157 citations · 227 across the 19 of their papers we have counts for
5 papers · 1 filter
COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search
Shibal Ibrahim, Wenyu Chen, Hussein Hazimeh +3
The sparse Mixture-of-Experts (Sparse-MoE) framework efficiently scales up model capacity in various domains, such as natural language processing and vision. Sparse-MoEs select a s…
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy
Natalia Ponomareva, Hussein Hazimeh, Alex Kurakin +6
ML models are ubiquitous in real world applications and are a constant focus of research. At the same time, the community has started to realize the importance of protecting the pr…
Fast as CHITA: Neural Network Pruning with Combinatorial Optimization
Riade Benbaki, Wenyu Chen, Xiang Meng +4
The sheer size of modern neural networks makes model serving a serious computational challenge. A popular class of compression techniques overcomes this challenge by pruning or spa…
Mind the (optimality) Gap: A Gap-Aware Learning Rate Scheduler for Adversarial Nets
Hussein Hazimeh, Natalia Ponomareva
Adversarial nets have proved to be powerful in various domains including generative modeling (GANs), transfer learning, and fairness. However, successfully training adversarial net…
Benchmarking Robustness to Adversarial Image Obfuscations
Florian Stimberg, Ayan Chakrabarti, Chun-Ta Lu +9
Automated content filtering and moderation is an important tool that allows online platforms to build striving user communities that facilitate cooperation and prevent abuse. Unfor…