Embedded Files
Working papers
These working papers are listed roughly in reverse chronological order of their finalization date.Working papers
with G. Wang, Z. Hu, V. Muthukumar, J. Abernethy
with L. Applebaum, T. Dick, H. Kaplan, T. Koren
Selected publications
These publications are listed roughly in reverse chronological order of their initial publication date.Selected publications
Nearly Optimal Sample Complexity for Learning with Label Proportions
with R. Busa-Fekete, T. Dick, H. Kaplan, T. Koren, U. Stemmer
Proc. of the 42th International Conference on Machine Learning (ICML 2025).
with F. Bonchi, A. Panisson, F. P. Nerini, F. Vitale
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025).
with R. Busa-Fekete, T. Dick, A. M. Medina, A. Smith, M. Swanberg.
Proc. of the 38th conference on Neural Information Processing Systems (NeurIPS 2024).
with S. Pasteris, F, Vitale, M Herbster, A. Panisson
Proc of the 35th International Conference on Algorithmic Learning Theory (ALT 2024)
Data-Driven Online Model Selection With Regret Guarantees
with C. Dann, A. Pacchiano
Proc. of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024)
with R. Busa-Fekete, H. Choi, T. Dick, A. M. Medina
Proc. of the 37th conference on Neural Information Processing Systems (NeurIPS 2023).
with S. Rudra, S. Goel, A. Santara, F. Xia, L. Perron, C. Parada, V. Sindhwani, G. Aggarwal
Proc. IEEE International Conference on Robotics and Automation (ICRA 2023).
See also website and longer version.
with A. Pacchiano and C. Dann
Proc. of the 36th conference on Neural Information Processing Systems (NeurIPS 2022).
with R. Busa-Fekete, H. Choi, K. Dembczynski, H. Reeve, B. Szorenyi
Proc. of the 36th conference on Neural Information Processing Systems (NeurIPS 2022).
with Z. Wang and T. Zhang
Journal of Machine Learning Research 25(262):1−42, 2024
Preliminary version in proc. of the 39th International Conference on Machine Learning (ICML 2022).
with G. Agarwal, A. Santara, and S. Li
Proc of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022).
with P. Awasthi, C. Dann, A. Sehkhari, Z. Wang
Proc. of the 35th conference on Neural Information Processing Systems (NeurIPS 2021).
with G. Citovsky, G. DeSalvo, L. Karydas, A. Rajagopalan, A. Rostamizadeh, S. Kumar
Proc. of the 35th conference on Neural Information Processing Systems (NeurIPS 2021).
with G. DeSalvo, T. Thune
Proc. of the 35th conference on Neural Information Processing Systems (NeurIPS 2021).
with A. Pacchiano, C. Dann,, M. Purohit, A. Das, A. Cutkosky
Proc. of the 38th International Conference on Machine Learning (ICML 2021).
with G. Citovsky, D. Vainstein, A. Rajagopalan, C. Procopiuc , F. Vitale
Proc. of the 38th International Conference on Machine Learning (ICML 2021).
with L. Cella, M. Pontil
Proc. of the 38th International Conference on Machine Learning (ICML 2021).
with D. Foster, M. Mohri, J. Zimmert
Proc. of the 34th conference on Neural Information Processing Systems (NeurIPS 2020).
Full version here.
with C. Cortes, G. DeSalvo, M. Mohri, N. Zhang.
Proc. of the 37th International Conference on Machine Learning (ICML 2020).
with C. Cortes, G. DeSalvo, M. Mohri, N. Zhang.
Proc. of the 37th International Conference on Machine Learning (ICML 2020).
Transient-Based Internet of Things Emitter Identification Using Convolutional Neural Networks and Optimized General Linear Chirplet Transform
with G. Baldini
IEEE Communication Letters, 24/7 (2020) , 1482--1486.
with C. Cortes, G. DeSalvo, M. Mohri, N. Zhang.
Proc. of the 36th International Conference on Machine Learning (ICML 2019).
with F. Vitale, A. Rajagopalan
Proc. of the 33rd conference on Neural Information Processing Systems (NeurIPS 2019).
with C. Cortes, G. DeSalvo, M. Mohri, S. Yang.
Proc. of the 36th International Conference on Machine Learning (ICML 2019).
Microphone Identification using Convolutional Neural Networks
with G. Baldini, I. Amerini.
IEEE Sensors Letters, 3/7 (2019), pp. 1--4.
with C. Cortes, G. DeSalvo, M. Mohri, N. Zhang.
Proc. 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019).
