Search Results for author:
Found 9 papers, 3 papers with code
Voronoi Candidates for Bayesian Optimization
Bayesian optimization (BO) offers an elegant approach for efficiently optimizing black-box functions.
Surrogate Active Subspaces for Jump-Discontinuous Functions
But given that active subspaces are defined by way of gradients, it is not clear what quantity is being estimated when this methodology is applied to a discontinuous simulator.
Sparse Bayesian Lasso via a Variable-Coefficient $\ell_1$ Penalty
Modern statistical learning algorithms are capable of amazing flexibility, but struggle with interpretability.
Triangulation candidates for Bayesian optimization
Bayesian optimization involves "inner optimization" over a new-data acquisition criterion which is non-convex/highly multi-modal, may be non-differentiable, or may otherwise thwart local numerical optimizers.
Neko: a Library for Exploring Neuromorphic Learning Rules
To address this gap, we present Neko, a modular, extensible library with a focus on aiding the design of new learning algorithms.
Sensitivity Prewarping for Local Surrogate Modeling
In the continual effort to improve product quality and decrease operations costs, computational modeling is increasingly being deployed to determine feasibility of product designs or configurations.
Towards On-Chip Bayesian Neuromorphic Learning
e-prop 1 is a promising learning algorithm that tackles this with Broadcast Alignment (a technique where network weights are replaced with random weights during feedback) and accumulated local information.
Sequential Learning of Active Subspaces
In such cases, often a surrogate model is employed, on which finite differencing is performed.
Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout
We use these results to demonstrate the feasibility of conducting the inference phase with permanent dropout on spiking neural networks, mitigating the technique's computational and energy burden, which is essential for its use at scale or on edge platforms.
