← Authors

Marco Mondelli

29 papers · 2018–2025 · 6 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (13) 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) πŸƒ Academic Marathon (7) 🐝 Cross-Pollinator (11) πŸ† Keyword Champion (2) ⚑ Prolific Year (8) πŸ—ƒοΈ Keyword Collector (94) πŸ”₯ Unstoppable (8) ❓ The Questioner (3) πŸ’Ž Century Club (29)

Conferences

ICML (11) NIPS (9) COLT (4) AISTATS (2) ICLR (2) JMLR (1)

Top co-authors

Simone Bombari (5) Peter SΓΊkenΓ­k (4) Ramji Venkataramanan (4) Kevin KΓΆgler (3) Quynh N Nguyen (2) Muhammed Emrullah Ildiz (2) Halil Alperen Gozeten (2) Andrea Montanari (2) Hamed Hassani (2) Aleksandr Shevchenko (2)

Keywords

gradient descent (7) approximate message passing (6) deep neural network (4) spectral method (3) generalized linear model (3) stochastic gradient descent (3) neural tangent kernel (3) asymptotic analysis (2) neural network optimization (2) eigenvalue bound (2) feature learning (2) neural collapse (2) dropout stability (2) representation learning (2) signal estimation (2) rotational invariance (2) high-dimensional statistics (1) neural network theory (1) binary classification (1) loss landscape (1)

Papers

High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws ICLR 2025
Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization ICML 2025
Test-Time Training Provably Improves Transformers as In-context Learners ICML 2025
Spectral Estimators for Multi-Index Models: Precise Asymptotics and Optimal Weak Recovery COLT 2025
Wide Neural Networks Trained with Weight Decay Provably Exhibit Neural Collapse ICLR 2025
Neural Collapse Beyond the Unconstrained Features Model: Landscape, Dynamics, and Generalization in the Mean-Field Regime ICML 2025
Contraction of Markovian Operators in Orlicz Spaces and Error Bounds for Markov Chain Monte Carlo (Extended Abstract) COLT 2024
Spectral Estimators for Structured Generalized Linear Models via Approximate Message Passing (Extended Abstract) COLT 2024
Neural collapse vs. low-rank bias: Is deep neural collapse really optimal? NIPS 2024
Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods NIPS 2024
Average gradient outer product as a mechanism for deep neural collapse NIPS 2024
How Spurious Features are Memorized: Precise Analysis for Random and NTK Features ICML 2024
Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth ICML 2024
Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features ICML 2024
Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model NIPS 2023
Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels ICML 2023
Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods ICML 2023
Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks JMLR 2022
Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization NIPS 2022
The price of ignorance: how much does it cost to forget noise structure in low-rank matrix estimation? NIPS 2022
Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing ICML 2022
When Are Solutions Connected in Deep Networks? NIPS 2021
PCA Initialization for Approximate Message Passing in Rotationally Invariant Models NIPS 2021
Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks ICML 2021
Approximate Message Passing with Spectral Initialization for Generalized Linear Models AISTATS 2021
Global Convergence of Deep Networks with One Wide Layer Followed by Pyramidal Topology NIPS 2020
Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks ICML 2020
On the Connection Between Learning Two-Layer Neural Networks and Tensor Decomposition AISTATS 2019
Fundamental Limits of Weak Recovery with Applications to Phase Retrieval COLT 2018