Rates, 43 - 2015.[J010]Oneto, L. and Ghio, A. and Ridella, S. and Anguita, D., Neural Networks, -, 115-125 - Local Rademacher Complexity: Sharper Risk Bounds With and Without Unlabeled Samples, 65 - 2015.

**J009** - Oneto, L. and Ghio, A. and Ridella, S. and Anguita, D., Neurocomputing, -, 225-235 - Learning Resource-Aware Models for Mobile Devices: from Regularization to Energy Efficiency, 169 - 2015.

**J008** - Oneto, L. and Ghio, A. and Ridella, S. and Anguita, D., IEEE Transactions on Cybernetics, 9 - 1913-1926 - Fully Empirical and Data-Dependent Stability-Based Bounds, 45 - 2015.

**J007** - Coraddu, A. and Oneto, L. and Ghio, A. and Savio, S. and Anguita, D. and Figari, M., Proceedings of the Institution of Mechanical Engineers Part M: Journal of Engineering for the Maritime Environment, 1 - 136-153 - Machine learning approaches for improving condition-based maintenance of naval propulsion plants, 230, 2016.

**J006** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., IEEE Transactions on Neural Networks and Learning Systems, 12 - 2202-2211 - A Deep Connection Between the Vapnik-Chervonenkis Entropy and the Rademacher Complexity, 25 - 2014.

**J005** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., Pattern Recognition Letters, -, 210-219 - Unlabeled patterns to tighten Rademacher complexity error bounds for kernel classifiers, 37 - 2014.

**J004** - Oneto, L. and Ghio, A. and Anguita, D. and Ridella, S., Neural Networks, -, 107-111 - An improved analysis of the Rademacher data-dependent bound using its self bounding property, 44 - 2013.

**J003** - Anguita, D. and Ghio, A. and Oneto, L. and Parra, X. and Reyes-Ortiz, J. L., Journal of Universal Computer Science, 9 - 1295-1314 - Energy Efficient Smartphone-Based Activity Recognition using Fixed-Point Arithmetic., 19 - 2013.

**J002** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., Neural processing letters, 3 - 275-283 - In-sample model selection for trimmed hinge loss support vector machine, 36 - 2012.

**J001** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., IEEE Transactions on Neural Networks and Learning Systems, 9 - 1390-1406 - In-sample and out-of-sample model selection and error estimation for support vector machines, 23 - 2012.

# Conferences

**C056** - Cipollini, F. and Oneto, L. and Coraddu, A., International Symposium On Naval Architecture And Maritime (INT-NAN), A Deep Learning Approach to Marine Propulsion System Maintenance, 2018.

**C055** - Cipollini, F. and Oneto, L. and Coraddu, A. and Savio, S. and Anguita, D., INNS International Conference on Big Data and Deep Learning (INNS BDDL), Unintrusive Monitoring of Induction Motors Bearings via Deep Learning on Stator Currents, 2018.

**C054** - Oneto, L. and Navarin, N. and Donini, M. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Emerging Trends in Machine Learning: Beyond Conventional Methods and Data, 2018.

**C053** - Oneto, L. and Ridella, S. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Local Rademacher Complexity Machine, 2018.

**C052** - Lulli, A. and Oneto, L. and Anguita, D., IEEE International Conference on Big Data (IEEE BIG DATA), Crack Random Forest for Arbitrary Large Datasets, 2015.

**C051** - Oneto, L. and Coraddu, A. and Sanetti, P. and Karpenko, O and Cipollini, F. and Cleophas, T. and Anguita, D., International Conference on Artificial Neural Networks (ICANN), Marine Safety and Data Analytics: Vessel Crash Stop Maneuvering Performance Prediction, 2017.

**C050** - Lulli, A. and Oneto, L. and Anguita, D., International Conference on Artificial Neural Networks (ICANN), ReForeSt: Random Forests in Apache Spark, 2017.

**C049** - Oneto, L. and Siri, A. and Luria, G. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Dropout Prediction at University of Genoa: a Privacy Preserving Data Driven Approach, 2017.

**C048** - Oneto, L. and Ridella, S. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Generalization Performances of Randomized Classifiers and Algorithms built on Data Dependent Distributions, 2017.

