Marco Mondelli

152 papers A* 27A 2B 19Misc 2Journal 97Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Theory of How Pretraining Shapes Inductive Bias in Fine-Tuning. CoRR Nicolas Anguita, Francesco Locatello, Andrew M. Saxe, Marco Mondelli, Flavia Mancini, Samuel Lippl, Clémentine C. J. Dominé
2026	J	`jnl`	Full-Batch Gradient Descent Outperforms One-Pass SGD: Sample Complexity Separation in Single-Index Learning. CoRR Filip Kovacevic, Hong Chang Ji, Denny Wu, Mahdi Soltanolkotabi, Marco Mondelli
2026	J	`jnl`	Improved Scaling Laws via Weak-to-Strong Generalization in Random Feature Ridge Regression. CoRR Diyuan Wu, Lehan Chen, Theodor Misiakiewicz, Marco Mondelli
2026	J	`jnl`	Optimal Estimation in Orthogonally Invariant Generalized Linear Models: Spectral Initialization and Approximate Message Passing. CoRR Yihan Zhang, Hong Chang Ji, Ramji Venkataramanan, Marco Mondelli
2025	J	`jnl`	A Law of Data Reconstruction for Random Features (and Beyond). CoRR Leonardo Iurada, Simone Bombari, Tatiana Tommasi, Marco Mondelli
2025	J	`jnl`	Attention with Trained Embeddings Provably Selects Important Tokens. CoRR Diyuan Wu, Aleksandr Shevchenko, Samet Oymak, Marco Mondelli
2025	J	`jnl`	Better Rates for Private Linear Regression in the Proportional Regime via Aggressive Clipping. CoRR Simone Bombari, Inbar Seroussi, Marco Mondelli
2025	A*	`conf`	High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws. ICLR Muhammed Emrullah Ildiz, Halil Alperen Gozeten, Ege Onur Taga, Marco Mondelli, Samet Oymak
2025	J	`jnl`	High-dimensional Analysis of Synthetic Data Selection. CoRR Parham Rezaei, Filip Kovacevic, Francesco Locatello, Marco Mondelli
2025	A*	`conf`	Neural Collapse Beyond the Unconstrained Features Model: Landscape, Dynamics, and Generalization in the Mean-Field Regime. ICML Diyuan Wu, Marco Mondelli
2025	J	`jnl`	Neural Collapse Beyond the Unconstrainted Features Model: Landscape, Dynamics, and Generalization in the Mean-Field Regime. CoRR Diyuan Wu, Marco Mondelli
2025	J	`jnl`	Neural Collapse is Globally Optimal in Deep Regularized ResNets and Transformers. CoRR Peter Súkeník, Christoph H. Lampert, Marco Mondelli
2025	J	`jnl`	Optimal Regularization for Performative Learning. CoRR Edwige Cyffers, Alireza Mirrokni, Marco Mondelli
2025	A*	`conf`	Spectral Estimators for Multi-Index Models: Precise Asymptotics and Optimal Weak Recovery. COLT Filip Kovacevic, Yihan Zhang, Marco Mondelli
2025	J	`jnl`	Spectral Estimators for Multi-Index Models: Precise Asymptotics and Optimal Weak Recovery. CoRR Filip Kovacevic, Yihan Zhang, Marco Mondelli
2025	A*	`conf`	Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization. ICML Simone Bombari, Marco Mondelli
2025	J	`jnl`	Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization. CoRR Simone Bombari, Marco Mondelli
2025	A*	`conf`	Test-Time Training Provably Improves Transformers as In-context Learners. ICML Halil Alperen Gozeten, Muhammed Emrullah Ildiz, Xuechen Zhang, Mahdi Soltanolkotabi, Marco Mondelli, Samet Oymak
2025	J	`jnl`	Test-Time Training Provably Improves Transformers as In-context Learners. CoRR Halil Alperen Gozeten, Muhammed Emrullah Ildiz, Xuechen Zhang, Mahdi Soltanolkotabi, Marco Mondelli, Samet Oymak
2025	A*	`conf`	Wide Neural Networks Trained with Weight Decay Provably Exhibit Neural Collapse. ICLR Arthur Jacot, Peter Súkeník, Zihan Wang, Marco Mondelli
