463 citations · 5.1k across the 190 of their papers we have counts for
6 papers · 2 filters
Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods
Kevin J Liang, Guoyin Wang, Yitong Li +2
We investigate time-dependent data analysis from the perspective of recurrent kernel machines, from which models with hidden units and gated memory cells arise naturally. By consid…
Adversarial Self-Paced Learning for Mixture Models of Hawkes Processes
Dixin Luo, Hongteng Xu, Lawrence Carin
We propose a novel adversarial learning strategy for mixture models of Hawkes processes, leveraging data augmentation techniques of Hawkes process in the framework of self-paced le…
Syntax-Infused Variational Autoencoder for Text Generation
Xinyuan Zhang, Yi Yang, Siyang Yuan +2
We present a syntax-infused variational autoencoder (SIVAE), that integrates sentences with their syntactic trees to improve the grammar of generated sentences. Distinct from exist…
Survival Function Matching for Calibrated Time-to-Event Predictions
Paidamoyo Chapfuwa, Chenyang Tao, Lawrence Carin +1
Models for predicting the time of a future event are crucial for risk assessment, across a diverse range of applications. Existing time-to-event (survival) models have focused prim…
Scalable Thompson Sampling via Optimal Transport
Ruiyi Zhang, Zheng Wen, Changyou Chen +1
Thompson sampling (TS) is a class of algorithms for sequential decision-making, which requires maintaining a posterior distribution over a model. However, calculating exact posteri…
GO Gradient for Expectation-Based Objectives
Yulai Cong, Miaoyun Zhao, Ke Bai +1
Within many machine learning algorithms, a fundamental problem concerns efficient calculation of an unbiased gradient wrt parameters $\gammav$ for expectation-based objectives $\Eb…