**C047** - Oneto, L. and Navarin, N. and Sperduti, A. and Anguita, D., IEEE International Joint Conference on Neural Networks (IJCNN), Deep Graph Node Kernels: a Convex Approach, 2017.

**C046** - Oneto, L. and Fumeo, E. and Clerico, C. and Canepa, R. and Papa, F. and Dambra, C. and Mazzino, N. and Anguita. D., IEEE International Conference on Data Science and Advanced Analytics (DSAA), Advanced Analytics for Train Delay Prediction Systems by Including Exogenous Weather Data, 2016.

**C045** - Oneto, L. and Fumeo, E. and Clerico, C. and Canepa, R. and Papa, F. and Dambra, C. and Mazzino, N. and Anguita. D., INNS International Conference on Big Data (INNS BIG DATA), Delay Prediction System for Large-Scale Railway Networks based on Big Data Analytics, 2016.

**C044** - Oneto, L. and Coraddu, A. and Anguita, D. and Cleophas, T. and Xepapa, K., International Forum on Research and Technologies for Society and Industry (RTSI), Vessel Monitoring and Design in Industry 4.0: a Data Driven Perspective, 2016.

**C043** - Oneto, L. and Navarin, N. and Donini, M. and Aiolli, F. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Advances in Learning with Kernels: Theory and Practice in a World of growing Constraints, 2016.

**C042** - Oneto, L. and Ridella, S. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Tuning the Distribution Dependent Prior in the PAC-Bayes Framework based on Empirical Data, 2016.

**C041** - Orlandi, I. and Oneto, L. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Random Forests Model Selection, 2016.

**C040** - Oneto, L. and Navarin, N. and Donini, M. and Sperduti, A. and Aiolli, F. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Measuring the Expressivity of Graph Kernels through the Rademacher Complexity, 2016.

**C039** - Coraddu, A. and Cleophas, T. and Xepapa, K. and Oneto, L. and Anguita, D., International Conference on Maritime Technology and Engineering (MARTECH), Operational profiles data analytics for ship design improvement, 2016.

**C038** - Coraddu, A. and Cleophas, T. and Ivancsics, S. and Oneto, L., International Conference on Computer Applications and Information Technology in the Maritime Industries (COMPIT), Vessel monitoring based on sensors data collection, 2016.

**C037** - Vahdat, M. and Oneto, L. and Anguita, D. and Funk, M. and Rauterberg, M., European Conference on Technology Enhanced Learning (EC-TEL), A Learning Analytics Approach to Correlate the Academic Achievements of Students with Interaction Data from an Educational Simulator, 2015.

**C036** - Oneto, L. and Orlandi, I. and Anguita, D., IEEE International Conference on Big Data (IEEE BIG DATA), Performance Assessment and Uncertainty Quantification of Predictive Models for Smart Manufacturing Systems, 2015.

**C035** - Reyes-Ortiz, J. L. and Oneto, L. and Anguita, D., INNS International Conference on Big Data (INNS BIG DATA), Big Data Analytics in the Cloud: Spark on Hadoop vs MPI/OpenMP on Beowulf, 2015.

**C034** - Fumeo, E. and Oneto, L. and Anguita, D., INNS International Conference on Big Data (INNS BIG DATA), Condition Based Maintenance in Railway Transportation Systems Based on Big Data Streaming Analysis, 2015.

**C033** - Oneto, L. and Anguita, D., Italian Workshop on Neural Network (WIRN), Learning Hardware Friendly Classifiers through Algorithmic Risk Minimization, 2015.

**C032** - Oneto, L. and Ghio, A. and Ridella, S. and Anguita, D., IEEE International Joint Conference on Neural Networks (IJCNN), Shrinkage Learning to Improve SVM with Hints, 2015.

**C031** - Oneto, L. and Ghio, A. and Ridella, S. and Anguita, D., IEEE International Joint Conference on Neural Networks (IJCNN), Support Vector Machines and Strictly Positive Definite Kernel: The Regularization Hyperparameter is More Important than the Kernel Hyperparameters, 2015.

**C030** -** **Oneto, L. and Ghio, A. and Ridella, S. and Anguita, D., IEEE International Joint Conference on Neural Networks (IJCNN), Fast Convergence of Extended Rademacher Complexity Bounds, 2015.

