Xiaoyu Lu | DeepAI

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∙ 06/20/2022

Additive Gaussian Processes Revisited

Gaussian Process (GP) models are a class of flexible non-parametric mode...

2 Xiaoyu Lu, et al. ∙

∙ 09/01/2021

Spatially and Robustly Hybrid Mixture Regression Model for Inference of Spatial Dependence

In this paper, we propose a Spatial Robust Mixture Regression model to i...

0 Wennan Chang, et al. ∙

∙ 07/18/2020

Structure Mapping for Transferability of Causal Models

Human beings learn causal models and constantly use them to transfer kno...

7 Purva Pruthi, et al. ∙

∙ 05/24/2020

Causal Bayesian Optimization

This paper studies the problem of globally optimizing a variable of inte...

0 Virginia Aglietti, et al. ∙

∙ 10/31/2018

On Exploration, Exploitation and Learning in Adaptive Importance Sampling

We study adaptive importance sampling (AIS) as an online learning proble...

16 Xiaoyu Lu, et al. ∙

∙ 06/25/2018

Inference Trees: Adaptive Inference with Exploration

We introduce inference trees (ITs), a new class of inference methods tha...

2 Tom Rainforth, et al. ∙

∙ 09/14/2016

Relativistic Monte Carlo

Hamiltonian Monte Carlo (HMC) is a popular Markov chain Monte Carlo (MCM...

0 Xiaoyu Lu, et al. ∙

∙ 05/23/2016

Collaborative Filtering with Side Information: a Gaussian Process Perspective

We tackle the problem of collaborative filtering (CF) with side informat...

0 Hyunjik Kim, et al. ∙

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