2024	A*	`conf`	Average gradient outer product as a mechanism for deep neural collapse. NeurIPS Daniel Beaglehole, Peter Súkeník, Marco Mondelli, Mikhail Belkin
2024	J	`jnl`	Average gradient outer product as a mechanism for deep neural collapse. CoRR Daniel Beaglehole, Peter Súkeník, Marco Mondelli, Mikhail Belkin
2024	A*	`conf`	Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth. ICML Kevin Kögler, Aleksandr Shevchenko, Hamed Hassani, Marco Mondelli
2024	J	`jnl`	Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth. CoRR Kevin Kögler, Alexander Shevchenko, Hamed Hassani, Marco Mondelli
2024	J	`jnl`	Concentration Without Independence via Information Measures. IEEE Trans. Inf. Theory Amedeo Roberto Esposito, Marco Mondelli
2024	A*	`conf`	Contraction of Markovian Operators in Orlicz Spaces and Error Bounds for Markov Chain Monte Carlo (Extended Abstract). COLT Amedeo Roberto Esposito, Marco Mondelli
2024	J	`jnl`	Contraction of Markovian Operators in Orlicz Spaces and Error Bounds for Markov Chain Monte Carlo. CoRR Amedeo Roberto Esposito, Marco Mondelli
2024	J	`jnl`	High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws. CoRR Muhammed Emrullah Ildiz, Halil Alperen Gozeten, Ege Onur Taga, Marco Mondelli, Samet Oymak
2024	A*	`conf`	How Spurious Features are Memorized: Precise Analysis for Random and NTK Features. ICML Simone Bombari, Marco Mondelli
2024	J	`jnl`	Improved Convergence of Score-Based Diffusion Models via Prediction-Correction. Trans. Mach. Learn. Res. Francesco Pedrotti, Jan Maas, Marco Mondelli
2024	Misc	`conf`	Inference of Genetic Effects via Approximate Message Passing. ICASSP Al Depope, Marco Mondelli, Matthew R. Robinson
2024	J	`jnl`	Information limits and Thouless-Anderson-Palmer equations for spiked matrix models with structured noise. CoRR Jean Barbier, Francesco Camilli, Marco Mondelli, Yizhou Xu
2024	A*	`conf`	Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods. NeurIPS Yihan Zhang, Marco Mondelli
2024	J	`jnl`	Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods. CoRR Yihan Zhang, Marco Mondelli
2024	J	`jnl`	Neural Collapse versus Low-rank Bias: Is Deep Neural Collapse Really Optimal? CoRR Peter Súkeník, Marco Mondelli, Christoph Lampert
2024	A*	`conf`	Neural collapse vs. low-rank bias: Is deep neural collapse really optimal? NeurIPS Peter Súkeník, Christoph H. Lampert, Marco Mondelli
2024	J	`jnl`	Privacy for Free in the Over-Parameterized Regime. CoRR Simone Bombari, Marco Mondelli
2024	A*	`conf`	Spectral Estimators for Structured Generalized Linear Models via Approximate Message Passing (Extended Abstract). COLT Yihan Zhang, Hong Chang Ji, Ramji Venkataramanan, Marco Mondelli
2024	A*	`conf`	Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features. ICML Simone Bombari, Marco Mondelli
2024	J	`jnl`	Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features. CoRR Simone Bombari, Marco Mondelli
2024	J	`jnl`	Wide Neural Networks Trained with Weight Decay Provably Exhibit Neural Collapse. CoRR Arthur Jacot, Peter Súkeník, Zihan Wang, Marco Mondelli
2023	B	`conf`	Approximate Message Passing for Multi-Layer Estimation in Rotationally Invariant Models. ITW Yizhou Xu, Tianqi Hou, Shansuo Liang, Marco Mondelli
2023	A*	`conf`	Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels. ICML Simone Bombari, Shayan Kiyani, Marco Mondelli
