Neural Network Pruning Through Constrained Reinforcement Learning

no code implementations • 16 Oct 2021 • Shehryar Malik, Muhammad Umair Haider, Omer Iqbal, Murtaza Taj

In this work, we propose a general methodology for pruning neural networks.

Image Classification Network Pruning +2

Constrained Reinforcement Learning With Learned Constraints

no code implementations • 1 Jan 2021 • Shehryar Malik, Usman Anwar, Alireza Aghasi, Ali Ahmed

In this work, given a reward function and a set of demonstrations from an expert that maximizes this reward function while respecting \textit{unknown} constraints, we propose a framework to learn the most likely constraints that the expert respects.

reinforcement-learning Reinforcement Learning (RL)

Inverse Constrained Reinforcement Learning

1 code implementation • 19 Nov 2020 • Usman Anwar, Shehryar Malik, Alireza Aghasi, Ali Ahmed

However, for the real world deployment of reinforcement learning (RL), it is critical that RL agents are aware of these constraints, so that they can act safely.

reinforcement-learning Reinforcement Learning (RL)

Learning To Solve Differential Equations Across Initial Conditions

no code implementations • ICLR Workshop DeepDiffEq 2019 • Shehryar Malik, Usman Anwar, Ali Ahmed, Alireza Aghasi

Recently, there has been a lot of interest in using neural networks for solving partial differential equations.