activity
20242026
collaborators

7 papers

cs.AI2026

When Do We Need LLMs? A Diagnostic for Language-Driven Bandits

Uljad Berdica, Fernando Acero, Anton Ipsen +3

We study Contextual Multi-Armed Bandits (CMABs) for non-episodic decision-making problems where the context includes both textual and numerical information (e.g., recommendation sy…

cs.AI2026

Beyond Manual Planning: Seating Allocation for Large Organizations

Anton Ipsen, Michael Cashmore, Kirsty Fielding +4

We introduce the Hierarchical Seating Allocation Problem (HSAP) which addresses the optimal assignment of hierarchically structured organizational teams to physical seating arrange…

cs.LG2026

Creating a Causally Grounded Rating Method for Assessing the Robustness of AI Models for Time-Series Forecasting

Kausik Lakkaraju, Rachneet Kaur, Parisa Zehtabi +5

AI models, including both time-series-specific and general-purpose Foundation Models (FMs), have demonstrated strong potential in time-series forecasting across sectors like financ…

cs.AI2025

The Subset Sum Matching Problem

Yufei Wu, Manuel R. Torres, Parisa Zehtabi +4

This paper presents a new combinatorial optimisation task, the Subset Sum Matching Problem (SSMP), which is an abstraction of common financial applications such as trades reconcili…

cs.DC2025

Capacity Planning and Scheduling for Jobs with Uncertainty in Resource Usage and Duration

Sunandita Patra, Mehtab Pathan, Mahmoud Mahfouz +4

Organizations around the world schedule jobs (programs) regularly to perform various tasks dictated by their end users. With the major movement towards using a cloud computing infr…

cs.AI2024

Temporal Fairness in Decision Making Problems

Manuel R. Torres, Parisa Zehtabi, Michael Cashmore +2

In this work we consider a new interpretation of fairness in decision making problems. Building upon existing fairness formulations, we focus on how to reason over fairness from a…