52 citations · 106 across the 9 of their papers we have counts for
5 papers · 1 filter
RIZE: Adaptive Regularization for Imitation Learning
Adib Karimi, Mohammad Mehdi Ebadzadeh
We propose a novel Inverse Reinforcement Learning (IRL) method that mitigates the rigidity of fixed reward structures and the limited flexibility of implicit reward regularization.…
EnTRPO: Trust Region Policy Optimization Method with Entropy Regularization
Sahar Roostaie, Mohammad Mehdi Ebadzadeh
Trust Region Policy Optimization (TRPO) is a popular and empirically successful policy search algorithm in reinforcement learning (RL). It iteratively solved the surrogate problem…
Maximum Entropy Dueling Network Architecture in Atari Domain
Alireza Nadali, Mohammad Mehdi Ebadzadeh
In recent years, there have been many deep structures for Reinforcement Learning, mainly for value function estimation and representations. These methods achieved great success in…
Adaptive Explicit Kernel Minkowski Weighted K-means
Amir Aradnia, Maryam Amir Haeri, Mohammad Mehdi Ebadzadeh
The K-means algorithm is among the most commonly used data clustering methods. However, the regular K-means can only be applied in the input space and it is applicable when cluster…
Backpropagation-Free Learning Method for Correlated Fuzzy Neural Networks
Armin Salimi-Badr, Mohammad Mehdi Ebadzadeh
In this paper, a novel stepwise learning approach based on estimating desired premise parts' outputs by solving a constrained optimization problem is proposed. This learning approa…