← Authors

Mahdi Soltanolkotabi

33 papers · 2016–2025 · 9 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (8) 🌈 Renaissance Researcher (8) πŸ—ΊοΈ Taxonomy Completionist (40) πŸƒ Academic Marathon (9) 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌍 Conference Polyglot (9) πŸ† Keyword Champion (2) πŸ‘‘ Triple Crown πŸ—ƒοΈ Keyword Collector (129) ⚑ Prolific Year (5) πŸš€ Conference Pioneer πŸ’Ž Century Club (33) πŸ”₯ Unstoppable (7) ❓ The Questioner (2)

Conferences

ICML (12) NIPS (9) COLT (4) AISTATS (2) ICLR (2) CVPR (1) JMLR (1) L4DC (1) NAACL (1)

Top co-authors

Zalan Fabian (7) Samet Oymak (6) Salman Avestimehr (4) Chaoyang He (3) Reinhard Heckel (3) Dominik StΓΆger (3) Berk Tinaz (3) Hamed Hassani (3) Ilias Diakonikolas (3) Mingchen Li (2)

Research topics

Privacy (1)

Keywords

gradient descent (11) neural network (3) sample complexity (3) non-convex optimization (3) overparameterized model (2) image restoration (2) learning theory (2) low-rank matrix recovery (2) inverse problem (2) high-dimensional analysis (2) spectral method (2) transfer learning (2) federated learning (2) high-dimensional regime (2) adversarial training (2) linear regression (2) high-dimensional statistics (2) convolutional neural network (2) compressive sensing (1) catastrophic forgetting (1)

Papers

MediConfusion: Can you trust your AI radiologist? Probing the reliability of multimodal medical foundation models ICLR 2025
Test-Time Training Provably Improves Transformers as In-context Learners ICML 2025
DiracDiffusion: Denoising and Incremental Reconstruction with Assured Data-Consistency ICML 2024
Learning from many trajectories JMLR 2024
Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks ICML 2024
Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion Models ICML 2024
Implicit Balancing and Regularization: Generalization and Convergence Guarantees for Overparameterized Asymmetric Matrix Sensing COLT 2023
Learning Provably Robust Estimators for Inverse Problems via Jittering NIPS 2023
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks NIPS 2023
On the Role of Attention in Prompt-tuning ICML 2023
CUDA: Convolution-Based Unlearnable Datasets CVPR 2023
FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks NAACL 2022
Neural Networks can Learn Representations with Gradient Descent COLT 2022
HUMUS-Net: Hybrid Unrolled Multi-scale Network Architecture for Accelerated MRI Reconstruction NIPS 2022
Outlier-Robust Sparse Estimation via Non-Convex Optimization NIPS 2022
Understanding Over-parameterization in Generative Adversarial Networks ICLR 2021
Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction NIPS 2021
Data augmentation for deep learning based accelerated MRI reconstruction with limited data ICML 2021
PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models ICML 2021
Generalization Guarantees for Neural Architecture Search with Train-Validation Split ICML 2021
High-dimensional Robust Mean Estimation via Gradient Descent ICML 2020
Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximation ICML 2020
Minimax Lower Bounds for Transfer Learning with Linear and One-hidden Layer Neural Networks NIPS 2020
Learning the model-free linear quadratic regulator via random search L4DC 2020
Precise Tradeoffs in Adversarial Training for Linear Regression COLT 2020
Approximation Schemes for ReLU Regression COLT 2020
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks AISTATS 2020
Theoretical Insights Into Multiclass Classification: A High-dimensional Asymptotic View NIPS 2020
Lagrange Coded Computing: Optimal Design for Resiliency, Security, and Privacy AISTATS 2019
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path? ICML 2019
Learning ReLUs via Gradient Descent NIPS 2017
Gradient Methods for Submodular Maximization NIPS 2017
Low-rank Solutions of Linear Matrix Equations via Procrustes Flow ICML 2016