A Comparison of techniques for radiometric identification based on deep convolutional neural networks.
with G. Baldini, R. Giuliani, G. Steri.
Electronic Letters, 55/2, pp. 90--92, 2019.
with F. Vitale and N. Parotsidis.
Proc. of the 32nd conference on Neural Information Processing Systems (NIPS 2018).
with C. Cortes, G. DeSalvo, M. Mohri, S. Yang.
Proc. of the 35th International Conference on Machine Learning (ICML 2018).
with N. Cesa-Bianchi, Y. Mansour.
Proc. of the 31st Annual Conference on Learning Theory (COLT 2018).
Long version (also with. R. Cesari and R. Colomboni), Journal of Machine Learning Research, 23 : 1−24, 2022.
with S. Pasteris, F. Vitale, M. Herbster.
Proc. Algorithmic Learning Theory 2018 (ALT 2018).
Measures to Address the Lack of Portability of the RF Fingerprints for Radiometric Identification
with G. Baldini, R. Giuliani, G. Steri, and I. Sanchez, NTMS 2018.
The Application of the Symbolic Aggregate Approximation Algorithm (SAX) to Radio Frequency Fingerprinting of IoT Devices
with G. Baldini, R. Giuliani, and G. Steri, SCVT 2017.
with G. Neu, N. Cesa-Bianchi, G. Lugosi.
Proc. of the 31st conference on Neural Information Processing Systems (NIPS 2017).
Imaging time series for the identification of IoT devices through RF fingerprinting
with with G. Baldini, G. Steri, and R. Giuliani
Proc. of the 51st International Carnahan Conference on Security Technology (ICCST 2017).
ICCST-2017_paper_34.pdfOn Context-Dependent Clustering of Bandits (main/supplemental)
with S. Li, A. Karatzoglou, P. Kar, E. Etrue, G. Zappella
Proc. of the 34th International Conference on Machine Learning (ICML 2017).
cab-final-main.pdfcab-final-supp.pdfAlgorithmic chaining and the role of partial feedback in online nonparametric learning (short/long version)
with N. Cesa-Bianchi, P. Gaillard, S. Gerchinovitz
Proc. of the 30th Annual Conference on Learning Theory (COLT 2017).
NonparametricLearning_short.pdfNonparametricLearning_long.pdfIdentification of mobile phones using the built-in magnetometers stimulated by motion patterns
with G. Baldini, F. Dimc, R. Kamnik, G. Steri, and R. Giuliani
Sensors, 17, 783, 2017.
sensors-17-00783.pdfOn the Troll-Trust Model for Edge Sign Prediction in Social Networks (main/supplemental)
with G. Le Falher, N. Cesa-Bianchi, F. Vitale
Proc. 20th International Conference on Artificial Intelligence and Statistics (AISTATS 2017).
aistats2017.pdfaistats2017_supplementary.pdfDelay and Cooperation in Nonstochastic Bandits
with N. Cesa-Bianchi, Y. Mansour.
Journal of Machine Learning Research, 20 (2019), pp. 1--38.
Preliminary version (also with A. Minora ) in proc. of the 29th Annual Conference on Learning Theory (COLT 2016).
bandCoop.pdfCollaborative Filtering Bandits
with S. Li, A. Karatzoglou
Proc. of the 39th ACM Conference on Research and Development in Information Retrieval (SIGIR 2016).
cofiba.pdfOnline Clustering of Bandits (main/supplemental)
with S. Li and G. Zappella
Proc. of the 31st International Conference on Machine Learning (ICML 2014).
club_icml.pdfclub_icml_suppl.pdfFrom Bandits to Experts: A Tale of Domination and Independence
with N. Alon, N. Cesa-Bianchi, Y. Mansour
Proc. of the 27th conference on Neural Information Processing Systems (NIPS 2013).
Long version (also with O. Shamir and S. Mannor): Nonstochastic Multi-armed Bandits with Graph-Structured Feedback
SIAM Journal on Computing, 46/6 (2017), pp. 1785--1826.
revealNips.pdfgraph_bandit_sicomp.pdfA gang of Bandits (main/supplemental)
with N. Cesa-Bianchi, G. Zappella
Proc. of the 27th conference on Neural Information Processing Systems (NIPS 2013).
goblin_nips2013.pdfgoblin_nips2013_suppl.pdfOnline Similarity Prediction of Networked Data from Known and Unknown Graphs
with M. Herbster, S. Pasteris
Proc. of the 26th Conference on Learning Theory (COLT 2013).
colt2013_similarity.pdfRegret Minimization for Branching Experts
with E. Gofer, N. Cesa-Bianchi, Y. Mansour
Proc. of the 26th Conference on Learning Theory (COLT 2013).
colt2013_branching.pdfRegret Minimization for Reserve Prices in Second-Price Auctions
with N. Cesa-Bianchi, Y. Mansour
IEEE Trans. on Information Theory, 61/1 (2015), pp. 549--564.
