13 citations · 32 across the 7 of their papers we have counts for
7 papers
Revisiting Energy Based Models as Policies: Ranking Noise Contrastive Estimation and Interpolating Energy Models
Sumeet Singh, Stephen Tu, Vikas Sindhwani
A crucial design decision for any robot learning pipeline is the choice of policy representation: what type of model should be used to generate the next set of robot actions? Owing…
Barkour: Benchmarking Animal-level Agility with Quadruped Robots
Ken Caluwaerts, Atil Iscen, J. Chase Kew +41
Animals have evolved various agile locomotion strategies, such as sprinting, leaping, and jumping. There is a growing interest in developing legged robots that move like their biol…
Provably Robust Blackbox Optimization for Reinforcement Learning
Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder +6
Interest in derivative-free optimization (DFO) and "evolutionary strategies" (ES) has recently surged in the Reinforcement Learning (RL) community, with growing evidence that they…
Geometry of 3D Environments and Sum of Squares Polynomials
Amir Ali Ahmadi, Georgina Hall, Ameesh Makadia +1
Motivated by applications in robotics and computer vision, we study problems related to spatial reasoning of a 3D environment using sublevel sets of polynomials. These include: tig…
Learning Machines Implemented on Non-Deterministic Hardware
Suyog Gupta, Vikas Sindhwani, Kailash Gopalakrishnan
This paper highlights new opportunities for designing large-scale machine learning systems as a consequence of blurring traditional boundaries that have allowed algorithm designers…
High-performance Kernel Machines with Implicit Distributed Optimization and Randomization
Vikas Sindhwani, Haim Avron
In order to fully utilize "big data", it is often required to use "big models". Such models tend to grow with the complexity and size of the training data, and do not make strong p…