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ORCIDMahdi Soltanolkotabi
Mehdi Soltanolkotabi
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- affiliation: University of Southern California, USA
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2020 – today
- 2024
[j12]Stephen Tu, Roy Frostig, Mahdi Soltanolkotabi:
Learning from many trajectories. J. Mach. Learn. Res. 25: 216:1-216:109 (2024)- [c45]Liam Collins, Hamed Hassani, Mahdi Soltanolkotabi, Aryan Mokhtari, Sanjay Shakkottai:
Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks. ICML 2024 - [c44]Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi:
Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion Models. ICML 2024 - [c43]Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi:
DiracDiffusion: Denoising and Incremental Reconstruction with Assured Data-Consistency. ICML 2024 - [i68]Mohammad Shahab Sepehri, Zalan Fabian, Mahdi Soltanolkotabi:
Serpent: Scalable and Efficient Image Restoration via Multi-scale Structured State Space Models. CoRR abs/2403.17902 (2024) - [i67]Mohammadamin Banayeeanzade, Mahdi Soltanolkotabi, Mohammad Rostami:
Theoretical Insights into Overparameterized Models in Multi-Task and Replay-Based Continual Learning. CoRR abs/2408.16939 (2024) - [i66]Mohammad Shahab Sepehri, Zalan Fabian, Maryam Soltanolkotabi, Mahdi Soltanolkotabi:
MediConfusion: Can you trust your AI radiologist? Probing the reliability of multimodal medical foundation models. CoRR abs/2409.15477 (2024) - 2023
- [j11]Yue Niu, Zalan Fabian, Sunwoo Lee, Mahdi Soltanolkotabi, Salman Avestimehr:
mL-BFGS: A Momentum-based L-BFGS for Distributed Large-scale Neural Network Optimization. Trans. Mach. Learn. Res. 2023 (2023) - [c42]Mahdi Soltanolkotabi
, Dominik Stöger, Changzhi Xie:
Implicit Balancing and Regularization: Generalization and Convergence Guarantees for Overparameterized Asymmetric Matrix Sensing. COLT 2023: 5140-5142 - [c41]Vinu Sankar Sadasivan, Mahdi Soltanolkotabi, Soheil Feizi:
CUDA: Convolution-Based Unlearnable Datasets. CVPR 2023: 3862-3871 - [c40]Samet Oymak, Ankit Singh Rawat, Mahdi Soltanolkotabi, Christos Thrampoulidis:
On the Role of Attention in Prompt-tuning. ICML 2023: 26724-26768 - [c39]Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr:
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks. NeurIPS 2023 - [c38]Anselm Krainovic, Mahdi Soltanolkotabi, Reinhard Heckel:
Learning Provably Robust Estimators for Inverse Problems via Jittering. NeurIPS 2023 - [i65]Vinu Sankar Sadasivan, Mahdi Soltanolkotabi, Soheil Feizi:
CUDA: Convolution-based Unlearnable Datasets. CoRR abs/2303.04278 (2023) - [i64]Mahdi Soltanolkotabi, Dominik Stöger, Changzhi Xie:
Implicit Balancing and Regularization: Generalization and Convergence Guarantees for Overparameterized Asymmetric Matrix Sensing. CoRR abs/2303.14244 (2023) - [i63]Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi:
DiracDiffusion: Denoising and Incremental Reconstruction with Assured Data-Consistency. CoRR abs/2303.14353 (2023) - [i62]Samet Oymak, Ankit Singh Rawat, Mahdi Soltanolkotabi, Christos Thrampoulidis:
