1 code implementation • 27 Nov 2022 • Katelyn Gao, Ozan Sener
Gaussian smoothing (GS) is a derivative-free optimization (DFO) algorithm that estimates the gradient of an objective using perturbations of the current parameters sampled from a standard normal distribution.
1 code implementation • NeurIPS 2020 • Katelyn Gao, Ozan Sener
By searching for shared inductive biases across tasks, meta-learning promises to accelerate learning on novel tasks, but with the cost of solving a complex bilevel optimization problem.
1 code implementation • ICLR 2019 • Charles Packer, Katelyn Gao, Jernej Kos, Philipp Krähenbühl, Vladlen Koltun, Dawn Song
Our aim is to catalyze community-wide progress on generalization in deep RL.
Out-of-Distribution Generalization reinforcement-learning +1
no code implementations • 5 Jun 2016 • Katelyn Gao
The age of big data has produced data sets that are computationally expensive to analyze and store.
1 code implementation • 31 Jan 2016 • Katelyn Gao, Art B. Owen
Large crossed data sets, described by generalized linear mixed models, have become increasingly common and provide challenges for statistical analysis.
Methodology Computation