
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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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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Neural Complexity Measures
While various complexity measures for diverse model classes have been pr...
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Discrete Infomax Codes for MetaLearning
Learning compact discrete representations of data is itself a key task i...
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Bayesian Optimization over Sets
We propose a Bayesian optimization method over sets, to minimize a black...
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Practical Bayesian Optimization with ThresholdGuided Marginal Likelihood Maximization
We propose a practical Bayesian optimization method, of which the surrog...
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MxML: Mixture of MetaLearners for FewShot Classification
A metamodel is trained on a distribution of similar tasks such that it ...
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On Local Optimizers of Acquisition Functions in Bayesian Optimization
Bayesian optimization is a sampleefficient method for finding a global ...
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A Bayesian model for sparse graphs with flexible degree distribution and overlapping community structure
We consider a nonprojective class of inhomogeneous random graph models ...
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Set Transformer
Many machine learning tasks such as multiple instance learning, 3D shape...
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MetaLearning with Adaptive Layerwise Metric and Subspace
Recent advances in metalearning demonstrate that deep representations c...
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Learning to WarmStart Bayesian Hyperparameter Optimization
Hyperparameter optimization undergoes extensive evaluations of validatio...
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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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Gaussian Copula Variational Autoencoders for Mixed Data
The variational autoencoder (VAE) is a generative model with continuous ...
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TreeGuided MCMC Inference for Normalized Random Measure Mixture Models
Normalized random measures (NRMs) provide a broad class of discrete rand...
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Learning to Select PreTrained Deep Representations with Bayesian Evidence Framework
We propose a Bayesian evidence framework to facilitate transfer learning...
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Bilinear Random Projections for LocalitySensitive Binary Codes
Localitysensitive hashing (LSH) is a popular dataindependent indexing ...
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Bayesian Hierarchical Clustering with Exponential Family: SmallVariance Asymptotics and Reducibility
Bayesian hierarchical clustering (BHC) is an agglomerative clustering me...
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Regularized Discriminant Embedding for Visual Descriptor Learning
Images can vary according to changes in viewpoint, resolution, noise, an...
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Seungjin Choi
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