**C029** - Coraddu, A. and Oneto, L. and Baldi, F. and Anguita, D., IEEE Genova OCEANS'15 MTS, A Ship Efficiency Forecast based on Sensors Data Collection: Improving Numerical Models through Data Analytics, 2015.

**C028** - Vahdat, M. and Oneto, L. and Ghio, A. and Anguita, D. and Funk, M. and Rauterberg, M., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Advances in learning analytics and educational data mining, 2015.

**C027** - Vahdat, M. and Oneto, L. and Ghio, A. and Anguita, D. and Funk, M. and Rauterberg, M., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Human Algorithmic Stability and Human Rademacher Complexity, 2015.

**C026** - Oneto, L. and Pilarz, B. and Ghio, A. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Model Selection for Big Data: Algorithmic Stability and Bag of Little Bootstraps on GPUs, 2015.

**C025** - Coraddu, A. and Oneto, L. and Ghio, A. and Savio, S. and Figari, M. and Anguita, D., IEEE International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles (ESARS), Machine learning for wear forecasting of naval assets for condition-based maintenance applications, 2015.

**C024** - Oneto, L. and Ghio, A. and Ridella, S. and Reyes-Ortiz, J. L. and Anguita, D., IEEE International Conference on Data Mining, International Workshop on High Dimensional Data Mining (ICDM), Out-of-Sample Error Estimation: the Blessing of High Dimensionality, 2014.

**C023** - Vahdat, M. and Oneto, L. and Ghio, A. and Donzellini, G. and Anguita, D. and Funk, M. and Rauterberg, M., European Conference on Technology Enhanced Learning (EC-TEL), A Learning Analytics Methodology to Profile Students Behavior and Explore Interactions with Deeds Simulator, 2014.

**C022** - Reyes-Ortiz, J. L. and Oneto, L. and Ghio, A. and Anguita, D. and Parra, X., International Conference on Artificial Neural Networks (ICANN), Human Activity Recognition on Smartphones With Awareness of Basic Activities and Postural Transitions, 2014.

**C021** - Coraddu, A. and Figari, M. and Ghio, A. and Oneto, L. and Savio, S., International Conference on Computer Applications and Information Technology in the Maritime Industries (COMPIT), A Sustainability Analytics Matlab Tool to Predict Ship Energy Consumption, 2014.

**C020** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., IEEE International Joint Conference on Neural Networks (IJCNN), Smartphone Battery Saving by Bit-Based Hypothesis Spaces and Local Rademacher Complexities, 2014.

**C019** - Ghio, A. and Oneto, L., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Byte The Bullet: Learning on Real-World Computing Architectures, 2014.

**C018** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Learning with Few Bits on Small-Scale Devices: from Regularization to Energy Efficiency, 2014.

**C017** - Anguita, D. and Ghio, A. and Oneto, L. and Parra, X. and Reyes-Ortiz, J. L., International Conference on Artificial Neural Networks (ICANN), Training Computationally Efficient Smartphone-Based Human Activity Recognition Models, 2013.

**C016** - Anguita, D. and Ghio, A. and Oneto, L. and Reyes-Ortiz, J. L. and Ridella, S., International Conference on Artificial Neural Networks (ICANN), A Novel Procedure for Training L1-L2 Support Vector Machine Classifiers, 2013.

**C015** - Anguita, D. and Ghio, A. and Lawal, I. A. and Oneto, L., International Workshop on Advances in Regularization, Optimization, Kernel Methods and Support Vector Machines: theory and applications (ROKS), A Heuristic Approach to Model Selection for Online Support Vector Machines, 2013.

**C014** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., IEEE International Joint Conference on Neural Networks (IJCNN), Some Results About the Vapnik-Chervonenkis Entropy and the Rademacher Complexity, 2013.

**C013** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., IEEE International Joint Conference on Neural Networks (IJCNN), A Support Vector Machine Classifier from a Bit-Constrained, Sparse and Localized Hypothesis Space, 2013.

**C012** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), A Learning Machine with a Bit-Based Hypothesis Space, 2013.

