Erik Sudderth
8 papers · 2013–2018 · 3 venues · across top CS/AI venues
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Achievements
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π Conference Polyglot Β· Bronze π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (28) π£ Hot Topic Early Bird
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Renaissance Researcher
(6)
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(56)
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Trend Setter
Venues
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Research topics
Machine Learning
(8)
Optimization & Theory
(7)
Artificial Intelligence
(6)
Bayesian & Probabilistic Β· Machine Learning
(5)
Learning Types
(5)
Deep Learning
(4)
Bayesian & Probabilistic Β· Artificial Intelligence
(4)
Core Methods
(3)
Models
(3)
Core AI
(2)
Computer Vision
(1)
Data Science & Analytics
(1)
Healthcare & Medicine
(1)
Mathematics & Optimization
(1)
Natural Language Processing
(1)
Keywords
variational inference
(5)
bayesian nonparametrics
(3)
hierarchical dirichlet process
(3)
stochastic variational inference
(2)
graphical model
(2)
nonparametric model
(2)
online learning
(2)
topic model
(2)
text analysis
(1)
latent dirichlet allocation
(1)
dirichlet process
(1)
belief propagation
(1)
neural decoding
(1)
mode estimation
(1)
particle filtering
(1)
network analysis
(1)
semi-supervised learning
(1)
markov chain monte carlo
(1)
brain-computer interface
(1)
probabilistic modeling
(1)
Papers
Semi-Supervised Prediction-Constrained Topic Models
AISTATS 2018
Multiscale Semi-Markov Dynamics for Intracortical Brain-Computer Interfaces
NeurIPS 2017
Proteins, Particles, and Pseudo-Max-Marginals: A Submodular Approach
ICML 2015
Reliable and Scalable Variational Inference for the Hierarchical Dirichlet Process
AISTATS 2015
Scalable Adaptation of State Complexity for Nonparametric Hidden Markov Models
NeurIPS 2015
Preserving Modes and Messages via Diverse Particle Selection
ICML 2014
Efficient Online Inference for Bayesian Nonparametric Relational Models
NeurIPS 2013
Memoized Online Variational Inference for Dirichlet Process Mixture Models
NeurIPS 2013