ICML에 나온 Gaussian process

IN 

ICML 2010 

총 152개의 논문 

1. Gaussian Process Change Point Models

2. Surrogating the surrogate: accelerating Gaussian-process-based global optimization with a mixture cross-entropy algorithm

3. Gaussian Covariance and Scalable Variational Inference

4. Gaussian Processes Multiple Instance Learning

5. Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

6. Sparse Gaussian Process Regression via $\ell_1$ Penalization

ICML 2011 

총 180개의 논문

1. Variational Heteroscedastic Gaussian Process Regression (Distinguished Paper Awards)

2. Probabilistic Matrix Addition 

ICML 2012

총 249개의 논문

1. Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations

2. Gaussian Process Regression Networks 

3. Gaussian Process Quantile Regression using Expectation Propagation 

4. Joint Optimization and Variable Selection of High-dimensional Gaussian Processes

5. Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization

ICML 2013

총 270r개의 논문

1. Gaussian Process Kernels for Pattern Discovery and Extrapolation

2. Scaling Multidimensional Gaussian Processes using Projected Additive Approximations

3. Nonparametric Mixture of Gaussian Processes with Constraints

4. Gaussian Process Vine Copulas for Multivariate Dependence

ICML 2014

총 312

1. Fast Allocation of Gaussian Process Experts

2. Nonmyopic $\epsilon$-Bayes-Optimal Active Learning of Gaussian Processes

3. Sample Efficient Reinforcement Learning with Gaussian Processes

4. Gaussian Processes for Bayesian Estimation in Ordinary Differential Equations

5. Gaussian Process Optimization with Mutual Information

6. Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications

7. Gaussian Process Classification and Active Learning with Multiple Annotators

 Track C - Bayesian Optimization and Gaussian Processes (Location: 201-2, Chair: Max Welling)

8. Agnostic Bayesian Learning of Ensembles

9. Robust RegBayes: Selectively Incorporating First-Order Logic Domain Knowledge into Bayesian Models

10. An Efficient Approach for Assessing Hyperparameter Importance

11. Bayesian Optimization with Inequality Constraints

12. A PAC-Bayesian bound for Lifelong Learning