Publications

Publications by categories in reverse chronological order.

Preprints

• High-dimensional sequential change detection
  Robert Malinas, Dogyoon Song, Benjamin D. Robinson and Alfred O. Hero
  arXiv preprint (v1, February 2025)

• Algebraic and statistical properties of the ordinary least squares interpolator
  Dennis Shen, Dogyoon Song, Peng Ding and Jasjeet Sekhon arXiv preprint (v2, May 2024)

• Community detection in high-dimensional graph ensembles
  Robert Malinas, Dogyoon Song, Alfred O. Hero
  arXiv preprint (v1, December 2023); presented at the Asilomar Conference 2023

• On separability of covariance in multiway data analysis
  Dogyoon Song and Alfred O. Hero
  arXiv preprint (v2, October 2023)

• Deconvolution with unknown error distribution interpreted as blind isotonic regression
  Devavrat Shah and Dogyoon Song
  arXiv preprint (v3, April 2020); presented at the Allerton Conference 2018

• Learning RUMs: Reducing mixture to single component via PCA
  Devavrat Shah and Dogyoon Song
  arXiv preprint (v3, March 2020)

Journal Articles

• Local minima structures in Gaussian mixture models
  Yudong Chen, Dogyoon Song, Xumei Xi and Yuqian Zhang
  IEEE Transactions on Information Theory, 2024

• On approximations of the PSD cone by a polynomial number of smaller-sized PSD cones
  Dogyoon Song and Pablo A. Parrilo
  Mathematical Programming, 2023

• Kronecker-structured covariance models for multiway data
  Yu Wang, Zeyu Sun, Dogyoon Song and Alfred O. Hero
  Statistics Surveys, 2022

• On robustness of principal component regression
  Anish Agarwal, Devavrat Shah, Dennis Shen and Dogyoon Song
  Journal of the American Statistical Association (JASA), 2021; Preliminary version presented at NeurIPS 2019

• Nearest neighbors for matrix estimation interpreted as blind regression for latent variable model
  Yihua Li, Devavrat Shah, Dogyoon Song and Christina Lee Yu
  IEEE Transactions on Information Theory, 2019; Preliminary version presented at NeurIPS 2016

Conference Proceedings

• Improving training efficiency of diffusion models via multi-stage framework and tailored multi-decoder architecture
  Huijie Zhang, Yifu Lu, Ismail Alkhouri, Saiprasad Ravishankar, Dogyoon Song and Qing Qu
  CVPR 2024

• Efficient low-dimensional compression of overparameterized models
  Soo Min Kwon, Zekai Zhang, Dogyoon Song, Laura Balzano and Qing Qu
  AISTATS 2024

• Errors-in-variables Fréchet regression with low-rank covariate approximation
  Dogyoon Song and Kyunghee Han
  NeurIPS 2023

• Minimum-risk recalibration of classifiers
  Zeyu Sun, Dogyoon Song and Alfred O. Hero
  NeurIPS 2023 (spotlight)

• Robustness-preserving lifelong learning via dataset condensation
  Jinghan Jia, Yihua Zhang, Dogyoon Song, Sijia Liu and Alfred O. Hero
  ICASSP 2023

• Sample-efficient reinforcement learning via low-rank matrix estimation
  Devavrat Shah, Dogyoon Song, Zhi Xu and Yuzhe Yang
  NeurIPS 2020

• On robustness of principal component regression
  Anish Agarwal, Devavrat Shah, Dennis Shen and Dogyoon Song
  NeurIPS 2019 (oral)

• Blind regression: Nonparametric regression for latent variable models via collaborative filtering
  Christina Lee, Yihua Li, Devavrat Shah and Dogyoon Song
  NeurIPS 2016

• Verifying start-up failures in coupled ring oscillators in presence of variability using predictive global optimization
  Taehwan Kim, Dogyoon Song, Sangho Youn, Jaejin Park, Hojin Park and Jaeha Kim
  IEEE/ACM ICCAD 2013

• Discretization and discrimination methods for design, verification, and testing of analog/mixed-signal circuits
  Jaeha Kim, Jiho Lee, Dogyoon Song, Taehwan Kim, Kyunghoon Kim, Seobin Jung and Sangho Youn
  IEEE CICC 2013

• A low-power high-radix switch fabric based on low-swing signaling and partially-activated input lines
  Dogyoon Song and Jaeha Kim
  VLSI-DAT 2013

Ph.D. Thesis

• Addressing missing data and scalable optimization for data-driven decision making
  Ph.D. Thesis, Massachusetts Institute of Technology, June 2021
  Advised by Pablo A. Parrilo and Devavrat Shah