6 citations · 9 across the 5 of their papers we have counts for
6 papers
Sharpness-Aware Minimization (SAM) Improves Classification Accuracy of Bacterial Raman Spectral Data Enabling Portable Diagnostics
Kaitlin Zareno, Jarett Dewbury, Siamak K. Sorooshyari +2
Antimicrobial resistance is expected to claim 10 million lives per year by 2050, and resource-limited regions are most affected. Raman spectroscopy is a novel pathogen diagnostic a…
Data-Aware Random Feature Kernel for Transformers
Amirhossein Farzam, Hossein Mobahi, Nolan Andrew Miller +1
Transformers excel across domains, yet their quadratic attention complexity poses a barrier to scaling. Random-feature attention, as in Performers, can reduce this cost to linear i…
PlanGEN: A Multi-Agent Framework for Generating Planning and Reasoning Trajectories for Complex Problem Solving
Mihir Parmar, Xin Liu, Palash Goyal +11
Recent agent frameworks and inference-time algorithms often struggle with complex planning problems due to limitations in verifying generated plans or reasoning and varying complex…
Avoiding spurious sharpness minimization broadens applicability of SAM
Sidak Pal Singh, Hossein Mobahi, Atish Agarwala +1
Curvature regularization techniques like Sharpness Aware Minimization (SAM) have shown great promise in improving generalization on vision tasks. However, we find that SAM performs…
Neglected Hessian component explains mysteries in Sharpness regularization
Yann N. Dauphin, Atish Agarwala, Hossein Mobahi
Recent work has shown that methods like SAM which either explicitly or implicitly penalize second order information can improve generalization in deep learning. Seemingly similar m…
On the Foundations of Shortcut Learning
Katherine L. Hermann, Hossein Mobahi, Thomas Fel +1
Deep-learning models can extract a rich assortment of features from data. Which features a model uses depends not only on \emph{predictivity} -- how reliably a feature indicates tr…