2023	J	`jnl`	Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels. CoRR Simone Bombari, Shayan Kiyani, Marco Mondelli
2023	B	`conf`	Concentration without Independence via Information Measures. ISIT Amedeo Roberto Esposito, Marco Mondelli
2023	J	`jnl`	Concentration without Independence via Information Measures. CoRR Amedeo Roberto Esposito, Marco Mondelli
2023	A*	`conf`	Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model. NeurIPS Peter Súkeník, Marco Mondelli, Christoph H. Lampert
2023	J	`jnl`	Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model. CoRR Peter Súkeník, Marco Mondelli, Christoph Lampert
2023	A*	`conf`	Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods. ICML Aleksandr Shevchenko, Kevin Kögler, Hamed Hassani, Marco Mondelli
2023	J	`jnl`	Improved Convergence of Score-Based Diffusion Models via Prediction-Correction. CoRR Francesco Pedrotti, Jan Maas, Marco Mondelli
2023	J	`jnl`	Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence. Trans. Mach. Learn. Res. Diyuan Wu, Vyacheslav Kungurtsev, Marco Mondelli
2023	B	`conf`	Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise. ISIT Teng Fu, Yuhao Liu, Jean Barbier, Marco Mondelli, Shansuo Liang, Tianqi Hou
2023	J	`jnl`	Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise. CoRR Teng Fu, Yuhao Liu, Jean Barbier, Marco Mondelli, Shansuo Liang, Tianqi Hou
2023	J	`jnl`	Spectral Estimators for Structured Generalized Linear Models via Approximate Message Passing. CoRR Yihan Zhang, Hong Chang Ji, Ramji Venkataramanan, Marco Mondelli
2023	J	`jnl`	Stability, Generalization and Privacy: Precise Analysis for Random and NTK Features. CoRR Simone Bombari, Marco Mondelli
2022	J	`jnl`	Approximate Message Passing for Multi-Layer Estimation in Rotationally Invariant Models. CoRR Yizhou Xu, Tianqi Hou, Shansuo Liang, Marco Mondelli
2022	J	`jnl`	Bayes-optimal limits in structured PCA, and how to reach them. CoRR Jean Barbier, Francesco Camilli, Marco Mondelli, Manuel Sáenz
2022	J	`jnl`	Decoding Reed-Muller Codes With Successive Codeword Permutations. IEEE Trans. Commun. Nghia Doan, Seyyed Ali Hashemi, Marco Mondelli, Warren J. Gross
2022	A*	`conf`	Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing. ICML Ramji Venkataramanan, Kevin Kögler, Marco Mondelli
2022	J	`jnl`	Finite Sample Identification of Wide Shallow Neural Networks with Biases. CoRR Massimo Fornasier, Timo Klock, Marco Mondelli, Michael Rauchensteiner
2022	J	`jnl`	Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods. CoRR Alexander Shevchenko, Kevin Kögler, Hamed Hassani, Marco Mondelli
2022	J	`jnl`	Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks. J. Mach. Learn. Res. Alexander Shevchenko, Vyacheslav Kungurtsev, Marco Mondelli
2022	J	`jnl`	Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence. CoRR Diyuan Wu, Vyacheslav Kungurtsev, Marco Mondelli
2022	A*	`conf`	Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization. NeurIPS Simone Bombari, Mohammad Hossein Amani, Marco Mondelli
2022	J	`jnl`	Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization. CoRR Simone Bombari, Mohammad Hossein Amani, Marco Mondelli
2022	J	`jnl`	Optimal Combination of Linear and Spectral Estimators for Generalized Linear Models. Found. Comput. Math. Marco Mondelli, Christos Thrampoulidis, Ramji Venkataramanan
