1 code implementation • 19 Jul 2022 • Luis Pineda, Taosha Fan, Maurizio Monge, Shobha Venkataraman, Paloma Sodhi, Ricky T. Q. Chen, Joseph Ortiz, Daniel DeTone, Austin Wang, Stuart Anderson, Jing Dong, Brandon Amos, Mustafa Mukadam
We present Theseus, an efficient application-agnostic open source library for differentiable nonlinear least squares (DNLS) optimization built on PyTorch, providing a common framework for end-to-end structured learning in robotics and vision.
1 code implementation • NeurIPS 2021 • Brian Knott, Shobha Venkataraman, Awni Hannun, Shubho Sengupta, Mark Ibrahim, Laurens van der Maaten
To foster adoption of secure MPC in machine learning, we present CrypTen: a software framework that exposes popular secure MPC primitives via abstractions that are common in modern machine-learning frameworks, such as tensor computations, automatic differentiation, and modular neural networks.
1 code implementation • ICML Workshop AutoML 2021 • Shobha Venkataraman, Brandon Amos
Fixed-point iterations are at the heart of numerical computing and are often a computational bottleneck in real-time applications that typically need a fast solution of moderate accuracy.
no code implementations • NeurIPS 2009 • Shobha Venkataraman, Avrim Blum, Dawn Song, Subhabrata Sen, Oliver Spatscheck
We formulate and address the problem of discovering dynamic malicious regions on the Internet.