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- Argonne National LaboratoryUS310 papers
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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…
Spectral Graph Matching and Regularized Quadratic Relaxations I: The Gaussian Model
Zhou Fan, Cheng Mao, Yihong Wu +1
Graph matching aims at finding the vertex correspondence between two unlabeled graphs that maximizes the total edge weight correlation. This amounts to solving a computationally in…
Reducing Exploration of Dying Arms in Mortal Bandits
Stefano Tracà, Cynthia Rudin, Weiyu Yan
Mortal bandits have proven to be extremely useful for providing news article recommendations, running automated online advertising campaigns, and for other applications where the s…
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…
On Target Shift in Adversarial Domain Adaptation
Yitong Li, Michael Murias, Samantha Major +2
Discrepancy between training and testing domains is a fundamental problem in the generalization of machine learning techniques. Recently, several approaches have been proposed to l…
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…