Publications

2019

• AutoAssist: A Framework to Accelerate Training of Deep Neural Networks
  J. Zhang, H. Yu, I. Dhillon.
  To appear in Neural Information Processing Systems (NIPS), December 2019.
• Extreme stochastic variational inference: distributed and asynchronous
  J. Zhang, P. Raman, S. Ji, S. Vishwanathan, I. Dhillon.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), 2019.

2018

• Learning long term dependencies via Fourier recurrent units (pdf, arXiv)
  J. Zhang, Y. Lin, Z. Song, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 5810–5818, July 2018.
• Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization (pdf, arXiv)
  J. Zhang, Q. Lei, I. Dhillon.
  In International Conference on Machine Learning (ICML), pp. 5801–5809, July 2018.

2017

• Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition (pdf)
  J. Zhang, I. Yen, P. Ravikumar, I. Dhillon.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), April 2017.

2016

• A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery (pdf, slides, poster)
  I. Yen, X. Lin, J. Zhang, P. Ravikumar, I. Dhillon.
  In International Conference on Machine Learning (ICML), June 2016. (Oral)