10 citations · 24 across the 9 of their papers we have counts for
6 papers · 1 filter
Dynamic Estimation of Learning Rates Using a Non-Linear Autoregressive Model
Ramin Okhrati
We introduce a new class of adaptive non-linear autoregressive (Nlar) models incorporating the concept of momentum, which dynamically estimate both the learning rates and momentum…
Simple Noisy Environment Augmentation for Reinforcement Learning
Raad Khraishi, Ramin Okhrati
Data augmentation is a widely used technique for improving model performance in machine learning, particularly in computer vision and natural language processing. Recently, there h…
An Introduction to Machine Unlearning
Salvatore Mercuri, Raad Khraishi, Ramin Okhrati +4
Removing the influence of a specified subset of training data from a machine learning model may be required to address issues such as privacy, fairness, and data quality. Retrainin…
Offline Deep Reinforcement Learning for Dynamic Pricing of Consumer Credit
Raad Khraishi, Ramin Okhrati
We introduce a method for pricing consumer credit using recent advances in offline deep reinforcement learning. This approach relies on a static dataset and requires no assumptions…
A Multilinear Sampling Algorithm to Estimate Shapley Values
Ramin Okhrati, Aldo Lipani
Shapley values are great analytical tools in game theory to measure the importance of a player in a game. Due to their axiomatic and desirable properties such as efficiency, they h…
A Baseline for Shapley Values in MLPs: from Missingness to Neutrality
Cosimo Izzo, Aldo Lipani, Ramin Okhrati +1
Deep neural networks have gained momentum based on their accuracy, but their interpretability is often criticised. As a result, they are labelled as black boxes. In response, sever…