On the Role of Attention in Prompt-tuning. CoRR abs/2306.03435 (2023) - [i61]Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr:
Don't Memorize; Mimic The Past: Federated Class Incremental Learning Without Episodic Memory. CoRR abs/2307.00497 (2023) - [i60]Liam Collins, Hamed Hassani, Mahdi Soltanolkotabi, Aryan Mokhtari, Sanjay Shakkottai:
Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks. CoRR abs/2307.06887 (2023) - [i59]Anselm Krainovic, Mahdi Soltanolkotabi, Reinhard Heckel:
Learning Provably Robust Estimators for Inverse Problems via Jittering. CoRR abs/2307.12822 (2023) - [i58]Yue Niu, Zalan Fabian, Sunwoo Lee, Mahdi Soltanolkotabi, Salman Avestimehr:
mL-BFGS: A Momentum-based L-BFGS for Distributed Large-Scale Neural Network Optimization. CoRR abs/2307.13744 (2023) - [i57]Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi:
Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion Models. CoRR abs/2309.06642 (2023) - [i56]Omar Zamzam, Haleh Akrami, Mahdi Soltanolkotabi, Richard M. Leahy:
Learning A Disentangling Representation For PU Learning. CoRR abs/2310.03833 (2023) - [i55]Sara Fridovich-Keil, Fabrizio Valdivia, Gordon Wetzstein, Benjamin Recht, Mahdi Soltanolkotabi:
Gradient Descent Provably Solves Nonlinear Tomographic Reconstruction. CoRR abs/2310.03956 (2023) - [i54]Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr:
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks. CoRR abs/2311.07784 (2023) - 2022
- [j10]Hesameddin Mohammadi, Armin Zare, Mahdi Soltanolkotabi, Mihailo R. Jovanovic:
Convergence and Sample Complexity of Gradient Methods for the Model-Free Linear-Quadratic Regulator Problem. IEEE Trans. Autom. Control. 67(5): 2435-2450 (2022) - [c37]Alexandru Damian, Jason D. Lee, Mahdi Soltanolkotabi:
Neural Networks can Learn Representations with Gradient Descent. COLT 2022: 5413-5452 - [c36]Xiaoyi Mai, Salman Avestimehr, Antonio Ortega, Mahdi Soltanolkotabi:
On The Effectiveness of Active Learning by Uncertainty Sampling in Classification of High-Dimensional Gaussian Mixture Data. ICASSP 2022: 4238-4242 - [c35]Seyed Mohammadreza Mousavi Kalan, Mahdi Soltanolkotabi, Amir Salman Avestimehr:
Statistical Minimax Lower Bounds for Transfer Learning in Linear Binary Classification. ISIT 2022: 282-287 - [c34]Bill Yuchen Lin, Chaoyang He, Zihang Ze, Hulin Wang, Yufen Hua, Christophe Dupuy, Rahul Gupta, Mahdi Soltanolkotabi, Xiang Ren, Salman Avestimehr:
FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks. NAACL-HLT (Findings) 2022: 157-175 - [c33]Yu Cheng, Ilias Diakonikolas, Rong Ge, Shivam Gupta, Daniel Kane, Mahdi Soltanolkotabi:
Outlier-Robust Sparse Estimation via Non-Convex Optimization. NeurIPS 2022 - [c32]Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi:
HUMUS-Net: Hybrid Unrolled Multi-scale Network Architecture for Accelerated MRI Reconstruction. NeurIPS 2022 - [i53]Zalan Fabian, Mahdi Soltanolkotabi:
HUMUS-Net: Hybrid unrolled multi-scale network architecture for accelerated MRI reconstruction. CoRR abs/2203.08213 (2022) - [i52]Stephen Tu, Roy Frostig, Mahdi Soltanolkotabi:
Learning from many trajectories. CoRR abs/2203.17193 (2022) - [i51]Romain Cosentino, Anirvan M. Sengupta, Salman Avestimehr, Mahdi Soltanolkotabi, Antonio Ortega, Theodore L. Willke, Mariano Tepper:
