4 papers · 1 filter
Exact Unlearning via Quantized Sufficient Statistics
Ami Tavory, Shripad Gade, Tal Sarig +2
Exact unlearning requires a deployed predictor to match one rebuilt without the information named by a deletion request. Existing general-purpose exact methods localize retraining…
Bandits via Additive Quantized Representations
Ami Tavory, Noam Touitou, Tal Sarig +2
Contextual bandits require balancing nonlinear reward modeling with online efficiency. Tree ensembles and neural methods capture nonlinearities but require periodic retraining and…
A Graph Meta-Network for Learning on Kolmogorov-Arnold Networks
Guy Bar-Shalom, Ami Tavory, Itay Evron +3
Weight-space models learn directly from the parameters of neural networks, enabling tasks such as predicting their accuracy on new datasets. Naive methods -- like applying MLPs to…
Billion-Scale Graph Foundation Models
Maya Bechler-Speicher, Yoel Gottlieb, Andrey Isakov +5
Graph-structured data underpins many critical applications. While foundation models have transformed language and vision via large-scale pretraining and lightweight adaptation, ext…