Deep Learning
rich Documents with Layout Annotations from Web Crawl Data Maurice Weber ETH Zurich Carlo Siebenschuh University of Chicago Rory M. Butler
The first three authors contributed equally.
A Deep Instance Generative Framework for MILP Solvers Under Limited Data Availability
We design a suite of benchmarks to evaluate the quality of the generated MILP instances.
Shared Adversarial Unlearning: Backdoor Mitigation by Unlearning Shared Adversarial Examples Shaokui Wei
However, these works face some limitations and challenges.
Undirected Probabilistic Model for Tensor Decomposition
Tensor decompositions (TDs) serve as a powerful tool for analyzing multiway data.
No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models Jean Kaddour 1 Oscar Key
This trend has motivated research on efficient training algorithms designed to improve training, validation, and downstream performance faster than standard training.