Publications

2019

• Provable Non-linear Inductive Matrix Completion
  K. Zhong, Z. Song, P. Jain, I. Dhillon.
  To appear in Neural Information Processing Systems (NIPS), 2019.

2017

• Recovery Guarantees for One-hidden-layer Neural Networks (pdf, arXiv)
  K. Zhong, Z. Song, P. Jain, P. Bartlett, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 4140-4149, August 2017. (Oral)
• Fast Classification with Binary Prototypes (pdf)
  K. Zhong, R. Guo, S. Kumar, B. Yan, D. Simcha, I. Dhillon.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), 2017.

2016

• Coordinate-wise Power Method (pdf, code)
  Q. Lei, K. Zhong, I. Dhillon.
  To appear in Neural Information Processing Systems (NIPS), December 2016.
• Dual Decomposed Learning with Factorwise Oracle for Structural SVM with Large Output Domain (pdf)
  I. Yen, X. Huang, K. Zhong, R. Zhang, P. Ravikumar, I. Dhillon.
  In Neural Information Processing Systems (NIPS), December 2016.
• Mixed Linear Regression with Multiple Components (pdf)
  K. Zhong, P. Jain, I. Dhillon.
  In Neural Information Processing Systems (NIPS), December 2016.
• Efficient and Non-Convex Coordinate Descent for Symmetric Nonnegative Matrix Factorization (pdf, code)
  A. Vandaele, N. Gillis, Q. Lei, K. Zhong, I. Dhillon.
  IEEE Transactions on Signal Processing 64(21), pp. 5571 – 5584, 2016.
• A Primal and Dual Sparse Approach to Extreme Classification (pdf, slides, poster, code)
  I. Yen, X. Huang, K. Zhong, P. Ravikumar, I. Dhillon.
  In International Conference on Machine Learning (ICML), June 2016. (Oral)

2015

• Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent (pdf, code)
  I. Yen, K. Zhong, C. Hsieh, P. Ravikumar, I. Dhillon.
  In Neural Information Processing Systems (NIPS), December 2015.
• Efficient Matrix Sensing Using Rank-1 Gaussian Measurements (pdf)
  K. Zhong, P. Jain, I. Dhillon.
  In International Conference on Algorithmic Learning Theory (ALT), pp. 3-18, October 2015.
• A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models (pdf, slides)
  I. Yen, X. Lin, K. Zhong, P. Ravikumar, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 2418-2426, July 2015.

2014

• Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators (pdf, code)
  K. Zhong, I. Yen, I. Dhillon, P. Ravikumar.
  In Neural Information Processing Systems (NIPS), pp. 2375-2383, December 2014.