Check out our website for more info: computationalprivacy.github.io/loss_traces/

arxiv: arxiv.org/abs/2411.05743

See you in Seattle!

And thanks to my amazing co-authors: Joseph Pollock, Euodia Dodd and @yvesalexandre.bsky.social

Why this matters:

✅ Enables iterative privacy risk assessment during model development
✅ Zero additional computational cost
✅ Could inform targeted defenses (selective unlearning, data removal)
✅ Practical for large models where shadow model approaches fail

The best part? You can collect per-sample losses for free during training by simply changing the loss reduction:

Our proposed loss trace aggregation methods achieve 92% Precision@k=1% in identifying samples vulnerable to LiRA attack on CIFAR-10 (positives at FPR=0.001). Prior computationally effective vulnerability detection methods (loss, gradient norm) perform barely better than random on the same task.

🐸 Check out these CIFAR-10 frog examples:

Easy-to-fit outliers: Loss drops late but reaches near zero → most vulnerable

Hard-to-fit outliers: Loss drops slowly, stays relatively high → somewhat vulnerable

Average samples: Loss drops quickly and stays low → least vulnerable

Problem: SoTA MIAs often require training hundreds of shadow models to identify vulnerable samples. This is extremely expensive, especially for large models.

Solution: Loss pattern throughout training tells you a lot about individual's vulnerability.

⬇️

We're very excited to host this meetup and we'd be thrilled to see you there!

imperial.ac.uk/events/18318...

We're also inviting PhD students to give 1-minute lightning talks to share their research with the community.

If you're interested, please sign up here:

docs.google.com/forms/d/e/1F...

The line-up for the evening:

- Graham Cormode (University of Warwick/Meta AI)
- Lukas Wutschitz (M365 Research, Microsoft)
- Jamie Hayes (Google DeepMind)
- Ilia Shumailov (Google DeepMind)

Recognizing the growing ML Privacy community in and around London, we hope this to be a great opportunity for people to connect and share perspectives.

We will be hosting research talks from our amazing invited speakers, followed by a happy hour.

Считаю, что можно забрать обратно слово твиты, потому что в Х теперь «посты»

Что как за что

Почему ты вообще туда писал

Мне от этого треда захотелось к зимней сессии подготовиться