Bayesian Learning
Predictive Uncertainty Estimation via Prior Networks
Neural Information Processing Systems http://nips.cc/
The Description Length of Deep Learning models
Neural Information Processing Systems http://nips.cc/
A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families
Brian Axelrod, Ilias Diakonikolas, Alistair Stewart, Anastasios Sidiropoulos, Gregory Valiant
Neural Information Processing Systems http://nips.cc/
This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian Optimization
Bayesian Optimization (BO) is an effective framework for black-box optimization.
Multi-value Rule Sets for Interpretable Classification with Feature-Efficient Representations
Neural Information Processing Systems http://nips.cc/
Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional Data
When training deep neural networks, a model's generalization error is often observed to follow a power scaling law dependent both on the model size and the
Bayesian Control of Large MDPs with Unknown Dynamics in Data-Poor Environments
Mahdi Imani, Seyede Fatemeh Ghoreishi, Ulisses M. Braga-Neto
Neural Information Processing Systems http://nips.cc/
Gradient Information for Representation and Modeling
Jie Ding, Robert Calderbank, Vahid Tarokh
Neural Information Processing Systems http://nips.cc/