Search Results for author: Harris Chan

Found 15 papers, 4 papers with code

Robotic Skill Acquisition via Instruction Augmentation with Vision-Language Models

no code implementations21 Nov 2022 Ted Xiao, Harris Chan, Pierre Sermanet, Ayzaan Wahid, Anthony Brohan, Karol Hausman, Sergey Levine, Jonathan Tompson

To accomplish this, we introduce Data-driven Instruction Augmentation for Language-conditioned control (DIAL): we utilize semi-supervised language labels leveraging the semantic understanding of CLIP to propagate knowledge onto large datasets of unlabelled demonstration data and then train language-conditioned policies on the augmented datasets.

Imitation Learning

Large Language Models Are Human-Level Prompt Engineers

3 code implementations3 Nov 2022 Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, Jimmy Ba

By conditioning on natural language instructions, large language models (LLMs) have displayed impressive capabilities as general-purpose computers.

Few-Shot Learning In-Context Learning +3

An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality

2 code implementations ICLR 2020 Silviu Pitis, Harris Chan, Kiarash Jamali, Jimmy Ba

When defining distances, the triangle inequality has proven to be a useful constraint, both theoretically--to prove convergence and optimality guarantees--and empirically--as an inductive bias.

Inductive Bias Metric Learning +3

Multichannel Generative Language Models

no code implementations25 Sep 2019 Harris Chan, Jamie Kiros, William Chan

For conditional generation, the model is given a fully observed channel, and generates the k-1 channels in parallel.

Machine Translation

An Empirical Study of Large-Batch Stochastic Gradient Descent with Structured Covariance Noise

no code implementations21 Feb 2019 Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba

We demonstrate that the learning performance of our method is more accurately captured by the structure of the covariance matrix of the noise rather than by the variance of gradients.

Stochastic Optimization

ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning

no code implementations12 Feb 2019 Harris Chan, Yuhuai Wu, Jamie Kiros, Sanja Fidler, Jimmy Ba

We first analyze the differences among goal representation, and show that ACTRCE can efficiently solve difficult reinforcement learning problems in challenging 3D navigation tasks, whereas HER with non-language goal representation failed to learn.

Multi-Goal Reinforcement Learning reinforcement-learning +1

Exploring Curvature Noise in Large-Batch Stochastic Optimization

no code implementations27 Sep 2018 Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba

Unfortunately, a major drawback is the so-called generalization gap: large-batch training typically leads to a degradation in generalization performance of the model as compared to small-batch training.

Stochastic Optimization

Are You Sure You Want To Do That? Classification with Verification

no code implementations7 Sep 2018 Harris Chan, Atef Chaudhury, Kevin Shen

Classification systems typically act in isolation, meaning they are required to implicitly memorize the characteristics of all candidate classes in order to classify.

General Classification Memorization

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