Fundamental limits in structured principal component analysis and how to reach them
J. Barbier, F. Camilli, M. Mondelli, M. Sáenz, Proceedings of the National Academy of Sciences of the United States of America 120 (2023).
LibreCat: https://research-explorer.ista.ac.at/record/13315
DOI: 10.1073/pnas.2302028120
PMID: 37463204

Multiple packing: Lower bounds via infinite constellations
Y. Zhang, S. Vatedka, IEEE Transactions on Information Theory 69 (2023) 4513–4527.
LibreCat: https://research-explorer.ista.ac.at/record/12838
DOI: 10.1109/TIT.2023.3260950
WoS: 001017307000023
arXiv: 2211.04407

Approximate message passing for multi-layer estimation in rotationally invariant models
Y. Xu, T.Q. Hou, S.S. Liang, M. Mondelli, in:, 2023 IEEE Information Theory Workshop, Institute of Electrical and Electronics Engineers, 2023, pp. 294–298.
LibreCat: https://research-explorer.ista.ac.at/record/13321
DOI: 10.1109/ITW55543.2023.10160238
WoS: 001031733100053
arXiv: 2212.01572

Zero-error communication over adversarial MACs
Y. Zhang, IEEE Transactions on Information Theory 69 (2023) 4093–4127.
LibreCat: https://research-explorer.ista.ac.at/record/14751
DOI: 10.1109/tit.2023.3257239
arXiv: 2101.12426

Codes for the Z-channel
N. Polyanskii, Y. Zhang, IEEE Transactions on Information Theory 69 (2023) 6340–6357.
LibreCat: https://research-explorer.ista.ac.at/record/13269
DOI: 10.1109/TIT.2023.3292219
WoS: 001069680100011
arXiv: 2105.01427

Beyond the universal law of robustness: Sharper laws for random features and neural tangent kernels
S. Bombari, S. Kiyani, M. Mondelli, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 2738–2776.
LibreCat: https://research-explorer.ista.ac.at/record/12859
arXiv: 2302.01629

Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence
D. Wu, V. Kungurtsev, M. Mondelli, in:, Transactions on Machine Learning Research, ML Research Press, 2023.
LibreCat: https://research-explorer.ista.ac.at/record/14924
arXiv: 2210.06819

Deep neural collapse is provably optimal for the deep unconstrained features model
P. Súkeník, M. Mondelli, C. Lampert, in:, 37th Annual Conference on Neural Information Processing Systems, 2023.
LibreCat: https://research-explorer.ista.ac.at/record/14921
arXiv: 2305.13165

Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise
T. Fu, Y. Liu, J. Barbier, M. Mondelli, S. Liang, T. Hou, in:, Proceedings of 2023 IEEE International Symposium on Information Theory, IEEE, 2023, pp. 1178–1183.
LibreCat: https://research-explorer.ista.ac.at/record/14923
DOI: 10.1109/isit54713.2023.10206671
arXiv: 2302.03306

Zero-rate thresholds and new capacity bounds for list-decoding and list-recovery
N. Resch, C. Yuan, Y. Zhang, in:, 50th International Colloquium on Automata, Languages, and Programming, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023.
LibreCat: https://research-explorer.ista.ac.at/record/14083
DOI: 10.4230/LIPIcs.ICALP.2023.99
arXiv: 2210.07754

Concentration without independence via information measures
A.R. Esposito, M. Mondelli, in:, Proceedings of 2023 IEEE International Symposium on Information Theory, IEEE, 2023, pp. 400–405.
LibreCat: https://research-explorer.ista.ac.at/record/14922
DOI: 10.1109/isit54713.2023.10206899
arXiv: 2303.07245

Fundamental limits of two-layer autoencoders, and achieving them with gradient methods
A. Shevchenko, K. Kögler, H. Hassani, M. Mondelli, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 31151–31209.
LibreCat: https://research-explorer.ista.ac.at/record/14459
arXiv: 2212.13468

The capacity of causal adversarial channels
Y. Zhang, S. Jaggi, M. Langberg, A.D. Sarwate, in:, 2022 IEEE International Symposium on Information Theory, IEEE, 2022, pp. 2523–2528.
LibreCat: https://research-explorer.ista.ac.at/record/12011
DOI: 10.1109/ISIT50566.2022.9834709
arXiv: 2205.06708

