1 citations · 1 across the 6 of their papers we have counts for
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Towards Faithful Data Selection: Statistical Limits and Scalable Algorithms
Ahmed Mehdi Inane, Mahdi Haghifam, Gintare Karolina Dziugaite +1
What does it mean to have an optimal data selection algorithm? Optimality is conventionally framed as finding a subset that minimizes the population error of the classifier trained…
Navigating Potholes with Geometry-Aware Sharpness Minimization
Simon Dufort-Labbé, Mehrab Hamidi, Razvan Pascanu +3
Sharpness-aware minimization (SAM) encourages flat minima by perturbing parameters along directions of high loss curvature, but treats all parameter directions uniformly, ignoring…
Adaptive Batch Sizes Using Non-Euclidean Gradient Noise Scales for Stochastic Sign and Spectral Descent
Hiroki Naganuma, Shagun Gupta, Youssef Briki +4
To maximize hardware utilization, modern machine learning systems typically employ large constant or manually tuned batch size schedules, relying on heuristics that are brittle and…
Generalization Measures under Controlled Covariate Shift: A Regime-Aware Benchmark
Sora Nakai, Youssef Fadhloun, Kacem Mathlouthi +4
Predicting generalization from quantities available before target-test evaluation remains a central challenge in deep learning. The systematic benchmark of Jiang et al. (2020) eval…