Preliminary version in Proc. 24th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2013), pp 1190-1204.
See also slides of the talk given at SODA 2013.
ieee_second_price2.pdfslides_soda2013.pdfOn multilabel classification and ranking with bandit feedback
with F. Orabona
Journal of Machine Learning Research, 15 (2014), pp. 2451--2487.
Preliminary version in Proc. 26th conference on Neural Information processing Systems (NIPS 2012).
jmlr_ranking.pdfA linear time active learning algorithm for link classification
with N. Cesa-Bianchi, F. Vitale, G. Zappella
Proc. of the 26th conference on Neural Information processing Systems (NIPS 2012).
starmaker_long.pdfA Correlation Clustering Approach to Link Classification in Signed Networks
with N. Cesa-Bianchi, F. Vitale, G. Zappella
Proc. 25th Conference on Learning Theory (COLT 2012).
colt2012.pdfBeyond logarithmic bounds in online learning
with F. Orabona, N. Cesa-Bianchi
Proc. 15th International Conference on Artificial Intelligence and Statistics (Aistats 2012).
aistats2012.pdfSee the tree through the lines: the Shazoo algorithm
with N. Cesa-Bianchi, F. Vitale, G. Zappella
Proc. 25th conference on Neural Information processing Systems (NIPS 2011).
nips2011_long.pdfMulticlass classification with bandit feedback using adaptive regularization
with K. Crammer
Machine Learning, 90/3 (2013), pp. 347-383.
Preliminary version in Proc. 28th International Conference on Machine Learning (ICML 2011).
mlj_mcbandit12.pdfSelective sampling and active learning from single and multiple teachers
with O. Dekel, K. Sridharan
Journal of Machine Learning Research, 13 (2012), pp. 2655--2697.
Preliminary version in Proc. of the 23rd Conference on Learning Theory (COLT 2010).
selective_jmlr.pdfActive learning on trees and graphs
with N. Cesa-Bianchi, F. Vitale, G. Zappella
Proc. 23rd Conference on Learning Theory (COLT 2010).
active8.pdfRandom spanning trees and the prediction of weighted graphs
with N. Cesa-Bianchi, F. Vitale, G. Zappella
Journal of Machine Learning Research, 14 (2013), pp. 1251--1284.
Preliminary version in Proc. 27th International Conference on Machine Learning (ICML 2010).
wta_jmlr.pdfPredicting the labels of an unknown graph via adaptive exploration
with N. Cesa-Bianchi, F, Vitale
Theoretical Computer Science , special issue on Algorithmic Learning Theory, 412/19 (2011), pp. 1791--1804.
Preliminary version in Proc. 20th International conference on Algorithmic Learning Theory (Alt 2009).
cga_tcs.pdfFast and optimal prediction of a labeled tree
with N. Cesa-Bianchi, F. Vitale
Proc. 22nd Conference on Learning Theory (COLT 2009).
treeopt-colt2.pdfRobust bounds for classification via selective sampling
with N. Cesa-Bianchi, F. Orabona
Proc. 26th International Conference on Machine Learning (ICML 2009).
kwik_camera_ready3.pdfLearning Noisy Linear Classifiers via Adaptive and Selective Sampling
with G. Cavallanti, N. Cesa-Bianchi
Machine Learning, 83 (2011), pp. 71-102.
Preliminary version in Proc. 22nd conference on Neural Information processing Systems (NIPS 2008).
selsam_revised.pdfLinear algorithms for online multitask classification
with G. Cavallanti, N. Cesa-Bianchi
Journal of Machine Learning Research, 11 (2010), pp. 2901--2934.
Preliminary version in Proc. of the 21st Conference on Learning Theory (COLT'08).
See also the presentation at the Workshop on Learning Theory at FoCM 2008, June 2008.
ccg10multitask.pdftalk_hk08.pdfOn higher-order Perceptron algorithms
with C. Brotto, F. Vitale
Proc. 21st conference on Neural Information processing Systems (NIPS 2007).
hopa_ana3.pdfHierarchical Classification: Combining Bayes with SVM
with N. Cesa-Bianchi, L. Zaniboni
Proc. 23rd International Conference on Machine Learning (ICML 2006), pages 177--184.