Toward a Geometrical Understanding of Self-supervised Contrastive Learning. CoRR abs/2205.06926 (2022) - [i50]Alex Damian, Jason D. Lee, Mahdi Soltanolkotabi:
Neural Networks can Learn Representations with Gradient Descent. CoRR abs/2206.15144 (2022) - [i49]Romain Cosentino, Sarath Shekkizhar, Mahdi Soltanolkotabi, Salman Avestimehr, Antonio Ortega:
The Geometry of Self-supervised Learning Models and its Impact on Transfer Learning. CoRR abs/2209.08622 (2022) - [i48]Chaoyang He, Shuai Zheng, Aston Zhang, George Karypis, Trishul Chilimbi, Mahdi Soltanolkotabi, Salman Avestimehr:
SMILE: Scaling Mixture-of-Experts with Efficient Bi-level Routing. CoRR abs/2212.05191 (2022) - 2021
- [j9]Hesameddin Mohammadi, Mahdi Soltanolkotabi, Mihailo R. Jovanovic:
On the Linear Convergence of Random Search for Discrete-Time LQR. IEEE Control. Syst. Lett. 5(3): 989-994 (2021) - [c31]Hesameddin Mohammadi, Mahdi Soltanolkotabi, Mihailo R. Jovanovic:
On the lack of gradient domination for linear quadratic Gaussian problems with incomplete state information. CDC 2021: 1120-1124 - [c30]Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi:
Understanding Over-parameterization in Generative Adversarial Networks. ICLR 2021 - [c29]Zalan Fabian, Reinhard Heckel, Mahdi Soltanolkotabi:
Data augmentation for deep learning based accelerated MRI reconstruction with limited data. ICML 2021: 3057-3067 - [c28]Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr:
PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models. ICML 2021: 4150-4159 - [c27]Samet Oymak, Mingchen Li, Mahdi Soltanolkotabi:
Generalization Guarantees for Neural Architecture Search with Train-Validation Split. ICML 2021: 8291-8301 - [c26]Dominik Stöger, Mahdi Soltanolkotabi:
Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction. NeurIPS 2021: 23831-23843 - [i47]Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr:
PipeTransformer: Automated Elastic Pipelining for Distributed Training of Transformers. CoRR abs/2102.03161 (2021) - [i46]Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi:
Understanding Overparameterization in Generative Adversarial Networks. CoRR abs/2104.05605 (2021) - [i45]Bill Yuchen Lin, Chaoyang He, Zihang Zeng, Hulin Wang, Yufen Huang, Mahdi Soltanolkotabi, Xiang Ren, Salman Avestimehr:
FedNLP: A Research Platform for Federated Learning in Natural Language Processing. CoRR abs/2104.08815 (2021) - [i44]Samet Oymak, Mingchen Li, Mahdi Soltanolkotabi:
Generalization Guarantees for Neural Architecture Search with Train-Validation Split. CoRR abs/2104.14132 (2021) - [i43]Zalan Fabian, Reinhard Heckel, Mahdi Soltanolkotabi:
Data augmentation for deep learning based accelerated MRI reconstruction with limited data. CoRR abs/2106.14947 (2021) - [i42]Dominik Stöger, Mahdi Soltanolkotabi:
Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction. CoRR abs/2106.15013 (2021) - [i41]Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horváth, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu:
