111 citations · 147 across the 6 of their papers we have counts for
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cs.LG2022★ 1 cited
Generalizing Gaussian Smoothing for Random Search
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 s…
cs.LG2020★ 9 cited
Modeling and Optimization Trade-off in Meta-learning
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 pro…
cs.LG2018★ 111 cited
Assessing Generalization in Deep Reinforcement Learning
Charles Packer, Katelyn Gao, Jernej Kos +3
Deep reinforcement learning (RL) has achieved breakthrough results on many tasks, but agents often fail to generalize beyond the environment they were trained in. As a result, deep…