research
∙
12/28/2022
On Implicit Bias in Overparameterized Bilevel Optimization
Many problems in machine learning involve bilevel optimization (BLO), in...
share
research
∙
08/26/2022
Task Selection for AutoML System Evaluation
Our goal is to assess if AutoML system changes - i.e., to the search spa...
research
∙
12/30/2021
Self-tuning networks:
Hyperparameter optimization can be formulated as a bilevel optimization ...
research
∙
12/30/2021
JacNet: Learning Functions with Structured Jacobians
Neural networks are trained to learn an approximate mapping from an inpu...
research
∙
12/24/2021
Lyapunov Exponents for Diversity in Differentiable Games
Ridge Rider (RR) is an algorithm for finding diverse solutions to optimi...
research
∙
11/23/2021
Input Convex Gradient Networks
The gradients of convex functions are expressive models of non-trivial v...
research
∙
11/02/2021
Meta-Learning to Improve Pre-Training
Pre-training (PT) followed by fine-tuning (FT) is an effective method fo...
research
∙
02/16/2021
Complex Momentum for Learning in Games
We generalize gradient descent with momentum for learning in differentia...
research
∙
11/06/2019
Optimizing Millions of Hyperparameters by Implicit Differentiation
We propose an algorithm for inexpensive gradient-based hyperparameter op...
research
∙
03/31/2019
Understanding Neural Architecture Search Techniques
Automatic methods for generating state-of-the-art neural network archite...
research
∙
02/26/2018
