About
 

Sara Magliacane

Affiliated Professor

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Who they work with

Categories

Causal Inference Machine Learning

For the past six years I have worked in various fields of Computer Science research, from databases, to Semantic web, distributed systems and machine learning. I just finished a PhD degree on the topic of causality and probabilistic logics at the VU University Amsterdam and the University of Amsterdam. During my PhD I did two internships, one in Google Zurich and one in Google Research in New York. I previously studied Computer Engineering at the University of Trieste, at Politecnico di Milano and Alta Scuola Politecnica.

Top Work

Causal inference is expensive. Here’s an algorithm for fixing that.

Causal inference is expensive. Here’s an algorithm for fixing that.

Causal Inference

Publications with the MIT-IBM Watson AI Lab

Factored Adaptation for Non-stationary Reinforcement Learning
Factored Adaptation for Non-stationary Reinforcement Learning
NeurIPSReinforcement Learning
 
AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning
AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning
ICLRReinforcement Learning
 
Active Structure Learning of Causal DAGs via Directed Clique Trees
Active Structure Learning of Causal DAGs via Directed Clique Trees
Causal Inference
 
Sample Efficient Active Learning of Causal Trees
Sample Efficient Active Learning of Causal Trees
NeurIPS
 
Causal inference is expensive. Here’s an algorithm for fixing that.
Causal inference is expensive. Here’s an algorithm for fixing that.
Causal Inference
 
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
Causal Inference