Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation
On 19 May, 2021 By admin 0 Comments
External Course
Causality for Machine Learning
On 19 May, 2021 By admin 0 Comments
December, 2019
Abstract
Graphical causal inference as pioneered by Judea Pearl arose from research on artificial intelligence (AI), and for a long time had little connection to the field of machine learning.
This article discusses where links have been and should be established, introducing key concepts along the way. It argues that the hard open problems of machine learning and AI are intrinsically related to causality, and explains how the field is beginning to understand them.
Graphical Depiction of Statistical Information Improves Gambling-Related Judgments
On 19 May, 2021 By admin 0 Comments
Reflection on modern methods: understanding bias and data analytical strategies through DAG-based data simulations
On 19 May, 2021 By admin 0 Comments
Tutorial on Fairness of Machine Learning in Recommender Systems
On 19 May, 2021 By admin 0 Comments
Causal Diagrams for Epidemiologic Research
On 19 May, 2021 By admin 0 Comments
On the Interpretation of do(x)
On 19 May, 2021 By admin 0 Comments
February, 2019
Abstract
Cooperative Inverse Reinforcement Learning
On 17 May, 2021 By admin 0 Comments
DSA ADS Course - 2021
Dylan Hadfield-Menell · Stuart J Russell · Pieter Abbeel · Anca Dragan
November, 2016
Abstract:
Foundations of Intelligence in Natural and Artificial Systems: A Workshop Report
On 16 May, 2021 By admin 0 Comments
BEYOND REWARD AND PUNISHMENT
On 16 May, 2021 By admin 0 Comments
DSA External Course
BEYOND REWARD AND PUNISHMENT David Deutsch
Creating AI