Publications tagged "Deep learning"


Conferences

AutoPandas: Neural-Backed Generators for Program Synthesis

Rohan Bavishi, Caroline Lemieux, Roy Fox, Koushik Sen, and Ion Stoica

10th ACM SIGPLAN Conference on Systems, Programming, Languages, and Applications: Software for Humanity (SPLASH OOPSLA), 2019


Constraint Estimation and Derivative-Free Recovery for Robot Learning from Demonstrations

Jonathan Lee, Michael Laskey, Roy Fox, and Ken Goldberg

14th IEEE Conference on Automation Science and Engineering (CASE), 2018


RLlib: Abstractions for Distributed Reinforcement Learning

Eric Liang*, Richard Liaw*, Robert Nishihara, Philipp Moritz, Roy Fox, Ken Goldberg, Joseph Gonzalez, Michael Jordan, and Ion Stoica

35th International Conference on Machine Learning (ICML), 2018


Parametrized Hierarchical Procedures for Neural Programming

Roy Fox, Richard Shin, Sanjay Krishnan, Ken Goldberg, Dawn Song, and Ion Stoica

6th International Conference on Learning Representations (ICLR), 2018


DDCO: Discovery of Deep Continuous Options for Robot Learning from Demonstrations

Sanjay Krishnan*, Roy Fox*, Ion Stoica, and Ken Goldberg

1st Conference on Robot Learning (CoRL), 2017


DART: Noise Injection for Robust Imitation Learning

Michael Laskey, Jonathan Lee, Roy Fox, Anca Dragan, and Ken Goldberg

1st Conference on Robot Learning (CoRL), 2017


Statistical Data Cleaning for Deep Learning of Automation Tasks from Demonstrations

Caleb Chuck, Michael Laskey, Sanjay Krishnan, Ruta Joshi, Roy Fox, and Ken Goldberg

13th IEEE Conference on Automation Science and Engineering (CASE), 2017


Workshops

Multi-Task Learning via Task Multi-Clustering

Andy Yan, Xin Wang, Ion Stoica, Joseph Gonzalez, and Roy Fox

Adaptive & Multitask Learning workshop (AMTL @ ICML), 2019


Hierarchical Imitation Learning via Variational Inference of Control Programs

Roy Fox, Richard Shin, William Paul, Yitian Zou, Dawn Song, Ken Goldberg, Pieter Abbeel, and Ion Stoica

Infer to Control: Probabilistic Reinforcement Learning and Structured Control workshop (Infer2Control @ NeurIPS), 2018


An Empirical Exploration of Gradient Correlations in Deep Learning

Daniel Rothchild, Roy Fox, Noah Golmant, Joseph Gonzalez, Michael Mahoney, Kai Rothauge, Ion Stoica, and Zhewei Yao

Integration of Deep Learning Theories workshop (DLT @ NeurIPS), 2018


Neural Inference of API Functions from Input–Output Examples

Rohan Bavishi, Caroline Lemieux, Neel Kant, Roy Fox, Koushik Sen, and Ion Stoica

Machine Learning for Systems workshop (ML for Sys @ NeurIPS), 2018


Imitation Learning of Hierarchical Programs via Variational Inference

Roy Fox*, Richard Shin*, Pieter Abbeel, Ken Goldberg, Dawn Song, and Ion Stoica

Neural Abstract Machines & Program Induction workshop (NAMPI @ ICML), 2018


Task-Relevant Embeddings for Robust Perception in Reinforcement Learning

Eric Liang, Roy Fox, Joseph Gonzalez, and Ion Stoica

Prediction and Generative Modeling in Reinforcement Learning workshop (PGMRL @ ICML), 2018


Ray RLlib: A Composable and Scalable Reinforcement Learning Library

Eric Liang*, Richard Liaw*, Robert Nishihara, Philipp Moritz, Roy Fox, Joseph Gonzalez, Ken Goldberg, and Ion Stoica

Deep Reinforcement Learning symposium (DeepRL @ NIPS), 2017


Preprints

Hierarchical Variational Imitation Learning of Control Programs

Roy Fox, Richard Shin, William Paul, Yitian Zou, Dawn Song, Ken Goldberg, Pieter Abbeel, and Ion Stoica

arXiv:1912.12612, 2019


Multi-Level Discovery of Deep Options

Roy Fox*, Sanjay Krishnan*, Ion Stoica, and Ken Goldberg

arXiv:1703.08294, 2017