Research

2024

1. NeurIPS M3L

   Provable Weak-to-Strong Generalization via Benign Overfitting

   David X Wu, and Anant Sahai

   arXiv preprint arXiv:2410.04638 (Accepted to M3L Workshop at NeurIPS 2024), 2024

   arXiv Bib

   @article{wu2024provable,
     title = {Provable Weak-to-Strong Generalization via Benign Overfitting},
     author = {Wu, David X and Sahai, Anant},
     journal = {arXiv preprint arXiv:2410.04638 (Accepted to M3L Workshop at NeurIPS 2024)},
     year = {2024}
   }

2. Weak Poincaré Inequalities, Simulated Annealing, and Sampling from Spherical Spin Glasses

   Brice Huang, Sidhanth Mohanty, Amit Rajaraman, and David X Wu

   arXiv preprint arXiv:2411.09075, 2024

   arXiv Bib

   @article{huang2024weak,
     title = {Weak Poincar\'{e} Inequalities, Simulated Annealing, and Sampling from Spherical Spin Glasses},
     author = {Huang, Brice and Mohanty, Sidhanth and Rajaraman, Amit and Wu, David X},
     journal = {arXiv preprint arXiv:2411.09075},
     year = {2024}
   }

2024

1. FOCS

   Locally Stationary Distributions: A Framework for Analyzing Slow-Mixing Markov Chains

   Kuikui Liu^*, Sidhanth Mohanty^*, Prasad Raghavendra^*, Amit Rajaraman^*, and David X Wu^*

   IEEE Annual Symposium on Foundations of Computer Science, 2024

   arXiv Bib

   @article{liu2024locally,
     title = {Locally Stationary Distributions: A Framework for Analyzing Slow-Mixing Markov Chains},
     author = {Liu, Kuikui and Mohanty, Sidhanth and Raghavendra, Prasad and Rajaraman, Amit and Wu, David X},
     journal = {IEEE Annual Symposium on Foundations of Computer Science},
     equal_contribution = {Liu, Kuikui and Mohanty, Sidhanth and Raghavendra, Prasad and Rajaraman, Amit and Wu, David X},
     year = {2024}
   }

2. FOCS

   Fast Mixing in Sparse Random Ising Models

   Kuikui Liu^*, Sidhanth Mohanty^*, Amit Rajaraman^*, and David X Wu^*

   IEEE Annual Symposium on Foundations of Computer Science, 2024

   arXiv Bib

   @article{liu2024fast,
     title = {Fast Mixing in Sparse Random Ising Models},
     author = {Liu, Kuikui and Mohanty, Sidhanth and Rajaraman, Amit and Wu, David X},
     journal = {IEEE Annual Symposium on Foundations of Computer Science},
     equal_contribution = {Liu, Kuikui and Mohanty, Sidhanth and Rajaraman, Amit and Wu, David X},
     year = {2024}
   }

3. STOC

   Robust recovery for stochastic block models, simplified and generalized

   Sidhanth Mohanty^*, Prasad Raghavendra^*, and David X Wu^*

   ACM Symposium on Theory of Computing, 2024

   arXiv Bib

   @article{mohanty2024robust,
     title = {Robust recovery for stochastic block models, simplified and generalized},
     author = {Mohanty, Sidhanth and Raghavendra, Prasad and Wu, David X},
     journal = {ACM Symposium on Theory of Computing},
     year = {2024},
     equal_contribution = {Mohanty, Sidhanth and Raghavendra, Prasad and Wu, David X}
   }

2023

1. NeurIPS

   Precise Asymptotic Generalization for Multiclass Classification with Overparameterized Linear Models

   David X Wu^*, and Anant Sahai

   Neural Information Processing Systems, 2023

   arXiv Bib

   @article{wu2023precise,
     title = {Precise Asymptotic Generalization for Multiclass Classification with Overparameterized Linear Models},
     author = {Wu, David X and Sahai, Anant},
     journal = {Neural Information Processing Systems},
     year = {2023},
     equal_contribution = {Wu, David X}
   }

2. ICML

   On the Training Instability of Shuffling SGD with Batch Normalization

   David X Wu^*, Chulhee Yun, and Suvrit Sra

   International Conference on Machine Learning, 2023

   arXiv Bib

   @article{wu2023training,
     title = {On the Training Instability of Shuffling SGD with Batch Normalization},
     author = {Wu, David X and Yun, Chulhee and Sra, Suvrit},
     journal = {International Conference on Machine Learning},
     year = {2023},
     equal_contribution = {Wu, David X}
   }

3. ISIT

   Lower Bounds for Multiclass Classification with Overparameterized Linear Models

   David X Wu^*, and Anant Sahai

   International Symposium on Information Theory, 2023

2022

1. SIOPT

   Maximum A Posteriori Inference of Random Dot Product Graphs via Conic Programming

   David X Wu^*, David Palmer, and Daryl R DeFord

   SIAM Journal on Optimization, 2022

   arXiv Bib

   @article{wu2022maximum,
     title = {Maximum A Posteriori Inference of Random Dot Product Graphs via Conic Programming},
     author = {Wu, David X and Palmer, David and DeFord, Daryl R},
     journal = {SIAM Journal on Optimization},
     volume = {32},
     number = {4},
     pages = {2527--2551},
     year = {2022},
     publisher = {SIAM},
     equal_contribution = {Wu, David X}
   }