5 citations · 8 across the 7 of their papers we have counts for
3 papers · 1 filter
Deep Learning with Label Noise: A Hierarchical Approach
Li Chen, Ningyuan Huang, Cong Mu +4
Deep neural networks are susceptible to label noise. Existing methods to improve robustness, such as meta-learning and regularization, usually require significant change to the net…
Leveraging semantically similar queries for ranking via combining representations
Hayden S. Helm, Marah Abdin, Benjamin D. Pedigo +8
In modern ranking problems, different and disparate representations of the items to be ranked are often available. It is sensible, then, to try to combine these representations to…
Learning without gradient descent encoded by the dynamics of a neurobiological model
Vivek Kurien George, Vikash Morar, Weiwei Yang +6
The success of state-of-the-art machine learning is essentially all based on different variations of gradient descent algorithms that minimize some version of a cost or loss functi…