See also the presentation given at University College London, July 2006.
svm-bayes2.pdftalk_ucl06.pdfwith G. Cavallanti, N. Cesa-Bianchi
Machine Learning, 69/2-3 (2007), special issue on COLT 2006, pp. 143--167.
Preliminary version in Proc. of the 19th annual Conference on Learning Theory (COLT'06), pages 483--496.
Improved risk tail bounds for on-line algorithms
with N. Cesa-Bianchi
IEEE Trans. on Information Theory, 54/1 (2008), pp. 386--390.
Preliminary version in Proc. 18th conference on Neural Information processing Systems (NIPS 2005).
iada_full5.pdfIncremental algorithms for hierarchical classification
with N. Cesa-Bianchi, L. Zaniboni
Journal of Machine Learning Research, 7 (2006), pp. 31--54.
Preliminary version in Proc. 17th conference on Neural Information processing Systems (NIPS 2004).
hier-hloss3.pdfWorst-Case Analysis of Selective sampling for linear-threshold algorithms
with N. Cesa-Bianchi, L. Zaniboni
Journal of Machine Learning Research, 7 (2006), pp. 1205--1230.
Preliminary version in Proc. 17th conference on Neural Information processing Systems (NIPS 2004).
jmlr_randlabel.pdfRegret bounds for hierarchical classification with linear-threshold functions
with N. Cesa-Bianchi, A. Conconi
Proc. of the 17th annual Conference on Learning Theory (COLT'04), pp. 93-108.
Fast feature selection from microarray expression data via multiplicative large margin algorithms
Proc. of the 16th conference on Neural Information processing Systems (NIPS 2003).
Margin-based algorithms for information filtering
with N. Cesa-Bianchi, A. Conconi
Proc. 15th conference on Neural Information processing Systems (NIPS 2002), pp. 470-477.
filtering_nips02.pdfLearning probabilistic linear-threshold classifiers via selective sampling
with N. Cesa-Bianchi, A. Conconi
Proc. 16th annual Conference on Learning Theory (COLT'03), pp. 373-387.
selsam_colt03.pdfA second-order perceptron algorithm
with N. Cesa-Bianchi, A. Conconi,
SIAM Journal on Computing, 34/3 (2005), pp. 640-668.
Preliminary version in Proc. 15th annual conference on Computational Learning Theory (COLT'02).
soperc_sicomp.pdfOn the generalization ability of on-line learning algorithms
with N. Cesa-Bianchi, A. Conconi,
IEEE Trans. on Information Theory, 50/9 (2004), pp. 2050-2057.
Preliminary version in Proc. 14th conference on Neural Information processing Systems (NIPS 2001)
adasampling_ieee_it.pdfA new approximate maximal margin classification algorithm
Journal of Machine Learning Research 2 (2002), pp. 213-242.
Preliminary version in Proc. of the 13th conference on Neural Information processing Systems (NIPS 2000).
A Matlab implementation of the algorithm (with kernels) can be found, e.g., here.
alma_jmlr.pdfAdaptive and self-confident on-line learning algorithms
with P. Auer, N. Cesa-Bianchi,
Journal of Computer and System Sciences, 64/1 (2002), special issue on Computational Learning Theory, pp. 48-75.
Preliminary version in Proc. 13th annual conference on Computational Learning Theory (COLT'00), pp. 107-117.
vareta_jcss.pdfMachine Learning, 53/3 (2003), pp. 265-299.
Preliminary version (with N. Littlestone) in Proc. 12th annual ACM conference on Computational Learning Theory (COLT'99), pp. 1-11.
Linear hinge loss and average margin
with M. Warmuth
Proc. 11th conference on Neural Information processing Systems (NIPS 1998), pp. 225-231.
hingeloss_nips98.pdfImproved lower bounds for learning from noisy examples: an information-theoretic approach
with D. Helmbold
Information and Computation, 166/2 (2001), pp. 133-155.
Preliminary version in Proc. 11th annual ACM conference on Computational Learning Theory (COLT'98), pp. 104-115.
noisyex_ic.pdfP-sufficient statistics for PAC learning k-term-DNF formulas through enumeration
with B. Apolloni
Theoretical Computer Science, 230 (2000), pp. 1-37.
Sample size lower bounds in PAC learning by algorithmic complexity theory
with B. Apolloni
Theoretical Computer Science, 209 (1998), pp. 141-162.
kolmog_tcs.pdfAll publications
All publications
As of August 2018
As of August 2018
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