Lawrence K. Saul
17 papers · 2003–2025 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (42) π Academic Marathon Β· Ultra π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Topic Pioneer
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Keyword Champion
(3)
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Keyword Pioneer
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Keyword Trendsetter Combo
(7)
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Century Club Β· Bronze
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Unstoppable Β· Bronze
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Conference Pioneer
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Renaissance Researcher
(6)
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Keyword Collector
(93)
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Research topics
Machine Learning
(16)
Optimization & Theory
(10)
Core Methods
(9)
Deep Learning
(8)
Learning Types
(6)
Models
(6)
Artificial Intelligence
(5)
Bayesian & Probabilistic Β· Machine Learning
(4)
Bayesian & Probabilistic Β· Artificial Intelligence
(3)
Mathematics & Optimization
(2)
Core AI
(2)
Optimization
(2)
Computer Science
(1)
Computer Vision
(1)
Data Science & Analytics
(1)
Keywords
variational inference
(5)
dimensionality reduction
(4)
semidefinite programming
(3)
gaussian approximation
(3)
bayesian inference
(3)
manifold learning
(2)
convex optimization
(2)
factor analysis
(2)
black-box variational inference
(2)
latent variable model
(2)
score matching
(2)
kullback-leibler divergence
(2)
low-rank approximation
(2)
distance metric learning
(2)
matrix factorization
(1)
large-scale optimization
(1)
probabilistic modeling
(1)
regularization
(1)
margin-based learning
(1)
graph laplacian
(1)
Papers
Batch, match, and patch: low-rank approximations for score-based variational inference
AISTATS 2025
Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs
JMLR 2025
Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix
AISTATS 2025
Batch and match: black-box variational inference with a score-based divergence
ICML 2024
EigenVI: score-based variational inference with orthogonal function expansions
NeurIPS 2024
The Shrinkage-Delinkage Trade-off: an Analysis of Factorized Gaussian Approximations for Variational Inference
UAI 2023
Variational Inference with Gaussian Score Matching
NeurIPS 2023
An online passive-aggressive algorithm for difference-of-squares classification
NeurIPS 2021
eDoctor: Automatically Diagnosing Abnormal Battery Drain Issues on Smartphones
NSDI 2013
Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning
NeurIPS 2012
Maximum Covariance Unfolding : Manifold Learning for Bimodal Data
NeurIPS 2011
Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development
NeurIPS 2010
Distance Metric Learning for Large Margin Nearest Neighbor Classification
JMLR 2009
Kernel Methods for Deep Learning
NeurIPS 2009
Graph Laplacian Regularization for Large-Scale Semidefinite Programming
NeurIPS 2006
Large Margin Hidden Markov Models for Automatic Speech Recognition
NeurIPS 2006
Think Globally, Fit Locally: Unsupervised Learning of Low Dimensional Manifolds
JMLR 2003