order derivative
Order Optimal One-Shot Distributed Learning
Arsalan Sharifnassab, Saber Salehkaleybar, S. Jamaloddin Golestani
Neural Information Processing Systems http://nips.cc/
Depth from a Single Image by Harmonizing Overcomplete Local Network Predictions
Ayan Chakrabarti, Jingyu Shao, Greg Shakhnarovich
Neural Information Processing Systems http://nips.cc/
FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models
Empirically, we verify the computational efficiency of our methods.
Derivative Estimation in Random Design
Neural Information Processing Systems http://nips.cc/
Direct Runge-Kutta Discretization Achieves Acceleration
Jingzhao Zhang, Aryan Mokhtari, Suvrit Sra, Ali Jadbabaie
We study gradient-based optimization methods obtained by directly discretizing a second-order ordinary differential equation (ODE) related to the continuous limit of Nesterov's accelerated gradient method.
Computing Higher Order Derivatives of Matrix and Tensor Expressions
Soeren Laue, Matthias Mitterreiter, Joachim Giesen
Optimization is an integral part of most machine learning systems and most numerical optimization schemes relyonthecomputation ofderivatives.
Order Optimal One-Shot Distributed Learning
Arsalan Sharifnassab, Saber Salehkaleybar, S. Jamaloddin Golestani
Neural Information Processing Systems http://nips.cc/