DSA ADS Course - 2021
Causality, Causal Reasoning, Causal Inference, Machine Learning, Algorithms
Discuss causality and machine learning - contrast with statistical correlations.
The Seven Tools of Causal Inference, with Reflections on Machine Learning - March, 2019 By Judea Pearl
DSA ADS Course - 2021
Algorithms for Causal Reasoning in Probability Trees
Causality, Algorithms, Causal Reasoning, Probability Trees, Machine Learning
October, 2020
Abstract
DSA ADS Course - 2021
The Sure-Thing Principle, Causal Reasoning, Data-Driven Decision-Making, Algorithm Decision Making, Applied Probability, Nonlinear Utility Scale, Simpson’s Paradox, Blyth’s Game
Discuss applied probability, causal reasoning and types of decision making processes. Apply to both traditional algorithms and machine learning algorithms in decision making processes.
See also: The Sure-Thing Principle
The Sure Thing - 2021
Abstract
DSA ADS Course - 2021
The Sure-Thing Principle, Causal Reasoning, Data-Driven Decision-Making, Algorithm Decision Making, Applied Probability
Discuss applied probability, causal reasoning and types of decision making processes. Apply to both traditional algorithms and machine learning algorithms in decision making processes.
See also: The Sure Thing
The Sure-Thing Principle - 2016
Abstract
October, 2020
Abstract
This paper proposes a formal framework for modeling the interaction of causal and (qualitative) epistemic reasoning. To this purpose, we extend the notion of a causal model [16, 17, 26, 11] with a representation of the epistemic state of an agent. On the side of the object language, we add operators to express knowledge and the act of observing new information. We provide a sound and complete axiomatization of the logic, and discuss the relation of this framework to causal team semantics.