6 papers
Adaptive Generate-Rank-Verify: Inference-Time Search with Costly Verification
Shaddin Dughmi, Mahdi Haghifam, Yusuf Hakan Kalayci
Many inference-time language-model pipelines combine a cheap reward signal with an expensive verifier, such as exact answer checking in mathematical reasoning or hidden-test execut…
The Distillation Game: Adaptive Attacks & Efficient Defenses
Youssef Allouah, Mahdi Haghifam, Sanmi Koyejo +1
Distillation attacks create a deployment trade-off for model providers: the same outputs that make a model more useful can also make it easier to imitate. We study this trade-off t…
The Sample Complexity of Membership Inference and Privacy Auditing
Mahdi Haghifam, Adam Smith, Jonathan Ullman
A membership-inference attack gets the output of a learning algorithm, and a target individual, and tries to determine whether this individual is a member of the training data or a…
On Traceability in Stochastic Convex Optimization
Sasha Voitovych, Mahdi Haghifam, Idan Attias +3
In this paper, we investigate the necessity of traceability for accurate learning in stochastic convex optimization (SCO) under geometries. Informally, we say a learning a…
Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization
Idan Attias, Gintare Karolina Dziugaite, Mahdi Haghifam +2
In this work, we investigate the interplay between memorization and learning in the context of \emph{stochastic convex optimization} (SCO). We define memorization via the informati…
Private Geometric Median
Mahdi Haghifam, Thomas Steinke, Jonathan Ullman
In this paper, we study differentially private (DP) algorithms for computing the geometric median (GM) of a dataset: Given points, in , the goal i…