2022	J	`jnl`	Parallelism Versus Latency in Simplified Successive-Cancellation Decoding of Polar Codes. IEEE Trans. Wirel. Commun. Seyyed Ali Hashemi, Marco Mondelli, Arman Fazeli, Alexander Vardy, John M. Cioffi, Andrea Goldsmith
2022	B	`conf`	Polar Coded Computing: The Role of the Scaling Exponent. ISIT Dorsa Fathollahi, Marco Mondelli
2022	J	`jnl`	Polar Coded Computing: The Role of the Scaling Exponent. CoRR Dorsa Fathollahi, Marco Mondelli
2022	J	`jnl`	Precise Asymptotics for Spectral Methods in Mixed Generalized Linear Models. CoRR Yihan Zhang, Marco Mondelli, Ramji Venkataramanan
2022	B	`conf`	Sharp asymptotics on the compression of two-layer neural networks. ITW Mohammad Hossein Amani, Simone Bombari, Marco Mondelli, Rattana Pukdee, Stefano Rini
2022	J	`jnl`	Sharp asymptotics on the compression of two-layer neural networks. CoRR Mohammad Hossein Amani, Simone Bombari, Marco Mondelli, Rattana Pukdee, Stefano Rini
2022	A*	`conf`	The price of ignorance: how much does it cost to forget noise structure in low-rank matrix estimation? NeurIPS Jean Barbier, Tianqi Hou, Marco Mondelli, Manuel Sáenz
2022	J	`jnl`	The price of ignorance: how much does it cost to forget noise structure in low-rank matrix estimation? CoRR Jean Barbier, Tianqi Hou, Marco Mondelli, Manuel Sáenz
2021	A	`conf`	Approximate Message Passing with Spectral Initialization for Generalized Linear Models. AISTATS Marco Mondelli, Ramji Venkataramanan
2021	J	`jnl`	Binary Linear Codes With Optimal Scaling: Polar Codes With Large Kernels. IEEE Trans. Inf. Theory Arman Fazeli, Hamed Hassani, Marco Mondelli, Alexander Vardy
2021	J	`jnl`	Decoding Reed-Muller Codes with Successive Factor-Graph Permutations. CoRR Nghia Doan, Seyyed Ali Hashemi, Marco Mondelli, Warren J. Gross
2021	J	`jnl`	Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing. CoRR Ramji Venkataramanan, Kevin Kögler, Marco Mondelli
2021	J	`jnl`	Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks. CoRR Alexander Shevchenko, Vyacheslav Kungurtsev, Marco Mondelli
2021	J	`jnl`	On Connectivity of Solutions in Deep Learning: The Role of Over-parameterization and Feature Quality. CoRR Quynh Nguyen, Pierre Bréchet, Marco Mondelli
2021	A*	`conf`	PCA Initialization for Approximate Message Passing in Rotationally Invariant Models. NeurIPS Marco Mondelli, Ramji Venkataramanan
2021	J	`jnl`	PCA Initialization for Approximate Message Passing in Rotationally Invariant Models. CoRR Marco Mondelli, Ramji Venkataramanan
2021	B	`conf`	Parallelism versus Latency in Simplified Successive-Cancellation Decoding of Polar Codes. ISIT Seyyed Ali Hashemi, Marco Mondelli, Arman Fazeli, Alexander Vardy, John M. Cioffi, Andrea Goldsmith
2021	B	`conf`	Sparse Multi-Decoder Recursive Projection Aggregation for Reed-Muller Codes. ISIT Dorsa Fathollahi, Nariman Farsad, Seyyed Ali Hashemi, Marco Mondelli
2021	J	`jnl`	Sublinear Latency for Simplified Successive Cancellation Decoding of Polar Codes. IEEE Trans. Wirel. Commun. Marco Mondelli, Seyyed Ali Hashemi, John M. Cioffi, Andrea Goldsmith
2021	—	`conf`	Successive Syndrome-Check Decoding of Polar Codes. ACSCC Seyyed Ali Hashemi, Marco Mondelli, John M. Cioffi, Andrea Goldsmith
2021	J	`jnl`	Successive Syndrome-Check Decoding of Polar Codes. CoRR Seyyed Ali Hashemi, Marco Mondelli, John M. Cioffi, Andrea Goldsmith
