Henry Lam
18 papers · 2013–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (7) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (10) π§ Keyword Pioneer π Academic Marathon (12)
π
Interdisciplinary Bridge
π
Conference Polyglot
(7)
π
Academic Marathon
(12)
ποΈ
Keyword Collector
(79)
β‘
Prolific Year
(7)
π
Century Club
(18)
π₯
Unstoppable
(6)
β
The Questioner
Conferences
AISTATS (7)
NIPS (4)
ICLR (2)
ICML (2)
ACML (1)
JMLR (1)
UAI (1)
Top co-authors
Research topics
Keywords
uncertainty quantification
(3)
ambiguity set
(2)
generalization bound
(2)
distributionally robust optimization
(2)
empirical risk minimization
(2)
bayesian inference
(2)
importance sampling
(2)
stochastic gradient descent
(1)
reinforcement learning
(1)
stochastic optimization
(1)
policy optimization
(1)
ensemble learning
(1)
approximate inference
(1)
model misspecification
(1)
online learning
(1)
neural tangent kernel
(1)
high-dimensional statistics
(1)
community detection
(1)
signal processing
(1)
statistical inference
(1)
Papers
MallowsPO: Fine-Tune Your LLM with Preference Dispersions
ICLR 2025
Dissecting the Impact of Model Misspecification in Data-Driven Optimization
AISTATS 2025
Learning from Sparse Offline Datasets via Conservative Density Estimation
ICLR 2024
Is Cross-validation the Gold Standard to Estimate Out-of-sample Model Performance?
NIPS 2024
Detection of Short-Term Temporal Dependencies in Hawkes Processes with Heterogeneous Background Dynamics
UAI 2023
Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework
NIPS 2023
Efficient Uncertainty Quantification and Reduction for Over-Parameterized Neural Networks
NIPS 2023
Hedging against Complexity: Distributionally Robust Optimization with Parametric Approximation
AISTATS 2023
Group Distributionally Robust Reinforcement Learning with Hierarchical Latent Variables
AISTATS 2023
Bootstrap in High Dimension with Low Computation
ICML 2023
Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous Bias-Variance Reduction and Supercanonical Convergence
JMLR 2023
Generalization Bounds with Minimal Dependency on Hypothesis Class via Distributionally Robust Optimization
NIPS 2022
Deep Probabilistic Accelerated Evaluation: A Robust Certifiable Rare-Event Simulation Methodology for Black-Box Safety-Critical Systems
AISTATS 2021
Learning Prediction Intervals for Regression: Generalization and Calibration
AISTATS 2021
Robust Importance Weighting for Covariate Shift
AISTATS 2020
Constrained Reinforcement Learning via Policy Splitting
ACML 2020
A Bayesian Framework for Online Classifier Ensemble
ICML 2014
Why Steiner-tree type algorithms work for community detection
AISTATS 2013