Search Results for author: Shubho Sengupta

Found 8 papers, 6 papers with code

Parallel Composition of Weighted Finite-State Transducers

no code implementations6 Oct 2021 Shubho Sengupta, Vineel Pratap, Awni Hannun

We benchmark our parallel algorithm on the composition of random graphs and the composition of graphs commonly used in speech recognition.

speech-recognition Speech Recognition

CrypTen: Secure Multi-Party Computation Meets Machine Learning

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.

BIG-bench Machine Learning Image Classification +4

Privacy-Preserving Multi-Party Contextual Bandits

no code implementations11 Oct 2019 Awni Hannun, Brian Knott, Shubho Sengupta, Laurens van der Maaten

This paper considers a learning setting in which multiple parties aim to train a contextual bandit together in a private way: the parties aim to maximize the total reward but do not want to share any of the relevant information they possess with the other parties.

Multi-Armed Bandits Privacy Preserving

ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero

1 code implementation12 Feb 2019 Yuandong Tian, Jerry Ma, Qucheng Gong, Shubho Sengupta, Zhuoyuan Chen, James Pinkerton, C. Lawrence Zitnick

The AlphaGo, AlphaGo Zero, and AlphaZero series of algorithms are remarkable demonstrations of deep reinforcement learning's capabilities, achieving superhuman performance in the complex game of Go with progressively increasing autonomy.

Game of Go

Exploring Sparsity in Recurrent Neural Networks

1 code implementation17 Apr 2017 Sharan Narang, Erich Elsen, Gregory Diamos, Shubho Sengupta

Benchmarks show that using our technique model size can be reduced by 90% and speed-up is around 2x to 7x.

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