43 citations · 64 across the 25 of their papers we have counts for
6 papers · 1 filter
Uniform Generalization Bounds for Overparameterized Neural Networks
Sattar Vakili, Michael Bromberg, Jezabel Garcia +2
An interesting observation in artificial neural networks is their favorable generalization error despite typically being extremely overparameterized. It is well known that the clas…
Optimal Order Simple Regret for Gaussian Process Bandits
Sattar Vakili, Nacime Bouziani, Sepehr Jalali +2
Consider the sequential optimization of a continuous, possibly non-convex, and expensive to evaluate objective function . The problem can be cast as a Gaussian Process (GP) band…
Natural continual learning: success is a journey, not (just) a destination
Ta-Chu Kao, Kristopher T. Jensen, Gido M. van de Ven +2
Biological agents are known to learn many different tasks over the course of their lives, and to be able to revisit previous tasks and behaviors with little to no loss in performan…
Meta-learning with negative learning rates
Alberto Bernacchia
Deep learning models require a large amount of data to perform well. When data is scarce for a target task, we can transfer the knowledge gained by training on similar tasks to qui…
Meta-Learning with MAML on Trees
Jezabel R. Garcia, Federica Freddi, Feng-Ting Liao +5
In meta-learning, the knowledge learned from previous tasks is transferred to new ones, but this transfer only works if tasks are related. Sharing information between unrelated tas…
How to distribute data across tasks for meta-learning?
Alexandru Cioba, Michael Bromberg, Qian Wang +5
Meta-learning models transfer the knowledge acquired from previous tasks to quickly learn new ones. They are trained on benchmarks with a fixed number of data points per task. This…