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Results of search for 'au:"Malinsky, Daniel"'
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Bhattacharya, Rohit
Malinsky, Daniel
Nabi, Razieh
Richardson, Thomas
Shpitser, Ilya
Spirtes, Peter
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1.
Estimating bounds on causal effects in high-dimensional and possibly confounded systems.
[electronic resource]
by
Malinsky, Daniel
Spirtes, Peter
Publication details:
International journal of approximate reasoning : official publication of the North American Fuzzy Information Processing Society
Sep 2017
In:
International journal of approximate reasoning : official publication of the North American Fuzzy Information Processing Society
vol. 88
Online resources:
Available from publisher's website
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2.
Estimating Causal Effects with Ancestral Graph Markov Models.
[electronic resource]
by
Malinsky, Daniel
Spirtes, Peter
Publication details:
JMLR workshop and conference proceedings
Aug 2016
In:
JMLR workshop and conference proceedings
vol. 52
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3.
Learning the Structure of a Nonstationary Vector Autoregression.
[electronic resource]
by
Malinsky, Daniel
Spirtes, Peter
Publication details:
Proceedings of machine learning research
Apr 2019
In:
Proceedings of machine learning research
vol. 89
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4.
Causal Inference Under Interference And Network Uncertainty.
[electronic resource]
by
Bhattacharya, Rohit
Malinsky, Daniel
Shpitser, Ilya
Publication details:
Uncertainty in artificial intelligence : proceedings of the ... conference. Conference on Uncertainty in Artificial Intelligence
Jul 2019
In:
Uncertainty in artificial intelligence : proceedings of the ... conference. Conference on Uncertainty in Artificial Intelligence
vol. 2019
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5.
A Potential Outcomes Calculus for Identifying Conditional Path-Specific Effects.
[electronic resource]
by
Malinsky, Daniel
Shpitser, Ilya
Richardson, Thomas
Publication details:
Proceedings of machine learning research
Apr 2019
In:
Proceedings of machine learning research
vol. 89
Availability:
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6.
Learning Optimal Fair Policies.
[electronic resource]
by
Nabi, Razieh
Malinsky, Daniel
Shpitser, Ilya
Publication details:
Proceedings of machine learning research
Jun 2019
In:
Proceedings of machine learning research
vol. 97
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