Seungjin Choi
19 papers · 2005–2022 · 7 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (44) π Academic Marathon Β· Full π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Gold π£ Hot Topic Early Bird
ποΈ
Keyword Collector
(95)
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Renaissance Researcher
(7)
π₯
Unstoppable Β· Bronze
π
Conference Pioneer
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Century Club Β· Bronze
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Trend Setter
Top co-authors
Research topics
Machine Learning
(13)
Artificial Intelligence
(12)
Optimization & Theory
(11)
Core Methods
(9)
Bayesian & Probabilistic Β· Artificial Intelligence
(7)
Bayesian & Probabilistic Β· Machine Learning
(6)
Learning Paradigms Β· Artificial Intelligence
(4)
Deep Learning
(3)
Mathematics & Optimization
(3)
Learning Types
(3)
Architectures
(2)
Learning Paradigms Β· Machine Learning
(2)
Optimization
(2)
Computer Science
(1)
Data Science & Analytics
(1)
Keywords
bayesian inference
(5)
bayesian nonparametrics
(3)
mixture model
(3)
variational inference
(3)
dirichlet process
(3)
hierarchical clustering
(2)
posterior inference
(2)
normalized random measure
(2)
gaussian process
(2)
few-shot learning
(2)
markov chain monte carlo
(2)
similarity search
(1)
anomaly detection
(1)
transfer learning
(1)
representation learning
(1)
attention mechanism
(1)
probabilistic modeling
(1)
collaborative filtering
(1)
clustering analysis
(1)
approximate inference
(1)
Papers
Combinatorial Bayesian optimization with random mapping functions to convex polytopes
UAI 2022
On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization
AISTATS 2022
Neural Complexity Measures
NeurIPS 2020
A Bayesian model for sparse graphs with flexible degree distribution and overlapping community structure
AISTATS 2019
Forward-Backward Generative Adversarial Networks for Anomaly Detection
ACML 2019
Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks
ICML 2019
Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace
ICML 2018
Bayesian inference on random simple graphs with power law degree distributions
ICML 2017
Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models
NeurIPS 2016
Learning to Select Pre-Trained Deep Representations With Bayesian Evidence Framework
CVPR 2016
Bayesian Hierarchical Clustering with Exponential Family: Small-Variance Asymptotics and Reducibility
AISTATS 2015
Bilinear Random Projections for Locality-Sensitive Binary Codes
CVPR 2015
Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models
NeurIPS 2015
Incremental Tree-Based Inference with Dependent Normalized Random Measures
AISTATS 2014
Scalable Variational Bayesian Matrix Factorization with Side Information
AISTATS 2014
Hierarchical Bayesian Matrix Factorization with Side Information
IJCAI 2013
Hierarchical Gaussian Process Regression
ACML 2010
Clustering sequence sets for motif discovery
NeurIPS 2009
Group Nonnegative Matrix Factorization for EEG Classification
AISTATS 2005