DOI,IST REx ID,Research Group,Title of publication
10.1109/isit54713.2023.10206899,14922,MaMo,Concentration without independence via information measures
10.1109/isit54713.2023.10206671,14923,MaMo,Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise
null,14924,MaMo,"Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence"
null,14459,"MaMo,DaAl","Fundamental limits of two-layer autoencoders, and achieving them with gradient methods"
10.1109/TIT.2022.3189542,11639,MaMo,List decoding random Euclidean codes and Infinite constellations
10.1109/ISIT50566.2022.9834709,12011,MaMo,The capacity of causal adversarial channels
10.1109/ISIT50566.2022.9834711,12012,MaMo,Heterogeneous differential privacy via graphs
10.1109/ISIT50566.2022.9834850,12013,MaMo,On the capacity of additive AVCs with feedback
10.1109/ISIT50566.2022.9834512,12014,MaMo,List-decodability of Poisson Point Processes
10.1109/ISIT50566.2022.9834443,12015,MaMo,Lower bounds for multiple packing
10.1109/ISIT50566.2022.9834712,12016,MaMo,Polar coded computing: The role of the scaling exponent
10.1109/ISIT50566.2022.9834632,12017,MaMo,New results on AVCs with omniscient and myopic adversaries
10.1109/ISIT50566.2022.9834815,12018,MaMo,Lower bounds on list decoding capacity using error exponents
10.1109/ISIT50566.2022.9834829,12019,MaMo,List-decodable zero-rate codes for the Z-channel
10.1109/tcomm.2022.3211101,12233,MaMo,Decoding Reed-Muller codes with successive codeword permutations
10.1109/tit.2022.3167554,12273,MaMo,Quadratically constrained myopic adversarial channels
10.1088/1742-5468/ac9828,12480,MaMo,Approximate message passing with spectral initialization for generalized linear models
null,12536,MaMo,The price of ignorance: How much does it cost to forget noise structure in low-rank matrix estimation?
null,12537,MaMo,Memorization and optimization in deep neural networks with minimum over-parameterization
10.1109/ITW54588.2022.9965870,12538,MaMo,Sharp asymptotics on the compression of two-layer neural networks