New results on AVCs with omniscient and myopic adversaries
A.K. Yadav, M. Alimohammadi, Y. Zhang, A.J. Budkuley, S. Jaggi, in:, 2022 IEEE International Symposium on Information Theory, Institute of Electrical and Electronics Engineers, 2022, pp. 2535–2540.
LibreCat: https://research-explorer.ista.ac.at/record/12017
DOI: 10.1109/ISIT50566.2022.9834632

On the capacity of additive AVCs with feedback
P. Joshi, A. Purkayastha, Y. Zhang, A.J. Budkuley, S. Jaggi, in:, 2022 IEEE International Symposium on Information Theory, IEEE, 2022, pp. 504–509.
LibreCat: https://research-explorer.ista.ac.at/record/12013
DOI: 10.1109/ISIT50566.2022.9834850

Polar coded computing: The role of the scaling exponent
D. Fathollahi, M. Mondelli, in:, 2022 IEEE International Symposium on Information Theory, IEEE, 2022, pp. 2154–2159.
LibreCat: https://research-explorer.ista.ac.at/record/12016
DOI: 10.1109/ISIT50566.2022.9834712
arXiv: 2201.10082

Heterogeneous differential privacy via graphs
S. Torkamani, J.B. Ebrahimi, P. Sadeghi, R.G.L. D’Oliveira, M. Médard, in:, 2022 IEEE International Symposium on Information Theory, IEEE, 2022, pp. 1623–1628.
LibreCat: https://research-explorer.ista.ac.at/record/12012
DOI: 10.1109/ISIT50566.2022.9834711
arXiv: 2203.15429

Lower bounds for multiple packing
Y. Zhang, S. Vatedka, in:, 2022 IEEE International Symposium on Information Theory, IEEE, 2022, pp. 3085–3090.
LibreCat: https://research-explorer.ista.ac.at/record/12015
DOI: 10.1109/ISIT50566.2022.9834443

List-decodability of Poisson Point Processes
Y. Zhang, S. Vatedka, in:, 2022 IEEE International Symposium on Information Theory, IEEE, 2022, pp. 2559–2564.
LibreCat: https://research-explorer.ista.ac.at/record/12014
DOI: 10.1109/ISIT50566.2022.9834512

List-decodable zero-rate codes for the Z-channel
N. Polyanskii, Y. Zhang, in:, 2022 IEEE International Symposium on Information Theory, Institute of Electrical and Electronics Engineers, 2022, pp. 2553–2558.
LibreCat: https://research-explorer.ista.ac.at/record/12019
DOI: 10.1109/ISIT50566.2022.9834829

Estimation in rotationally invariant generalized linear models via approximate message passing
R. Venkataramanan, K. Kögler, M. Mondelli, in:, Proceedings of the 39th International Conference on Machine Learning, ML Research Press, 2022.
LibreCat: https://research-explorer.ista.ac.at/record/12540

Towards differential relational privacy and its use in question answering
S. Bombari, A. Achille, Z. Wang, Y.-X. Wang, Y. Xie, K.Y. Singh, S. Appalaraju, V. Mahadevan, S. Soatto, ArXiv (n.d.).
LibreCat: https://research-explorer.ista.ac.at/record/12860
DOI: 10.48550/arXiv.2203.16701
arXiv: 2203.16701

List decoding random Euclidean codes and Infinite constellations
Y. Zhang, S. Vatedka, IEEE Transactions on Information Theory 68 (2022) 7753–7786.
LibreCat: https://research-explorer.ista.ac.at/record/11639
DOI: 10.1109/TIT.2022.3189542
WoS: 000891796100007
arXiv: 1901.03790

Decoding Reed-Muller codes with successive codeword permutations
N. Doan, S.A. Hashemi, M. Mondelli, W.J. Gross, IEEE Transactions on Communications 70 (2022) 7134–7145.
LibreCat: https://research-explorer.ista.ac.at/record/12233
DOI: 10.1109/tcomm.2022.3211101
WoS: 000937284600006
arXiv: 2109.02122

Quadratically constrained myopic adversarial channels
Y. Zhang, S. Vatedka, S. Jaggi, A.D. Sarwate, IEEE Transactions on Information Theory 68 (2022) 4901–4948.
LibreCat: https://research-explorer.ista.ac.at/record/12273
DOI: 10.1109/tit.2022.3167554
WoS: 000838527100004
arXiv: 1801.05951

