10 citations · 24 across the 9 of their papers we have counts for
11 papers
When a High Score Is an Illusion: Certifying Genuine versus Repackaged Forecasting Skill
Pin Ni, Francesca Medda, Ramin Okhrati
Ranks depend on the observations used for comparison. Reusing those observations can add association between forecast and outcome rank contrasts even when the evaluated forecast an…
How Personality Traits Shape LLM Risk-Taking Behaviour
John Hartley, Conor Hamill, Devesh Batra +3
Large Language Models (LLMs) are increasingly deployed as autonomous agents, necessitating a deeper understanding of their decision-making behaviour under risk. This study investig…
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…
Agent-based Modelling of Credit Card Promotions
Conor B. Hamill, Raad Khraishi, Simona Gherghel +4
Interest-free promotions are a prevalent strategy employed by credit card lenders to attract new customers, yet the research exploring their effects on both consumers and lenders r…
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…
Itô's formula for finite variation Lévy processes: The case of non-smooth functions
Ramin Okhrati, Uwe Schmock
Extending Itô's formula to non-smooth functions is important both in theory and applications. One of the fairly general extensions of the formula, known as Meyer-Itô, applies to on…
Hedging of defaultable claims in a structural model using a locally risk-minimizing approach
Ramin Okhrati, Alejandro Balbás, José Garrido
In the context of a locally risk-minimizing approach, the problem of hedging defaultable claims and their Follmer-Schweizer decompositions are discussed in a structural model. This…