Vasilis Syrgkanis

41 papers · 2015–2025 · 7 conferences · across top CS/AI conferences

Achievements

+13 more ↓

🌍 Conference Polyglot (7) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (18) 🏃 Academic Marathon (10)

🗺️ Taxonomy Completionist (18) 🧭 Keyword Pioneer 🏃 Academic Marathon (10) 👑 Triple Crown 🌱 Topic Pioneer 🔬 Deep Specialist (16) 🏆 Keyword Champion (5) 🚀 Conference Pioneer 🗃️ Keyword Collector (169) ⚡ Prolific Year (6) 💎 Century Club (41) 🔥 Unstoppable (11) 📈 Trend Setter

Conferences

NIPS (19) ICML (8) COLT (6) ICLR (4) CLEAR (2) AISTATS (1) IJCAI (1)

Top co-authors

Greg Lewis (6) Lester Mackey (3) Miruna Oprescu (3) Whitney Newey (3) Akshay Krishnamurthy (3) Zhiwei Steven Wu (3) Ioannis Mitliagkas (2) Morgane Austern (2) Andrew Bennett (2) Dylan J. Foster (2)

Keywords

causal inference (14) instrumental variable (5) statistical learning (5) regret bound (5) treatment effect (5) heterogeneous treatment effect (4) asymptotic normality (4) game theory (4) confidence interval (3) contextual bandit (3) neyman orthogonality (3) random forest (2) sample splitting (2) model selection (2) instrumental variable regression (2) structural causal model (2) domain adaptation (2) excess risk (2) sample complexity (2) partial identification (2)

Papers

Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation (Extended Abstract) COLT 2025 A Meta-learner for Heterogeneous Effects in Difference-in-Differences ICML 2025 Orthogonal Causal Calibration (Extended Abstract) COLT 2025 Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation ICLR 2024 Causal Q-Aggregation for CATE Model Selection AISTATS 2024 Consistency of Neural Causal Partial Identification NIPS 2024 Learning Linear Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity NIPS 2024 Adaptive Instrument Design for Indirect Experiments ICLR 2024 Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity NIPS 2024 Inference on Strongly Identified Functionals of Weakly Identified Functions COLT 2023 Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness COLT 2023 Non-parametric Inference Adaptive to Intrinsic Dimension CLEAR 2022 RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests ICML 2022 Debiased Machine Learning without Sample-Splitting for Stable Estimators NIPS 2022 Robust Generalized Method of Moments: A Finite Sample Viewpoint NIPS 2022 Partial Identification of Treatment Effects with Implicit Generative Models NIPS 2022 Towards efficient representation identification in supervised learning CLEAR 2022 Asymptotics of the Bootstrap via Stability with Applications to Inference with Model Selection NIPS 2021 Estimating the Long-Term Effects of Novel Treatments NIPS 2021 Knowledge Distillation as Semiparametric Inference ICLR 2021 Incentivizing Compliance with Algorithmic Instruments ICML 2021 Double/Debiased Machine Learning for Dynamic Treatment Effects NIPS 2021 Statistical Learning with a Nuisance Component (Extended Abstract) IJCAI 2020 Minimax Estimation of Conditional Moment Models NIPS 2020 Estimation and Inference with Trees and Forests in High Dimensions COLT 2020 Orthogonal Random Forest for Causal Inference ICML 2019 Statistical Learning with a Nuisance Component COLT 2019 Low-Rank Bandit Methods for High-Dimensional Dynamic Pricing NIPS 2019 Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments NIPS 2019 Semi-Parametric Efficient Policy Learning with Continuous Actions NIPS 2019 Accurate Inference for Adaptive Linear Models ICML 2018 Training GANs with Optimism ICLR 2018 Semiparametric Contextual Bandits ICML 2018 Orthogonal Machine Learning: Power and Limitations ICML 2018 Robust Optimization for Non-Convex Objectives NIPS 2017 Welfare Guarantees from Data NIPS 2017 A Sample Complexity Measure with Applications to Learning Optimal Auctions NIPS 2017 Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits NIPS 2016 Efficient Algorithms for Adversarial Contextual Learning ICML 2016 Fast Convergence of Regularized Learning in Games NIPS 2015 No-Regret Learning in Bayesian Games NIPS 2015