**C011** - Anguita, D. and Ghio, A. and Oneto, L. and Parra, X. and Reyes-Ortiz, J. L., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), A Public Domain Dataset for Human Activity Recognition using Smartphones, 2013.

**C010** - Anguita, D. and Ghio, A. and Oneto, L. and Parra, X. and Reyes-Ortiz, J. L., International Workshop on Ambient Assisted Living (IWAAL), Human Activity Recognition on Smartphones using a Multiclass Hardware-Friendly Support Vector Machine, 2012.

**C009** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S. and Schatten, C., International Conference on Artificial Neural Networks (ICANN), Nested Sequential Minimal Optimization for Support Vector Machine, 2012.

**C008** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., International Conference on Artificial Neural Networks (ICANN), Rademacher Complexity and Structural Risk Minimization: an Application to Human Gene Expression Datasets, 2012.

**C007** - Anguita, D. and Ghelardoni, L. and Ghio, A. and Oneto, L. and Ridella, S., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), The 'K' in K-fold Cross Validation, 2012.

**C006** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Structural Risk Minimization and Rademacher Complexity for Regression, 2012.

**C005** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., Advances in Neural Information Processing Systems (NIPS), The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers, 2011.

**C004** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., IEEE International Joint Conference on Neural Networks (IJCNN), In-sample Model Selection for Support Vector Machines, 2011.

**C003** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., IEEE International Joint Conference on Neural Networks (IJCNN), Selecting the Hypothesis Space for Improving the Generalization Ability of Support Vector Machines, 2011.

**C002** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Maximal Discrepancy vs. Rademacher Complexity for Error Estimation, 2011.

**C001** - Anguita, D. and Ghio, A. and Greco, N. and Oneto, L. and Ridella, S., IEEE International Joint Conference on Neural Networks (IJCNN), Model selection for support vector machines: Advantages and disadvantages of the machine learning theory, 2010.

# Workshops

**W008** - Coraddu, A. and Oneto, L. and Baldi, F. and Pazouki, K. and Norman, R. and Murphy, A. J., Shipping in Changing Climates international conference, A Data Driven approach for ship energy efficiency and maintenance, 2017.

**W007** - Oneto, L. and Anguita, D., Fifth Italian Workshop on Machine Learning and Data Mining, Workshop of the XIII AI*IA Symposium on Artificial Intelligence, PAC-Bayesian and Stability Analysis of Distribution Dependent Priors, 2016.

**W006** - Oneto, L. and Ghio, A. and Anguita, D., Third Italian Workshop on Machine Learning and Data Mining, Workshop of the XIII AI*IA Symposium on Artificial Intelligence, Applied Model Selection and Error Estimation: Some New Results and Open problems, 2014.

**W005** - Oneto, L. and Ghio, A. and Anguita, D. and Ridella, S., Workshop on Resource-Efficient Machine Learning of the Neural Information Processing Systems (NIPS), Learning With Few Bits on Small-Scale Devices, 2013.

**W004** - Anguita, D. and Ghio, A. and Oneto, L., Applications in Electronics Pervading Industry, Environment & Society, A Learning Machine for Embedded Systems, 2013.

**W003** - Anguita, D. and Ghio, A. and Oneto, L. and Parra, X. and Reyes-Ortiz, J. L., Workshop on Machine Learning Approaches to Mobile Context Awareness of the Neural Information Processing Systems (NIPS), Human Activity Recognition on Smartphones for Mobile Context Awareness, 2012.

**W002** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., Virtual Physiological Human (VPH), A Tool for Training Effective Classifiers in the Small Sample Setting, 2012.

**W001** - Anguita, D. and Ghio, A. and Oneto, L. and Reyes-Ortiz, J. L., Applications in Electronics Pervading Industry, Environment & Society, Activity Recognition Using Smartphone Inertial Sensors, 2012.

# Technical Reports

**TR002** - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., University of Genoa, Department of Biophysical and Electronic Engineering, SmartLab, Maximal Discrepancy Vs. Rademacher Complexity for Error Estimation, 2011.

**TR001** - Oneto, L. and Bisogno, A. and Chessa, M., University of Genoa, Department of Biophysical and Electronic Engineering, PSPC lab, Optic flow regularization technique, 2010.