2021	A*	`conf`	Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks. ICML Quynh Nguyen, Marco Mondelli, Guido F. Montúfar
2021	A*	`conf`	When Are Solutions Connected in Deep Networks? NeurIPS Quynh Nguyen, Pierre Bréchet, Marco Mondelli
2020	J	`jnl`	Approximate Message Passing with Spectral Initialization for Generalized Linear Models. CoRR Marco Mondelli, Ramji Venkataramanan
2020	A*	`conf`	Global Convergence of Deep Networks with One Wide Layer Followed by Pyramidal Topology. NeurIPS Quynh Nguyen, Marco Mondelli
2020	J	`jnl`	Global Convergence of Deep Networks with One Wide Layer Followed by Pyramidal Topology. CoRR Quynh Nguyen, Marco Mondelli
2020	A*	`conf`	Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks. ICML Alexander Shevchenko, Marco Mondelli
2020	J	`jnl`	Optimal Combination of Linear and Spectral Estimators for Generalized Linear Models. CoRR Marco Mondelli, Christos Thrampoulidis, Ramji Venkataramanan
2020	J	`jnl`	Parallelism versus Latency in Simplified Successive-Cancellation Decoding of Polar Codes. CoRR Seyyed Ali Hashemi, Marco Mondelli, Arman Fazeli, Alexander Vardy, John M. Cioffi, Andrea Goldsmith
2020	B	`conf`	Simplified Successive Cancellation Decoding of Polar Codes Has Sublinear Latency. ISIT Marco Mondelli, Seyyed Ali Hashemi, John M. Cioffi, Andrea Goldsmith
2020	J	`jnl`	Sparse Multi-Decoder Recursive Projection Aggregation for Reed-Muller Codes. CoRR Dorsa Fathollahi, Nariman Farsad, Seyyed Ali Hashemi, Marco Mondelli
2020	J	`jnl`	Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks. CoRR Quynh Nguyen, Marco Mondelli, Guido Montúfar
2019	J	`jnl`	A New Coding Paradigm for the Primitive Relay Channel. Algorithms Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke
2019	J	`jnl`	Analysis of a Two-Layer Neural Network via Displacement Convexity. CoRR Adel Javanmard, Marco Mondelli, Andrea Montanari
2019	J	`jnl`	Construction of Polar Codes With Sublinear Complexity. IEEE Trans. Inf. Theory Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke
2019	J	`jnl`	Fundamental Limits of Weak Recovery with Applications to Phase Retrieval. Found. Comput. Math. Marco Mondelli, Andrea Montanari
2019	J	`jnl`	Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks. CoRR Alexander Shevchenko, Marco Mondelli
2019	A	`conf`	On the Connection Between Learning Two-Layer Neural Networks and Tensor Decomposition. AISTATS Marco Mondelli, Andrea Montanari
2019	B	`conf`	Rate-Flexible Fast Polar Decoders. ITW Seyyed Ali Hashemi, Carlo Condo, Marco Mondelli, Warren J. Gross
2019	J	`jnl`	Rate-Flexible Fast Polar Decoders. CoRR Seyyed Ali Hashemi, Carlo Condo, Marco Mondelli, Warren J. Gross
2019	J	`jnl`	Rate-Flexible Fast Polar Decoders. IEEE Trans. Signal Process. Seyyed Ali Hashemi, Carlo Condo, Marco Mondelli, Warren J. Gross
2019	J	`jnl`	Sublinear Latency for Simplified Successive Cancellation Decoding of Polar Codes. CoRR Marco Mondelli, Seyyed Ali Hashemi, John M. Cioffi, Andrea Goldsmith
2018	B	`conf`	A New Coding Paradigm for the Primitive Relay Channel. ISIT Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke
2018	J	`jnl`	A New Coding Paradigm for the Primitive Relay Channel. CoRR Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke
2018	B	`conf`	Binary Linear Codes with Optimal Scaling: Polar Codes with Large Kernels. ITW Arman Fazeli, S. Hamed Hassani, Marco Mondelli, Alexander Vardy
