Jonathan Huggins
13 papers · 2009–2021 · 4 conferences · across top CS/AI conferences
Achievements
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🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (4) 🏃 Academic Marathon (12) 🐣 Hot Topic Early Bird
🌈
Renaissance Researcher
(5)
🌉
Interdisciplinary Bridge
🌍
Conference Polyglot
(4)
🔬
Deep Specialist
(10)
🌱
Topic Pioneer
💎
Century Club
(13)
🔥
Unstoppable
(7)
📈
Trend Setter
Conferences
NIPS (5)
ICML (4)
AISTATS (3)
CONLL (1)
Top co-authors
Keywords
bayesian inference
(6)
markov chain monte carlo
(6)
posterior approximation
(3)
variational inference
(2)
generalized linear model
(2)
logistic regression
(2)
posterior inference
(2)
uncertainty quantification
(2)
laplace approximation
(2)
importance sampling
(2)
low-rank approximation
(1)
kernel approximation
(1)
stochastic optimization
(1)
high-dimensional inference
(1)
approximate bayesian inference
(1)
stochastic gradient descent
(1)
diffusion process
(1)
feature selection
(1)
gaussian process
(1)
langevin dynamics
(1)
Papers
Challenges and Opportunities in High Dimensional Variational Inference
NIPS 2021
Robust, Accurate Stochastic Optimization for Variational Inference
NIPS 2020
Validated Variational Inference via Practical Posterior Error Bounds
AISTATS 2020
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations
ICML 2019
Data-dependent compression of random features for large-scale kernel approximation
AISTATS 2019
The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions
ICML 2019
Random Feature Stein Discrepancies
NIPS 2018
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference
NIPS 2017
Quantifying the accuracy of approximate diffusions and Markov chains
AISTATS 2017
Coresets for Scalable Bayesian Logistic Regression
NIPS 2016
JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes
ICML 2015
Risk and Regret of Hierarchical Bayesian Learners
ICML 2015
A simple feature-copying approach for long-distance dependencies
CONLL 2009