A Field Guide to Federated Optimization. CoRR abs/2107.06917 (2021) - [i40]Yu Cheng, Ilias Diakonikolas, Daniel M. Kane, Rong Ge, Shivam Gupta, Mahdi Soltanolkotabi:
Outlier-Robust Sparse Estimation via Non-Convex Optimization. CoRR abs/2109.11515 (2021) - [i39]Chaoyang He, Zhengyu Yang, Erum Mushtaq, Sunwoo Lee, Mahdi Soltanolkotabi, Salman Avestimehr:
SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision. CoRR abs/2110.02470 (2021) - [i38]Chaoyang He, Alay Dilipbhai Shah, Zhenheng Tang, Di Fan, Adarshan Naiynar Sivashunmugam, Keerti Bhogaraju, Mita Shimpi, Li Shen, Xiaowen Chu, Mahdi Soltanolkotabi, Salman Avestimehr:
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks. CoRR abs/2111.11066 (2021) - 2020
- [j8]Samet Oymak, Mahdi Soltanolkotabi:
Toward Moderate Overparameterization: Global Convergence Guarantees for Training Shallow Neural Networks. IEEE J. Sel. Areas Inf. Theory 1(1): 84-105 (2020) - [c25]Mingchen Li, Mahdi Soltanolkotabi, Samet Oymak:
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks. AISTATS 2020: 4313-4324 - [c24]Hesameddin Mohammadi, Mahdi Soltanolkotabi, Mihailo R. Jovanovic:
Random search for learning the linear quadratic regulator. ACC 2020: 4798-4803 - [c23]Ilias Diakonikolas, Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans, Mahdi Soltanolkotabi:
Approximation Schemes for ReLU Regression. COLT 2020: 1452-1485 - [c22]Adel Javanmard, Mahdi Soltanolkotabi, Hamed Hassani:
Precise Tradeoffs in Adversarial Training for Linear Regression. COLT 2020: 2034-2078 - [c21]Zalan Fabian, Justin P. Haldar, Richard M. Leahy, Mahdi Soltanolkotabi:
3D Phase Retrieval at Nano-Scale via Accelerated Wirtinger Flow. EUSIPCO 2020: 2080-2084 - [c20]Reinhard Heckel, Mahdi Soltanolkotabi:
Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators. ICLR 2020 - [c19]Yu Cheng, Ilias Diakonikolas, Rong Ge, Mahdi Soltanolkotabi:
High-dimensional Robust Mean Estimation via Gradient Descent. ICML 2020: 1768-1778 - [c18]Reinhard Heckel, Mahdi Soltanolkotabi:
Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximation. ICML 2020: 4149-4158 - [c17]Hesameddin Mohammadi, Mihailo R. Jovanovic, Mahdi Soltanolkotabi:
Learning the model-free linear quadratic regulator via random search. L4DC 2020: 531-539 - [c16]Seyed Mohammadreza Mousavi Kalan, Zalan Fabian, Salman Avestimehr, Mahdi Soltanolkotabi:
Minimax Lower Bounds for Transfer Learning with Linear and One-hidden Layer Neural Networks. NeurIPS 2020 - [c15]Christos Thrampoulidis, Samet Oymak, Mahdi Soltanolkotabi:
Theoretical Insights Into Multiclass Classification: A High-dimensional Asymptotic View. NeurIPS 2020 - [i37]Adel Javanmard, Mahdi Soltanolkotabi, Hamed Hassani:
Precise Tradeoffs in Adversarial Training for Linear Regression. CoRR abs/2002.10477 (2020) - [i36]Zalan Fabian, Justin P. Haldar, Richard M. Leahy, Mahdi Soltanolkotabi:
3D Phase Retrieval at Nano-Scale via Accelerated Wirtinger Flow. CoRR abs/2002.11785 (2020) - [i35]Yu Cheng, Ilias Diakonikolas, Rong Ge, Mahdi Soltanolkotabi:
High-Dimensional Robust Mean Estimation via Gradient Descent. CoRR abs/2005.01378 (2020) - [i34]Reinhard Heckel, Mahdi Soltanolkotabi:
Compressive sensing with un-trained neural networks: Gradient descent finds the smoothest approximation. CoRR abs/2005.03991 (2020) - [i33]Ilias Diakonikolas, Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans, Mahdi Soltanolkotabi:
Approximation Schemes for ReLU Regression. CoRR abs/2005.12844 (2020) - [i32]Seyed Mohammadreza Mousavi Kalan, Zalan Fabian, Amir Salman Avestimehr, Mahdi Soltanolkotabi:
Minimax Lower Bounds for Transfer Learning with Linear and One-hidden Layer Neural Networks. CoRR abs/2006.10581 (2020) - [i31]Adel Javanmard, Mahdi Soltanolkotabi:
Precise Statistical Analysis of Classification Accuracies for Adversarial Training. CoRR abs/2010.11213 (2020) - [i30]Christos Thrampoulidis, Samet Oymak, Mahdi Soltanolkotabi:
Theoretical Insights Into Multiclass Classification: A High-dimensional Asymptotic View. CoRR abs/2011.07729 (2020)
2010 – 2019
- 2019
- [j7]Mahdi Soltanolkotabi, Adel Javanmard, Jason D. Lee:
Theoretical Insights Into the Optimization Landscape of Over-Parameterized Shallow Neural Networks. IEEE Trans. Inf. Theory 65(2): 742-769 (2019) - [j6]Mahdi Soltanolkotabi:
Structured Signal Recovery From Quadratic Measurements: Breaking Sample Complexity Barriers via Nonconvex Optimization. IEEE Trans. Inf. Theory 65(4): 2374-2400 (2019) - [c14]Samet Oymak, Zalan Fabian, Mingchen Li, Mahdi Soltanolkotabi:
Generalization, Adaptation and Low-Rank Representation in Neural Networks. ACSSC 2019: 581-585 - [c13]Qian Yu, Songze Li, Netanel Raviv, Seyed Mohammadreza Mousavi Kalan, Mahdi Soltanolkotabi, Amir Salman Avestimehr:
Lagrange Coded Computing: Optimal Design for Resiliency, Security, and Privacy. AISTATS 2019: 1215-1225 - [c12]Hesameddin Mohammadi, Armin Zare, Mahdi Soltanolkotabi, Mihailo R. Jovanovic:
Global exponential convergence of gradient methods over the nonconvex landscape of the linear quadratic regulator. CDC 2019: 7474-7479 - [c11]Samet Oymak, Mahdi Soltanolkotabi:
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path? ICML 2019: 4951-4960 - [c10]Seyed Mohammadreza Mousavi Kalan, Mahdi Soltanolkotabi, Amir Salman Avestimehr:
Fitting ReLUs via SGD and Quantized SGD. ISIT 2019: 2469-2473 - [i29]Seyed Mohammadreza Mousavi Kalan, Mahdi Soltanolkotabi, Amir Salman Avestimehr:
Fitting ReLUs via SGD and Quantized SGD. CoRR abs/1901.06587 (2019) - [i28]Samet Oymak, Mahdi Soltanolkotabi:
Towards moderate overparameterization: global convergence guarantees for training shallow neural networks. CoRR abs/1902.04674 (2019) - [i27]Mingchen Li, Mahdi Soltanolkotabi, Samet Oymak:
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks. CoRR abs/1903.11680 (2019) - [i26]Samet Oymak, Zalan Fabian, Mingchen Li, Mahdi Soltanolkotabi:
Generalization Guarantees for Neural Networks via Harnessing the Low-rank Structure of the Jacobian. CoRR abs/1906.05392 (2019) - [i25]Reinhard Heckel, Mahdi Soltanolkotabi:
Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators. CoRR abs/1910.14634 (2019) - [i24]Hesameddin Mohammadi, Armin Zare, Mahdi Soltanolkotabi, Mihailo R. Jovanovic:
Convergence and sample complexity of gradient methods for the model-free linear quadratic regulator problem. CoRR abs/1912.11899 (2019) - 2018