Parallelism versus latency in simplified successive-cancellation decoding of polar codes
S.A. Hashemi, M. Mondelli, A. Fazeli, A. Vardy, J. Cioffi, A. Goldsmith, IEEE Transactions on Wireless Communications 21 (2022) 3909–3920.
LibreCat: https://research-explorer.ista.ac.at/record/10364
DOI: 10.1109/TWC.2021.3125626
WoS: 000809406400028
arXiv: 2012.13378

Sharp asymptotics on the compression of two-layer neural networks
M.H. Amani, S. Bombari, M. Mondelli, R. Pukdee, S. Rini, IEEE Information Theory Workshop (2022) 588–593.
LibreCat: https://research-explorer.ista.ac.at/record/12538
DOI: 10.1109/ITW54588.2022.9965870
arXiv: 2205.08199

Memorization and optimization in deep neural networks with minimum over-parameterization
S. Bombari, M.H. Amani, M. Mondelli, in:, 36th Conference on Neural Information Processing Systems, Curran Associates, 2022, pp. 7628–7640.
LibreCat: https://research-explorer.ista.ac.at/record/12537
arXiv: 2205.10217

Approximate message passing with spectral initialization for generalized linear models
M. Mondelli, R. Venkataramanan, Journal of Statistical Mechanics: Theory and Experiment 2022 (2022).
LibreCat: https://research-explorer.ista.ac.at/record/12480
DOI: 10.1088/1742-5468/ac9828
WoS: 000889589900001

Optimal combination of linear and spectral estimators for generalized linear models
M. Mondelli, C. Thrampoulidis, R. Venkataramanan, Foundations of Computational Mathematics 22 (2022) 1513–1566.
LibreCat: https://research-explorer.ista.ac.at/record/10211
DOI: 10.1007/s10208-021-09531-x
WoS: 000685721000001
arXiv: 2008.03326

The price of ignorance: How much does it cost to forget noise structure in low-rank matrix estimation?
J. Barbier, T. Hou, M. Mondelli, M. Saenz, in:, 36th Annual Conference on Neural Information Processing Systems, 2022.
LibreCat: https://research-explorer.ista.ac.at/record/12536
arXiv: 2205.10009

Mean estimation in high-dimensional binary Markov Gaussian mixture models
Y. Zhang, N. Weinberger, in:, 36th Conference on Neural Information Processing Systems, ML Research Press, 2022.
LibreCat: https://research-explorer.ista.ac.at/record/17086
arXiv: 2206.02455

Mean-field analysis of piecewise linear solutions for wide ReLU networks
A. Shevchenko, V. Kungurtsev, M. Mondelli, Journal of Machine Learning Research 23 (2022) 1–55.
LibreCat: https://research-explorer.ista.ac.at/record/11420
arXiv: 2111.02278

Lower bounds on list decoding capacity using error exponents
Y. Zhang, S. Vatedka, in:, 2022 IEEE International Symposium on Information Theory, Institute of Electrical and Electronics Engineers, 2022, pp. 1324–1329.
LibreCat: https://research-explorer.ista.ac.at/record/12018
DOI: 10.1109/ISIT50566.2022.9834815

Tight bounds on the smallest eigenvalue of the neural tangent kernel for deep ReLU networks
Q. Nguyen, M. Mondelli, G.F. Montufar, in:, M. Meila, T. Zhang (Eds.), Proceedings of the 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 8119–8129.
LibreCat: https://research-explorer.ista.ac.at/record/10595
arXiv: 2012.11654

Successive syndrome-check decoding of polar codes
S.A. Hashemi, M. Mondelli, J. Cioffi, A. Goldsmith, in:, Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, Institute of Electrical and Electronics Engineers, 2021, pp. 943–947.
LibreCat: https://research-explorer.ista.ac.at/record/10599
DOI: 10.1109/IEEECONF53345.2021.9723394
arXiv: 2112.00057

Tight bounds on the smallest Eigenvalue of the neural tangent kernel for deep ReLU networks
Q. Nguyen, M. Mondelli, G. Montufar, in:, Proceedings of the 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 8119–8129.
LibreCat: https://research-explorer.ista.ac.at/record/13146
arXiv: 2012.11654

Sublinear latency for simplified successive cancellation decoding of polar codes
M. Mondelli, S.A. Hashemi, J.M. Cioffi, A. Goldsmith, IEEE Transactions on Wireless Communications 20 (2021) 18–27.
LibreCat: https://research-explorer.ista.ac.at/record/9047
DOI: 10.1109/TWC.2020.3022922
WoS: 000607808800002
arXiv: 1909.04892

