55 citations · 152 across the 23 of their papers we have counts for
24 papers
mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization
Kayhan Behdin, Qingquan Song, Aman Gupta +7
Modern deep learning models are over-parameterized, where different optima can result in widely varying generalization performance. The Sharpness-Aware Minimization (SAM) technique…
Improved Deep Neural Network Generalization Using m-Sharpness-Aware Minimization
Kayhan Behdin, Qingquan Song, Aman Gupta +4
Modern deep learning models are over-parameterized, where the optimization setup strongly affects the generalization performance. A key element of reliable optimization for these s…
Logit Attenuating Weight Normalization
Aman Gupta, Rohan Ramanath, Jun Shi +4
Over-parameterized deep networks trained using gradient-based optimizers are a popular choice for solving classification and ranking problems. Without appropriately tuned …
Image Generation Via Minimizing Fréchet Distance in Discriminator Feature Space
Khoa D. Doan, Saurav Manchanda, Fengjiao Wang +3
For a given image generation problem, the intrinsic image manifold is often low dimensional. We use the intuition that it is much better to train the GAN generator by minimizing th…
Regression via Implicit Models and Optimal Transport Cost Minimization
Saurav Manchanda, Khoa Doan, Pranjul Yadav +1
This paper addresses the classic problem of regression, which involves the inductive learning of a map, , denoting noise, $f:\mathbb{R}^n\times \mathbb{R}^k \rightarr…
Targeted display advertising: the case of preferential attachment
Saurav Manchanda, Pranjul Yadav, Khoa Doan +1
An average adult is exposed to hundreds of digital advertisements daily (https://www.mediadynamicsinc.com/uploads/files/PR092214-Note-only-150-Ads-2mk.pdf), making the digital adve…