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02/22/2022
On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization
Sequential model-based optimization sequentially selects a candidate poi...
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11/26/2020
Combinatorial Bayesian Optimization with Random Mapping Functions to Convex Polytope
Bayesian optimization is a popular method for solving the problem of glo...
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09/07/2020
Sparse Network Inversion for Key Instance Detection in Multiple Instance Learning
Multiple Instance Learning (MIL) involves predicting a single label for ...
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08/07/2020
Neural Complexity Measures
While various complexity measures for diverse model classes have been pr...
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05/28/2019
Discrete Infomax Codes for Meta-Learning
Learning compact discrete representations of data is itself a key task i...
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05/23/2019
Bayesian Optimization over Sets
We propose a Bayesian optimization method over sets, to minimize a black...
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05/18/2019
Practical Bayesian Optimization with Threshold-Guided Marginal Likelihood Maximization
We propose a practical Bayesian optimization method, of which the surrog...
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04/11/2019
MxML: Mixture of Meta-Learners for Few-Shot Classification
A meta-model is trained on a distribution of similar tasks such that it ...
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01/24/2019
On Local Optimizers of Acquisition Functions in Bayesian Optimization
Bayesian optimization is a sample-efficient method for finding a global ...
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10/03/2018
A Bayesian model for sparse graphs with flexible degree distribution and overlapping community structure
We consider a non-projective class of inhomogeneous random graph models ...
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10/01/2018
Set Transformer
Many machine learning tasks such as multiple instance learning, 3D shape...
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01/17/2018
Meta-Learning with Adaptive Layerwise Metric and Subspace
Recent advances in meta-learning demonstrate that deep representations c...
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10/17/2017
Learning to Warm-Start Bayesian Hyperparameter Optimization
Hyperparameter optimization undergoes extensive evaluations of validatio...
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02/27/2017
Bayesian inference on random simple graphs with power law degree distributions
We present a model for random simple graphs with a degree distribution t...
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04/18/2016
Gaussian Copula Variational Autoencoders for Mixed Data
The variational autoencoder (VAE) is a generative model with continuous ...
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11/18/2015
Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models
Normalized random measures (NRMs) provide a broad class of discrete rand...
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06/08/2015
Learning to Select Pre-Trained Deep Representations with Bayesian Evidence Framework
We propose a Bayesian evidence framework to facilitate transfer learning...
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06/03/2015
Bilinear Random Projections for Locality-Sensitive Binary Codes
Locality-sensitive hashing (LSH) is a popular data-independent indexing ...
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01/29/2015
Bayesian Hierarchical Clustering with Exponential Family: Small-Variance Asymptotics and Reducibility
Bayesian hierarchical clustering (BHC) is an agglomerative clustering me...
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01/16/2013