Local Minima Structures in Gaussian Mixture Models.
IEEE Trans. Inf. Theory, June, 2024
Improving Training Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architecture.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
Efficient Low-Dimensional Compression of Overparameterized Models.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
Sequential Community Detection in High-Dimensional Temporal Graphs.
Proceedings of the 58th Asilomar Conference on Signals, 2024
On approximations of the PSD cone by a polynomial number of smaller-sized PSD cones.
Math. Program., March, 2023
Improving Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architectures.
CoRR, 2023
Efficient Compression of Overparameterized Deep Models through Low-Dimensional Learning Dynamics.
CoRR, 2023
Algebraic and Statistical Properties of the Ordinary Least Squares Interpolator.
CoRR, 2023
Minimum-Risk Recalibration of Classifiers.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Errors-in-variables Fr\'echet Regression with Low-rank Covariate Approximation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Robustness-Preserving Lifelong Learning Via Dataset Condensation.
Proceedings of the IEEE International Conference on Acoustics, 2023
Community Detection in High-Dimensional Graph Ensembles.
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023
Addressing Missing Data and Scalable Optimization for Data-driven Decision Making.
PhD thesis, 2021
Nearest Neighbors for Matrix Estimation Interpreted as Blind Regression for Latent Variable Model.
IEEE Trans. Inf. Theory, 2020
Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Model Agnostic High-Dimensional Error-in-Variable Regression.
CoRR, 2019
On Robustness of Principal Component Regression.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Learning Mixture Model with Missing Values and its Application to Rankings.
CoRR, 2018
Blind Regression: Nonparametric Regression for Latent Variable Models via Collaborative Filtering.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016