Marco Mondelli

1. Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks
   2020/12/21 by Quynh Nguyen, Marco Mondelli, Nguyen, Quynh +3 · 6 citations
   Computer Science · Engineering · #Stochastic Gradient Optimization Techniques #Sparse and Compressive Sensing Techniques #Machine Learning and ELM
2. Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model
   2023/05/22 by Peter Súkeník, Marco Mondelli, Súkeník, Peter +3 · 7 citations
   Computer Science · #Advanced Neural Network Applications #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM
3. Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization
   2022/05/20 by Simone Bombari, Bombari, Simone, Mohammad Hossein Amani +3 · 5 citations
   Computer Science · Engineering · #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
4. High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws
   2024/10/24 by M. Emrullah Ildiz, Ildiz, M. Emrullah, Halil Alperen Gozeten +7 · 8 citations
   Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
5. Improved Convergence of Score-Based Diffusion Models via Prediction-Correction
   2023/05/23 by Francesco Pedrotti, Jan Maas, Pedrotti, Francesco +3 · 3 citations
   Computer Science · Mathematics · #Generative Adversarial Networks and Image Synthesis #Gaussian Processes and Bayesian Inference #Markov Chains and Monte Carlo Methods
6. Approximate Message Passing with Spectral Initialization for Generalized\n Linear Models
   2020/10/07 by Marco Mondelli, Ramji Venkataramanan, Mondelli, Marco +1 · 2 citations
   Engineering · Computer Science · Mathematics · #Sparse and Compressive Sensing Techniques #Gaussian Processes and Bayesian Inference #Statistical and numerical algorithms
7. Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization
   2025/02/03 by Simone Bombari, Marco Mondelli, Bombari, Simone +1 · 5 citations
   Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Inference
8. Reed-Muller Codes Achieve Capacity on Erasure Channels
   2016/01/18 by Shrinivas Kudekar, Santhosh Kumar, Kudekar, Shrinivas +9 · 1 voice
   Computer Science · #Coding theory and cryptography #Cooperative Communication and Network Coding #Error Correcting Code Techniques #cs.IT
9. Optimal Combination of Linear and Spectral Estimators for Generalized\n Linear Models
   2020/08/07 by Marco Mondelli, Christos Thrampoulidis, Mondelli, Marco +3 · 1 citation
   Computer Science · Engineering · #Blind Source Separation Techniques #Distributed Sensor Networks and Detection Algorithms #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Statistics Theory (math.ST)
10. Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing
    2021/12/08 by Ramji Venkataramanan, Kevin Kögler, Venkataramanan, Ramji +3 · 1 citation
    Computer Science · #Blind Source Separation Techniques #Distributed Sensor Networks and Detection Algorithms #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST) #Target Tracking and Data Fusion in Sensor Networks
11. Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks
    2021/11/03 by Alexander P. Shevchenko, Shevchenko, Alexander, Vyacheslav Kungurtsev +3 · 1 citation
    Computer Science · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Stochastic Gradient Optimization Techniques
12. Finite Sample Identification of Wide Shallow Neural Networks with Biases
    2022/11/08 by Massimo Fornasier, Timo Klock, Fornasier, Massimo +5 · 1 citation
    Computer Science · Physics and Astronomy · #65D15 #68T07 #90C26 #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Model Reduction and Neural Networks #Stochastic Gradient Optimization Techniques
13. Neural Collapse is Globally Optimal in Deep Regularized ResNets and Transformers
    2025/05/21 by Peter Súkeník, Christoph H. Lampert, Súkeník, Peter +3 · 3 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
14. Neural Collapse Beyond the Unconstrained Features Model: Landscape, Dynamics, and Generalization in the Mean-Field Regime
    2025/01/31 by Diyuan Wu, Marco Mondelli, Wu, Diyuan +1 · 2 citations
    Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural Networks and Applications
15. Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods
    2024/05/22 by Yihan Zhang, Marco Mondelli, Zhang, Yihan +1 · 1 citation
    Computer Science · Engineering · Mathematics · #Elasticity and Wave Propagation #FOS: Computer and information sciences #FOS: Mathematics #Image and Signal Denoising Methods #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Numerical methods in inverse problems #Probability (math.PR) #Statistics Theory (math.ST)