Tamara Broderick
32 papers · 2013–2025 · 5 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 3 separate collaboration groups - the largest holds only 44% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Tamara Broderick?
3 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Trevor Campbell, Jonathan Huggins, Raj Agrawal
14 papers
· 2016–2023
· ICML, NeurIPS, AISTATS
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The SKIM-FA Kernel: High-Dimensional Variable Selection and Nonlinear Interaction Discovery in Linear Time
JMLR 2023
Finite mixture models do not reliably learn the number of components
ICML 2021
For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets
NeurIPS 2021
Validated Variational Inference via Practical Posterior Error Bounds
AISTATS 2020
Automated Scalable Bayesian Inference via Hilbert Coresets
JMLR 2019
Data-dependent compression of random features for large-scale kernel approximation
AISTATS 2019
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations
ICML 2019
Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees
AISTATS 2019
The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions
ICML 2019
Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent
ICML 2018
Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models
ICML 2018
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference
NeurIPS 2017
Coresets for Scalable Bayesian Logistic Regression
NeurIPS 2016
Edge-exchangeable graphs and sparsity
NeurIPS 2016