2 code implementations • 1 Jun 2022 • Yongchao Zhou, Ehsan Nezhadarya, Jimmy Ba
Dataset distillation can be formulated as a bi-level meta-learning problem where the outer loop optimizes the meta-dataset and the inner loop trains a model on the distilled data.
no code implementations • CVPR 2021 • Shengdong Zhang, Ehsan Nezhadarya, Homa Fashandi, Jiayi Liu, Darin Graham, Mohak Shah
BN uses scaling and shifting to normalize activations of mini-batches to accelerate convergence and improve generalization.
no code implementations • 19 Aug 2019 • Ehsan Nezhadarya, Yang Liu, Bingbing Liu
We present a learning-based method to estimate the object bounding box from its 2D bird's-eye view (BEV) LiDAR points.
no code implementations • CVPR 2020 • Ehsan Nezhadarya, Ehsan Taghavi, Ryan Razani, Bingbing Liu, Jun Luo
While several convolution-like operators have recently been proposed for extracting features out of point clouds, down-sampling an unordered point cloud in a deep neural network has not been rigorously studied.
no code implementations • 12 Jun 2013 • Tanaya Guha, Ehsan Nezhadarya, Rabab K. Ward
This sparse strategy is employed because it is known to generate basis vectors that are qualitatively similar to the receptive field of the simple cells present in the mammalian primary visual cortex.