8 papers
Learning from Equivalence Queries, Revisited
Mark Braverman, Roi Livni, Yishay Mansour +2
Modern machine learning systems, such as generative models and recommendation systems, often evolve through a cycle of deployment, user interaction, and periodic model updates. Thi…
Margin in Abstract Spaces
Yair Ashlagi, Roi Livni, Shay Moran +1
Margin-based learning, exemplified by linear and kernel methods, is one of the few classical settings where generalization guarantees are independent of the number of parameters. T…
Reconstructing Template-Memorized Images from Natural Prompts
Sol Yarkoni, Mahmood Sharif, Roi Livni
Recent advances in generative models, such as diffusion models, have raised concerns related to privacy, copyright infringement, and data stewardship. To better understand and cont…
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…
Rapid Overfitting of Multi-Pass Stochastic Gradient Descent in Stochastic Convex Optimization
Shira Vansover-Hager, Tomer Koren, Roi Livni
We study the out-of-sample performance of multi-pass stochastic gradient descent (SGD) in the fundamental stochastic convex optimization (SCO) model. While one-pass SGD is known to…
Credit Attribution and Stable Compression
Roi Livni, Shay Moran, Kobbi Nissim +1
Credit attribution is crucial across various fields. In academic research, proper citation acknowledges prior work and establishes original contributions. Similarly, in generative…