- [j5]Reinhard Heckel, Mahdi Soltanolkotabi:
Generalized Line Spectral Estimation via Convex Optimization. IEEE Trans. Inf. Theory 64(6): 4001-4023 (2018) - [j4]Samet Oymak, Benjamin Recht, Mahdi Soltanolkotabi:
Sharp Time-Data Tradeoffs for Linear Inverse Problems. IEEE Trans. Inf. Theory 64(6): 4129-4158 (2018) - [c9]Emrah Bostan, Mahdi Soltanolkotabi, David Ren, Laura Waller:
Accelerated Wirtinger Flow for Multiplexed Fourier Ptychographic Microscopy. ICIP 2018: 3823-3827 - [c8]Songze Li, Seyed Mohammadreza Mousavi Kalan, Amir Salman Avestimehr, Mahdi Soltanolkotabi:
Near-Optimal Straggler Mitigation for Distributed Gradient Methods. IPDPS Workshops 2018: 857-866 - [i23]Amir Salman Avestimehr, Seyed Mohammadreza Mousavi Kalan, Mahdi Soltanolkotabi:
Fundamental Resource Trade-offs for Encoded Distributed Optimization. CoRR abs/1804.00217 (2018) - [i22]Samet Oymak, Mahdi Soltanolkotabi:
End-to-end Learning of a Convolutional Neural Network via Deep Tensor Decomposition. CoRR abs/1805.06523 (2018) - [i21]Songze Li, Seyed Mohammadreza Mousavi Kalan, Qian Yu, Mahdi Soltanolkotabi, Amir Salman Avestimehr:
Polynomially Coded Regression: Optimal Straggler Mitigation via Data Encoding. CoRR abs/1805.09934 (2018) - [i20]Samet Oymak, Mahdi Soltanolkotabi:
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path? CoRR abs/1812.10004 (2018) - 2017
- [j3]Samet Oymak, Mahdi Soltanolkotabi:
Fast and Reliable Parameter Estimation from Nonlinear Observations. SIAM J. Optim. 27(4): 2276-2300 (2017) - [c7]Mahdi Soltanolkotabi:
Learning ReLUs via Gradient Descent. NIPS 2017: 2007-2017 - [c6]S. Hamed Hassani, Mahdi Soltanolkotabi, Amin Karbasi:
Gradient Methods for Submodular Maximization. NIPS 2017: 5841-5851 - [i19]Mahdi Soltanolkotabi:
Structured signal recovery from quadratic measurements: Breaking sample complexity barriers via nonconvex optimization. CoRR abs/1702.06175 (2017) - [i18]Mahdi Soltanolkotabi:
Learning ReLUs via Gradient Descent. CoRR abs/1705.04591 (2017) - [i17]Mahdi Soltanolkotabi, Adel Javanmard, Jason D. Lee:
Theoretical insights into the optimization landscape of over-parameterized shallow neural networks. CoRR abs/1707.04926 (2017) - [i16]S. Hamed Hassani, Mahdi Soltanolkotabi, Amin Karbasi:
Gradient Methods for Submodular Maximization. CoRR abs/1708.03949 (2017) - [i15]Songze Li, Seyed Mohammadreza Mousavi Kalan, Amir Salman Avestimehr, Mahdi Soltanolkotabi:
Near-Optimal Straggler Mitigation for Distributed Gradient Methods. CoRR abs/1710.09990 (2017) - 2016
- [c5]Stephen Tu, Ross Boczar, Max Simchowitz, Mahdi Soltanolkotabi, Ben Recht:
Low-rank Solutions of Linear Matrix Equations via Procrustes Flow. ICML 2016: 964-973 - [i14]Reinhard Heckel, Mahdi Soltanolkotabi:
Generalized Line Spectral Estimation via Convex Optimization. CoRR abs/1609.08198 (2016) - [i13]Samet Oymak, Mahdi Soltanolkotabi:
Fast and Reliable Parameter Estimation from Nonlinear Observations. CoRR abs/1610.07108 (2016) - 2015
- [j2]Emmanuel J. Candès, Xiaodong Li, Mahdi Soltanolkotabi:
Phase Retrieval via Wirtinger Flow: Theory and Algorithms. IEEE Trans. Inf. Theory 61(4): 1985-2007 (2015) - [i12]Samet Oymak, Benjamin Recht, Mahdi Soltanolkotabi:
Isometric sketching of any set via the Restricted Isometry Property. CoRR abs/1506.03521 (2015) - [i11]Samet Oymak, Benjamin Recht, Mahdi Soltanolkotabi:
Sharp Time-Data Tradeoffs for Linear Inverse Problems. CoRR abs/1507.04793 (2015) - [i10]Li-Hao Yeh, Jonathan Dong, Jingshan Zhong, Lei Tian, Michael Chen, Gongguo Tang, Mahdi Soltanolkotabi, Laura Waller:
Experimental robustness of Fourier Ptychography phase retrieval algorithms. CoRR abs/1511.02986 (2015) - 2014
- [i9]Emmanuel J. Candès, Xiaodong Li, Mahdi Soltanolkotabi:
Phase Retrieval via Wirtinger Flow: Theory and Algorithms. CoRR abs/1407.1065 (2014) - [i8]Reinhard Heckel, Veniamin I. Morgenshtern, Mahdi Soltanolkotabi:
Super-Resolution Radar. CoRR abs/1411.6272 (2014) - 2013
- [i7]Mahdi Soltanolkotabi, Ehsan Elhamifar, Emmanuel J. Candès:
Robust Subspace Clustering. CoRR abs/1301.2603 (2013) - [i6]Emmanuel J. Candès, Xiaodong Li, Mahdi Soltanolkotabi:
Phase Retrieval from masked Fourier transforms. CoRR abs/1310.3240 (2013) - 2012
- [j1]Farokh Marvasti, Arash Amini, Farzan Haddadi, Mehdi Soltanolkotabi, Babak Hossein Khalaj, Akram Aldroubi, Saeid Sanei, Jonathon A. Chambers:
A unified approach to sparse signal processing. EURASIP J. Adv. Signal Process. 2012: 44 (2012) - [i5]Emmanuel J. Candès, Mahdi Soltanolkotabi:
Discussion: Latent variable graphical model selection via convex optimization. CoRR abs/1211.0817 (2012) - 2011
- [i4]Mahdi Soltanolkotabi, Emmanuel J. Candès:
A Geometric Analysis of Subspace Clustering with Outliers. CoRR abs/1112.4258 (2011)
2000 – 2009
- 2009
- [c4]Mahdi Soltanolkotabi, Arash Amini, Farokh Marvasti:
OFDM channel estimation based on Adaptive Thresholding for Sparse Signal Detection. EUSIPCO 2009: 1685-1689 - [c3]Pedram Pad, Mahdi Soltanolkotabi, Saeed Hadikhanlou, Arash Enayati, Farrokh Marvasti:
Errorless Codes for Over-Loaded CDMA with Active User Detection. ICC 2009: 1-6 - [c2]Mahdi Soltanolkotabi, Mojtaba Soltanalian, Arash Amini, Farokh Marvasti:
A practical sparse channel estimation for current OFDM standards. ICT 2009: 217-222 - [i3]Mahdi Soltanolkotabi, Arash Amini, Farrokh Marvasti:
OFDM Channel Estimation Based on Adaptive Thresholding for Sparse Signal Detection. CoRR abs/0901.3948 (2009) - [i2]Farrokh Marvasti, Arash Amini, Farzan Haddadi, Mahdi Soltanolkotabi, Babak Hossein Khalaj, Akram Aldroubi, Sverre Holm, Saeid Sanei, Jonathon A. Chambers:
A Unified Approach to Sparse Signal Processing. CoRR abs/0902.1853 (2009) - 2008
- [c1]Soheil Feizi, Sina Zahedpour, Mahdi Soltanolkotabi, Arash Amini, Farokh Marvasti:
Salt and pepper noise removal for image signals. ICT 2008: 1-5 - [i1]Pedram Pad, Mahdi Soltanolkotabi, Saeed Hadikhanlou, Arash Enayati, Farrokh Marvasti:
Errorless Codes for Over-loaded CDMA with Active User Detection. CoRR abs/0810.0763 (2008)
Coauthor Index
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Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-17 20:32 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
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since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