2018	J	`jnl`	Decoder Partitioning: Towards Practical List Decoding of Polar Codes. IEEE Trans. Commun. Seyyed Ali Hashemi, Marco Mondelli, S. Hamed Hassani, Carlo Condo, Rüdiger L. Urbanke, Warren J. Gross
2018	—	`conf`	Decoding Reed-Muller and Polar Codes by Successive Factor Graph Permutations. ISTC Seyyed Ali Hashemi, Nghia Doan, Marco Mondelli, Warren J. Gross
2018	J	`jnl`	Decoding Reed-Muller and Polar Codes by Successive Factor Graph Permutations. CoRR Seyyed Ali Hashemi, Nghia Doan, Marco Mondelli, Warren J. Gross
2018	A*	`conf`	Fundamental Limits of Weak Recovery with Applications to Phase Retrieval. COLT Marco Mondelli, Andrea Montanari
2018	J	`jnl`	How to Achieve the Capacity of Asymmetric Channels. IEEE Trans. Inf. Theory Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke
2018	J	`jnl`	On the Connection Between Learning Two-Layers Neural Networks and Tensor Decomposition. CoRR Marco Mondelli, Andrea Montanari
2018	B	`conf`	On the Decoding of Polar Codes on Permuted Factor Graphs. GLOBECOM Nghia Doan, Seyyed Ali Hashemi, Marco Mondelli, Warren J. Gross
2018	J	`jnl`	On the Decoding of Polar Codes on Permuted Factor Graphs. CoRR Nghia Doan, Seyyed Ali Hashemi, Marco Mondelli, Warren J. Gross
2017	J	`jnl`	Binary Linear Codes with Optimal Scaling and Quasi-Linear Complexity. CoRR Arman Fazeli, S. Hamed Hassani, Marco Mondelli, Alexander Vardy
2017	—	`conf`	Capacity-Achieving Rate-Compatible Polar Codes for General Channels. WCNC Workshops Marco Mondelli, S. Hamed Hassani, Ivana Maric, Dennis Hui, Song-Nam Hong
2017	B	`conf`	Construction of polar codes with sublinear complexity. ISIT Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke
2017	J	`jnl`	Fundamental Limits of Weak Recovery with Applications to Phase Retrieval. CoRR Marco Mondelli, Andrea Montanari
2017	B	`conf`	Partitioned List Decoding of Polar Codes: Analysis and Improvement of Finite Length Performance. GLOBECOM Seyyed Ali Hashemi, Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke, Warren J. Gross
2017	J	`jnl`	Partitioned List Decoding of Polar Codes: Analysis and Improvement of Finite Length Performance. CoRR Seyyed Ali Hashemi, Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke, Warren J. Gross
2017	J	`jnl`	Reed-Muller Codes Achieve Capacity on Erasure Channels. IEEE Trans. Inf. Theory Shrinivas Kudekar, Santhosh Kumar, Marco Mondelli, Henry D. Pfister, Eren Sasoglu, Rüdiger L. Urbanke
2016	J	`jnl`	Capacity-Achieving Rate-Compatible Polar Codes for General Channels. CoRR Marco Mondelli, S. Hamed Hassani, Ivana Maric, Dennis Hui, Song-Nam Hong
2016	J	`jnl`	Comparing the Bit-MAP and Block-MAP Decoding Thresholds of Reed-Muller Codes on BMS Channels. CoRR Shrinivas Kudekar, Santhosh Kumar, Marco Mondelli, Henry D. Pfister, Rüdiger L. Urbanke
2016	B	`conf`	Comparing the bit-MAP and block-MAP decoding thresholds of reed-muller codes on BMS channels. ISIT Shrinivas Kudekar, Santhosh Kumar, Marco Mondelli, Henry D. Pfister, Rüdiger L. Urbanke
2016	J	`jnl`	Construction of Polar Codes with Sublinear Complexity. CoRR Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke
2016	—	`—`	From Polar to Reed-Muller Codes - Unified Scaling, Non-standard Channels, and a Proven Conjecture. Marco Mondelli
