Centre for Supply Chain Research Events

Centre for Supply Chain Research events provide opportunities for open debate, shape business agendas, and establish research priorities.

2025 events 

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Wednesday 2 July 

'It's all in the mix: Wasserstein classification and regression with mixed features'

Speaker: Mr Aras Selvi, Imperial College London Business School (UK)  
Open to: OSCM Group staff and students, with no sign up needed
Time: 11am-12pm
In person: Management School, Committee Room 2
Online: Zoom Link, Meeting ID: 926 6268 2235, Passcode: q4q&!S#z

Abstract: 

A key challenge in supervised learning is data scarcity, which can cause prediction models to overfit to the training data and perform poorly out of sample.

A contemporary approach to combat overfitting is offered by distributionally robust problem formulations that consider all data-generating distributions close to the empirical distribution derived from historical samples, where ‘closeness’ is determined by the Wasserstein distance.

While such formulations show significant promise in prediction tasks where all input features are continuous, they scale exponentially when discrete features are present.

We demonstrate that distributionally robust mixed-feature classification and regression problems can indeed be solved in polynomial time.

Our proof relies on classical ellipsoid method-based solution schemes that do not scale well in practice.

To overcome this limitation, we develop a practically efficient (yet, in the worst case, exponential time) cutting plane based algorithm that admits a polynomial time separation oracle, despite the presence of exponentially many constraints.

We compare our method against alternative techniques both theoretically and empirically on standard benchmark instances.

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