Parallelism versus latency in simplified successive-cancellation decoding of polar codes
S.A. Hashemi, M. Mondelli, A. Fazeli, A. Vardy, J. Cioffi, A. Goldsmith, in:, 2021 IEEE International Symposium on Information Theory, Institute of Electrical and Electronics Engineers, 2021, pp. 2369–2374.
LibreCat: https://research-explorer.ista.ac.at/record/10053
DOI: 10.1109/ISIT45174.2021.9518153
WoS: 000701502202078
arXiv: 2012.13378

Sparse multi-decoder recursive projection aggregation for Reed-Muller codes
D. Fathollahi, N. Farsad, S.A. Hashemi, M. Mondelli, in:, 2021 IEEE International Symposium on Information Theory, Institute of Electrical and Electronics Engineers, 2021, pp. 1082–1087.
LibreCat: https://research-explorer.ista.ac.at/record/10597
DOI: 10.1109/isit45174.2021.9517887
WoS: 000701502201029
arXiv: 2011.12882

PCA initialization for approximate message passing in rotationally invariant models
M. Mondelli, R. Venkataramanan, in:, 35th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2021, pp. 29616–29629.
LibreCat: https://research-explorer.ista.ac.at/record/10593
arXiv: 2106.02356

When are solutions connected in deep networks?
Q. Nguyen, P. Bréchet, M. Mondelli, in:, 35th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/10594
arXiv: 2102.09671

Approximate message passing with spectral initialization for generalized linear models
M. Mondelli, R. Venkataramanan, in:, A. Banerjee, K. Fukumizu (Eds.), Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, ML Research Press, 2021, pp. 397–405.
LibreCat: https://research-explorer.ista.ac.at/record/10598
arXiv: 2010.03460

Binary linear codes with optimal scaling: Polar codes with large kernels
A. Fazeli, H. Hassani, M. Mondelli, A. Vardy, IEEE Transactions on Information Theory 67 (2021) 5693–5710.
LibreCat: https://research-explorer.ista.ac.at/record/9002
DOI: 10.1109/TIT.2020.3038806
arXiv: 1711.01339

Network coding with myopic adversaries
S. Li, R. Bitar, S. Jaggi, Y. Zhang, IEEE Journal on Selected Areas in Information Theory 2 (2021) 1108–1119.
LibreCat: https://research-explorer.ista.ac.at/record/15254
DOI: 10.1109/JSAIT.2021.3126474
arXiv: 2102.09885

Global convergence of deep networks with one wide layer followed by pyramidal topology
Q. Nguyen, M. Mondelli, in:, 34th Conference on Neural Information Processing Systems, Curran Associates, 2020, pp. 11961–11972.
LibreCat: https://research-explorer.ista.ac.at/record/9221
arXiv: 2002.07867

Simplified successive cancellation decoding of polar codes has sublinear latency
M. Mondelli, S.A. Hashemi, J. Cioffi, A. Goldsmith, in:, IEEE International Symposium on Information Theory - Proceedings, IEEE, 2020.
LibreCat: https://research-explorer.ista.ac.at/record/8536
DOI: 10.1109/ISIT44484.2020.9174141
arXiv: 1909.04892

Analysis of a two-layer neural network via displacement convexity
A. Javanmard, M. Mondelli, A. Montanari, Annals of Statistics 48 (2020) 3619–3642.
LibreCat: https://research-explorer.ista.ac.at/record/6748
DOI: 10.1214/20-AOS1945
WoS: 000598369200021
arXiv: 1901.01375

Landscape connectivity and dropout stability of SGD solutions for over-parameterized neural networks
A. Shevchenko, M. Mondelli, in:, Proceedings of the 37th International Conference on Machine Learning, ML Research Press, 2020, pp. 8773–8784.
LibreCat: https://research-explorer.ista.ac.at/record/9198
arXiv: 1912.10095

Rate-flexible fast polar decoders
S.A. Hashemi, C. Condo, M. Mondelli, W.J. Gross, IEEE Transactions on Signal Processing 67 (2019).
LibreCat: https://research-explorer.ista.ac.at/record/6750
DOI: 10.1109/TSP.2019.2944738
arXiv: 1903.09203

A new coding paradigm for the primitive relay channel
M. Mondelli, S.H. Hassani, R. Urbanke, Algorithms 12 (2019).
LibreCat: https://research-explorer.ista.ac.at/record/7007
DOI: 10.3390/a12100218
arXiv: 1801.03153