G
Gourav Roy
Researcher at Amazon.com
Publications - 6
Citations - 288
Gourav Roy is an academic researcher from Amazon.com. The author has contributed to research in topics: Data structure & Reinforcement learning. The author has an hindex of 4, co-authored 6 publications receiving 173 citations.
Papers
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Proceedings Article
Robust random cut forest based anomaly detection on streams
TL;DR: A robust random cut data structure that can be used as a sketch or synopsis of the input stream is investigated and it is shown how the sketch can be efficiently updated in a dynamic data stream.
Posted Content
DeepRacer: Educational Autonomous Racing Platform for Experimentation with Sim2Real Reinforcement Learning.
Bharathan Balaji,Sunil Mallya,Sahika Genc,Saurabh Gupta,Leo Parker Dirac,Vineet R. Khare,Gourav Roy,Tao Sun,Yunzhe Tao,Brian Townsend,Eddie Calleja,Sunil Muralidhara,Dhanasekar Karuppasamy +12 more
TL;DR: This work demonstrates how a 1/18th scale car can learn to drive autonomously using RL with a monocular camera and is the first successful large-scale deployment of deep reinforcement learning on a robotic control agent that uses only raw camera images as observations and a model-free learning method to perform robust path planning.
Proceedings ArticleDOI
DeepRacer: Autonomous Racing Platform for Experimentation with Sim2Real Reinforcement Learning
Bharathan Balaji,Sunil Mallya,Sahika Genc,Saurabh Gupta,Leo Parker Dirac,Vineet R. Khare,Gourav Roy,Tao Sun,Yunzhe Tao,Brian Townsend,Eddie Calleja,Sunil Muralidhara,Dhanasekar Karuppasamy +12 more
TL;DR: This work demonstrates how a 1/18th scale car can learn to drive autonomously using RL with a monocular camera using DeepRacer, the first successful large-scale deployment of deep reinforcement learning on a robotic control agent that uses only raw camera images as observations and a model-free learning method to perform robust path planning.
Journal ArticleDOI
Machine learning in the real world
TL;DR: This tutorial takes a hands-on approach to introducing the audience to machine learning and takes the audience through the end-to-end modeling pipeline for a real-world income prediction problem.
Patent
Clustering sparse high dimensional data using sketches
Gourav Roy,Amit Chandak,Prateek Gupta,Srujana Merugu,Aswin Natarajan,Sathish Kumar Palanisamy,Gowda Dayananda Anjaneyapura Range,Jagannathan Srinivasan,Bharath Venkatesh +8 more
TL;DR: In this article, an approximate data structure to represent clusters of observation records of a data set is identified and a hierarchical representation of a plurality of clusters, including the targeted number of clusters among which the observation records are to be distributed, is generated.