2016	J	`jnl`	Reed-Muller Codes Achieve Capacity on Erasure Channels. CoRR Shrinivas Kudekar, Santhosh Kumar, Marco Mondelli, Henry D. Pfister, Eren Sasoglu, Rüdiger L. Urbanke
2016	A*	`conf`	Reed-Muller codes achieve capacity on erasure channels. STOC Shrinivas Kudekar, Santhosh Kumar, Marco Mondelli, Henry D. Pfister, Eren Sasoglu, Rüdiger L. Urbanke
2016	J	`jnl`	Unified Scaling of Polar Codes: Error Exponent, Scaling Exponent, Moderate Deviations, and Error Floors. IEEE Trans. Inf. Theory Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke
2015	J	`jnl`	Achieving Marton's Region for Broadcast Channels Using Polar Codes. IEEE Trans. Inf. Theory Marco Mondelli, Seyed Hamed Hassani, Igal Sason, Rüdiger L. Urbanke
2015	J	`jnl`	Reed-Muller Codes Achieve Capacity on the Binary Erasure Channel under MAP Decoding. CoRR Shrinivas Kudekar, Marco Mondelli, Eren Sasoglu, Rüdiger L. Urbanke
2015	J	`jnl`	Scaling Exponent of List Decoders With Applications to Polar Codes. IEEE Trans. Inf. Theory Marco Mondelli, Seyed Hamed Hassani, Rüdiger L. Urbanke
2015	J	`jnl`	Unified Scaling of Polar Codes: Error Exponent, Scaling Exponent, Moderate Deviations, and Error Floors. CoRR Marco Mondelli, Seyed Hamed Hassani, Rüdiger L. Urbanke
2015	B	`conf`	Unified scaling of polar codes: Error exponent, scaling exponent, moderate deviations, and error floors. ISIT Marco Mondelli, Rüdiger L. Urbanke, Seyed Hamed Hassani
2014	B	`conf`	Achieving Marton's region for broadcast channels using polar codes. ISIT Marco Mondelli, Seyed Hamed Hassani, Rüdiger L. Urbanke, Igal Sason
2014	J	`jnl`	Achieving the Superposition and Binning Regions for Broadcast Channels Using Polar Codes. CoRR Marco Mondelli, Seyed Hamed Hassani, Igal Sason, Rüdiger L. Urbanke
2014	J	`jnl`	From Polar to Reed-Muller Codes: A Technique to Improve the Finite-Length Performance. IEEE Trans. Commun. Marco Mondelli, Seyed Hamed Hassani, Rüdiger L. Urbanke
2014	J	`jnl`	From Polar to Reed-Muller Codes: a Technique to Improve the Finite-Length Performance. CoRR Marco Mondelli, Seyed Hamed Hassani, Rüdiger L. Urbanke
2014	B	`conf`	From polar to Reed-Muller codes: A technique to improve the finite-length performance. ISIT Marco Mondelli, Seyed Hamed Hassani, Rüdiger L. Urbanke
2014	J	`jnl`	How to Achieve the Capacity of Asymmetric Channels. CoRR Marco Mondelli, Seyed Hamed Hassani, Rüdiger L. Urbanke
2014	—	`conf`	How to achieve the capacity of asymmetric channels. Allerton Marco Mondelli, Rüdiger L. Urbanke, Seyed Hamed Hassani
2014	J	`jnl`	Joint Power Allocation and Path Selection for Multi-Hop Noncoherent Decode and Forward UWB Communications. IEEE Trans. Wirel. Commun. Marco Mondelli, Qi Zhou, Vincenzo Lottici, Xiaoli Ma
2013	J	`jnl`	A Finite Difference Scheme for the Stack Filter Simulating the MCM. Image Process. Line Marco Mondelli
2013	J	`jnl`	Scaling Exponent of List Decoders with Applications to Polar Codes CoRR Marco Mondelli, Seyed Hamed Hassani, Rüdiger L. Urbanke
2013	B	`conf`	Scaling exponent of list decoders with applications to polar codes. ITW Marco Mondelli, Seyed Hamed Hassani, Rüdiger L. Urbanke
2012	Misc	`conf`	A cooperative approach for amplify-and-forward differential transmitted reference IR-UWB relay systems. ICASSP Marco Mondelli, Qi Zhou, Xiaoli Ma, Vincenzo Lottici
2011	J	`jnl`	Finite Difference Schemes for MCM and AMSS. Image Process. Line Marco Mondelli, Adina Ciomaga