Dave Zachariah
13 papers · 2017–2025 · 5 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+7 more ↓ Show less ↑
๐งญ Keyword Pioneer ๐ Interdisciplinary Bridge ๐ Conference Polyglot (5) ๐ Academic Marathon (8) ๐ Cross-Pollinator (13)
๐
Interdisciplinary Bridge
๐
Conference Polyglot
(5)
๐
Academic Marathon
(8)
๐
Century Club
(13)
๐
Trend Setter
๐๏ธ
Keyword Collector
(53)
๐ฅ
Unstoppable
(9)
Conferences
NIPS (5)
AISTATS (3)
ICML (3)
ICLR (1)
UAI (1)
Top co-authors
Keywords
uncertainty quantification
(3)
observational datum
(2)
causal effect inference
(2)
conformal prediction
(2)
pareto efficiency
(1)
domain adaptation
(1)
robust optimization
(1)
ridge regression
(1)
risk management
(1)
adversarial training
(1)
model calibration
(1)
decision policy
(1)
gaussian process regression
(1)
multi-class classification
(1)
linear regression
(1)
cramรฉr-rao bound
(1)
sequential learning
(1)
sequential prediction
(1)
multi-objective optimization
(1)
policy evaluation
(1)
Papers
Efficient Optimization Algorithms for Linear Adversarial Training
AISTATS 2025
Adaptive Robust Learning using Latent Bernoulli Variables
ICML 2024
Externally Valid Policy Evaluation from Randomized Trials Using Additional Observational Data
NIPS 2024
Regularization properties of adversarially-trained linear regression
NIPS 2023
Learning Pareto-Efficient Decisions with Confidence
AISTATS 2022
Inference of causal effects when control variables are unknown
UAI 2021
Calibration tests beyond classification
ICLR 2021
Learning Robust Decision Policies from Observational Data
NIPS 2020
Calibration tests in multi-class classification: A unifying framework
NIPS 2019
Inferring Heterogeneous Causal Effects in Presence of Spatial Confounding
ICML 2019
Prediction of Spatial Point Processes: Regularized Method with Out-of-Sample Guarantees
NIPS 2019
Learning Localized Spatio-Temporal Models From Streaming Data
ICML 2018
Prediction Performance After Learning in Gaussian Process Regression
AISTATS 2017