528 citations · 1.1k across the 28 of their papers we have counts for
5 papers · 1 filter
Extracting or Guessing? Improving Faithfulness of Event Temporal Relation Extraction
Haoyu Wang, Hongming Zhang, Yuqian Deng +3
In this paper, we seek to improve the faithfulness of TempRel extraction models from two perspectives. The first perspective is to extract genuinely based on contextual description…
Local Bayesian optimization via maximizing probability of descent
Quan Nguyen, Kaiwen Wu, Jacob R. Gardner +1
Local optimization presents a promising approach to expensive, high-dimensional black-box optimization by sidestepping the need to globally explore the search space. For objective…
Discovering Many Diverse Solutions with Bayesian Optimization
Natalie Maus, Kaiwen Wu, David Eriksson +1
Bayesian optimization (BO) is a popular approach for sample-efficient optimization of black-box objective functions. While BO has been successfully applied to a wide range of scien…
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients
Kyurae Kim, Jisu Oh, Jacob R. Gardner +2
Minimizing the inclusive Kullback-Leibler (KL) divergence with stochastic gradient descent (SGD) is challenging since its gradient is defined as an integral over the posterior. Rec…
Local Latent Space Bayesian Optimization over Structured Inputs
Natalie Maus, Haydn T. Jones, Juston S. Moore +3
Bayesian optimization over the latent spaces of deep autoencoder models (DAEs) has recently emerged as a promising new approach for optimizing challenging black-box functions over…