Patrick Thiran
14 papers · 2017–2025 · 5 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (42) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Gold π£ Hot Topic Early Bird
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Keyword Champion
(2)
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Renaissance Researcher
(5)
π₯
Unstoppable Β· Bronze
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Prolific Year Β· Productive
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Century Club Β· Bronze
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Keyword Collector
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Research topics
Machine Learning
(13)
Optimization & Theory
(11)
Mathematics & Optimization
(10)
Optimization
(7)
Artificial Intelligence
(5)
Learning Types
(5)
Mathematics
(4)
Deep Learning
(3)
Bayesian & Probabilistic Β· Machine Learning
(3)
Core AI
(3)
Core Methods
(3)
Computer Science
(2)
Data Science & Analytics
(2)
Bayesian & Probabilistic Β· Artificial Intelligence
(2)
Foundations
(2)
Keywords
variational inference
(2)
sample complexity
(2)
multivariate hawkes process
(2)
bayesian optimization
(2)
stochastic optimization
(2)
causal structure
(2)
stochastic process
(2)
event sequence
(2)
bayesian inference
(2)
point process
(2)
stochastic gradient descent
(1)
decentralized optimization
(1)
community detection
(1)
image denoising
(1)
reinforcement learning
(1)
unsupervised learning
(1)
sparse representation
(1)
causal inference
(1)
label noise
(1)
bregman divergence
(1)
Papers
Learn to Vaccinate: Combining Structure Learning and Effective Vaccination for Epidemic and Outbreak Control
ICML 2025
Fast Proxy Experiment Design for Causal Effect Identification
NeurIPS 2024
Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization
ICLR 2024
This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian Optimization
NeurIPS 2024
Universal Lower Bounds and Optimal Rates: Achieving Minimax Clustering Error in Sub-Exponential Mixture Models
COLT 2024
Why the Metric Backbone Preserves Community Structure
NeurIPS 2024
Leveraging Unlabeled Data to Track Memorization
ICLR 2023
Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Functions
NeurIPS 2022
A Variational Inference Approach to Learning Multivariate Wold Processes
AISTATS 2021
Cumulants of Hawkes Processes are Robust to Observation Noise
ICML 2021
Learning Hawkes Processes from a handful of events
NeurIPS 2019
Learning Hawkes Processes Under Synchronization Noise
ICML 2019
Coordinate Descent with Bandit Sampling
NeurIPS 2018
Dictionary Learning Based on Sparse Distribution Tomography
ICML 2017