Vasilis Syrgkanis

Discipline

Economies et finances (35) Méthodes et statistiques (4)

Type de document

Textes imprimés (35)

Co-auteur

Date

Source

Mot-clé

science économique (35) Economics (35) statistiques (33) Statistics (33) Statistics (33) Machine learning (33) Econometrics (33) Statistics (33) Computer science (32) informatique (32) Mathematics (19) Mathematics (19) spectacle (18) Treatment (18) méthode (17) Inference (17) abords (agglomération) (16) Models (14) méthodologie (13) Methodology (13) Methods (13) Methodology (13) Methods (13) effet (12) Work (12) Learning (12) Example (12) Knowledge and learning (12) modèle (11) paramètre (10)

Documents écrit par Vasilis Syrgkanis (35) | parle de Vasilis Syrgkanis (0)

Dynamic Local Average Treatment Effects
Ravi B. Sojitra et al. (2 mai 2024)
Regularized DeepIV with Model Selection
Zihao Li et al. (7 mars 2024)
Applied Causal Inference Powered by ML and AI
Victor Chernozhukov et al. (4 mars 2024)
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
Jikai Jin et al. (21 févr. 2024)
Incentive-Aware Synthetic Control: Accurate Counterfactual Estimation via Incentivized Exploration
Daniel Ngo et al. (26 déc. 2023)
Learning Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity
Jikai Jin et al. (20 nov. 2023)
Causal Q-Aggregation for CATE Model Selection
Hui Lan et al. (25 oct. 2023)
Source Condition Double Robust Inference on Functionals of Inverse Problems
Andrew Bennett et al. (25 juil. 2023)
Inference on Optimal Dynamic Policies via Softmax Approximation
Qizhao Chen et al. (8 mars 2023)
Post-Episodic Reinforcement Learning Inference
Vasilis Syrgkanis et al. (17 févr. 2023)
Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness
Andrew Bennett et al. (10 févr. 2023)
Synthetic Blip Effects: Generalizing Synthetic Controls for the Dynamic Treatment Regime
Anish Agarwal et al. (20 oct. 2022)
Inference on Strongly Identified Functionals of Weakly Identified Functions
Andrew Bennett et al. (17 août 2022)
Debiased Machine Learning without Sample-Splitting for Stable Estimators
Qizhao Chen et al. (3 juin 2022)
Automatic Debiased Machine Learning for Dynamic Treatment Effects and General Nested Functionals
Victor Chernozhukov et al. (25 mars 2022)
Long Story Short: Omitted Variable Bias in Causal Machine Learning
Victor Chernozhukov et al. (26 déc. 2021)
Robust Generalized Method of Moments: A Finite Sample Viewpoint
Dhruv Rohatgi et al. (6 oct. 2021)
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests
Victor Chernozhukov et al. (6 oct. 2021)
Automatic Debiased Machine Learning via Riesz Regression
Victor Chernozhukov et al. (29 avr. 2021)
Estimating the Long-Term Effects of Novel Treatments
Keith Battocchi et al. (15 mars 2021)
Finding Subgroups with Significant Treatment Effects
Jann Spiess et al. (11 mars 2021)
Adversarial Estimation of Riesz Representers
Victor Chernozhukov et al. (30 déc. 2020)
Minimax Estimation of Conditional Moment Models
Nishanth Dikkala et al. (12 juin 2020)
Double/Debiased Machine Learning for Dynamic Treatment Effects via g-Estimation
Greg Lewis et al. (17 févr. 2020)
Multi-item Non-truthful Auctions Achieve Good Revenue
Constantinos Daskalakis et al. (16 févr. 2020)

next