2022
![]() N. Konstantinov, C. H. Lampert. Fairness-Aware PAC Learning from Corrupted Data. JMLR 23 (2022) 1-60 | ![]() B. Prach, C. H. Lampert. Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks. ECCV 2022 | M. Mondelli, and R. Venkataramanan, “Approximate Message Passing with Spectral Initialization for Generalized Linear Models”,STAT 2022 | A. Shevchenko, V. Kungurtsev, and M. Mondelli, “Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks”, JMLR 2022 |
| Paper | Paper | Paper | Paper |
| | Project |
R. Venkataramanan, K. Kögler, and M. Mondelli, “Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing”, ICML 2022 | D. Fathollahi and M. Mondelli, “Polar Coded Computing: The Role of the Scaling Exponent”, ISIT 2022 | ||
| Paper | Paper | ||
2021
![]() AC/DC: ALTERNATING COMPRESSED/DECOMPRESSED TRAINING OF DEEP NEURAL NETWORKS NeurIPS 2021 Peste, Iofinova, Vladu, Alistarh | NeurIPS 2021 Alimisis, Davies, Vandereycken, Alistarh | WHEN ARE SOLUTIONS CONNECTED IN DEEP NETWORKS? NeurIPS 2021 Nguyen Bréchet Mondelli | M-FAC: EFFICIENT MATRIX-FREE APPROXIMATIONS OF SECOND-ORDER INFORMATION NeurIPS 2021 Frantar Kurtic Alistarh |
| Project Paper | Project Paper | Project Paper | |
ICLR 2021 Phuong, Lampert | BYZANTINE-RESILIENT NON-CONVEX STOCHASTIC GRADIENT DESCENTICLR 2021 Allen-Zhu, Ebrahimian, Li, Alistarh | TOWARDS TIGHT COMMUNICATION LOWER BOUNDS FOR DISTRIBUTED OPTIMIZATIONNeurIPS 2021 Korhonen Alistarh | NeurIPS 2021 Nadiradze, Sabour, Davies, Li, Alistarh |
| Project Paper | Project Paper | Project Paper | Project Paper |
NeurIPS 2021 Mondelli, Venkataramanan | AISTATS 2021 Mondelli, Venkataramanan | TIGHT BOUNDS ON THE SMALLEST EIGENVALUE OF THE NEURAL TANGENT KERNEL FOR DEEP RELU NETWORKS ICML 2021 Nguyen, Mondelli, Montufar | ![]() ONE-SIDED FRANK-WOLFE ALGORITHMS FOR SADDLE PROBLEMS ICML 2021 Kolmogorov, Pock |
| Paper | Paper | Paper | Paper |
ICML 2021 Alimisis, Davies, Alistarh | ![]() GENOMIC ARCHITECTURE AND PREDICTION OF CENSORED TIME-TO-EVENT PHENOTYPES WITH A BAYESIAN GENOME-WIDE ANALYSIS Nature Communications Ojavee, Robinson | PARALLELISM VERSUS LATENCY IN SIMPLIFIED SUCCESSIVE-CANCELLATION DECODING OF POLAR CODES ISIT 2021 Hashemi, Mondelli, Fazeli, Vardy, Cioffi, Goldsmith | ISIT 2021 Fathollahi, Farsad, Hashemi, Mondelli |
| Project Paper | Project Paper | Paper | Paper |
NEW BOUNDS FOR DISTRIBUTED MEAN ESTIMATION AND VARIANCE REDUCTIONICLR 2021 Davies, Gurunanthan, Moshrefi, Ashkboos, Alistarh Project Paper Foundations of Computational Mathematics Mondelli, Thrampoulidis Venkataramanan Paper | ELASTIC CONSISTENCY: A PRACTICAL CONSISTENCY MODEL FOR DISTRIBUTED STOCHASTIC GRADIENT DESCENTAAAI 2021 Nadiradze, Markov, Chatterjee, Kungurtsev, Alistarh Project Paper | JMLR Hoefler, Alistarh, Ben-Nun, Dryden, Peste Project Paper | IEEE Transactions on Wireless Communications Mondelli, Hashemi, Cioffi, Goldsmith Paper |
2020
NeurIPS 2020 Nguyen, Mondelli Paper | WOODFISHER: EFFICIENT SECOND-ORDER APPROXIMATION FOR NEURAL NETWORK COMPRESSIONNeurIPS 2020 Singh, Alistarh Project Paper | RELAXED SCHEDULING FOR SCALABLE BELIEF PROPAGATIONNeurIPS 2020 Aksenov, Alistarh Project Paper | NeurIPS 2020 Henderson, Lampert Project Paper |
ACM Transactions on Graphics 39(6) (SIGGRAPH Asia 2020) Gavriil, Guseinov, Pérez, Pellis Henderson, Rist, Pottmann, Bickel Paper | IEEE Transactions on Information Theory Fazeli, Hassani, Mondelli, Vardy Paper | DOES SGD IMPLICITLY OPTIMIZE FOR SMOOTHNESS? GCPR 2020 Volhejn, Lampert Paper | ICML 2020 Shevchenko, Mondelli Paper |
ON THE SAMPLE COMPLEXITY OF ADVERSARIAL MULTI-SOURCE PAC LEARNING ICML 2020 Konstantinov, Frantar, Alistarh, Lampert Paper | PROBABILISTIC INFERENCE OF THE GENETIC ARCHITECTURE OF FUNCTIONAL ENRICHMENT OF COMPLEX TRAITSmedRxiv Patxot, Robinson Project Paper | BAYESIAN REASSESSMENT OF THE EPIGENETIC ARCHITECTURE OF COMPLEX TRAITSNature Communications Trejo Banos, Robinson Paper | ICLR 2020 Phuong, Lampert Paper |
WACV 2020 Royer, Lampert Project Paper | Annals of Statistics Javanmard, Mondelli, Montanari Paper | WACV 2020 Royer, Lampert Project Paper | |
| 2019 | |||
IEEE Transactions on Signal Processing Hashemi, Condo, Mondelli, Gross Paper | ICCV 2019 Phuong, Lampert Paper | IJCV Sun, Lampert Project Paper | FUNCTION NORMS FOR NEURAL NETWORKSWorkshop on Statistical Deep Learning in Computer Vision at ICCV 2019 Triki, Berman, Kolmogorov, Blaschko Paper |
![]() TESTING THE COMPLEXITY OF A VALUED CSP LANGUAGE ICALP 2019 Kolmogorov Project Paper | ICML 2019 Phuong, Lampert Paper | ICML 2019 Konstantinov, Lampert Project Paper | MAP INFERENCE VIA BLOCK-COORDINATE FRANK-WOLFE ALGORITHMCVPR 2019 Swoboda, Kolmogorov Project Paper |
ON THE CONNECTION BETWEEN LEARNING TWO-LAYERS NEURAL NETWORKS AND TENSOR DECOMPOSITION AISTATS 2019 Mondelli, Montanari Paper |


