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Estimand-Agnostic Causal Query Estimation with Deep Causal Graphs

Alvaro Parafita, Jordi Vitria
2022 IEEE Access  
We follow the experimental setup and results from [29] , and focus on four metrics: e AT E , absolute error in the Average Treatment Effect (ATE); e P EHE , RSME in the Individual Treatment Effect (ITE  ...  , Balancing Neural Networks (BNN) [8] , Treatment-Agnostic Representation Network (TAR) [29] , Counterfactual Regression (CFR) [29] , Adaptively similarity-preserved representation learning for We expect  ...  Causal Effect estimation (ACE) 7 [40] , Subspace Learning Based Counterfactual Inference (SCI) [41] and Causal Optimal Transport (CausalOT) 8 [13] .  ... 
doi:10.1109/access.2022.3188395 fatcat:d4y3mxwvxjfojm6rki2wevuuju

Are GCMs obsolete? [article]

V. Balaji, Fleur Couvreux, Julie Deshayes, Jacques Gautrais, Frédéric Hourdin, Catherine Rio
2022 arXiv   pre-print
We consider these shortcomings in the context of a future generation of models that may address these issues through substantially higher resolution and detail, or through the use of machine learning techniques  ...  Traditional general circulation models, or GCMs -- i.e. 3D dynamical models with unresolved terms represented in equations with tunable parameters -- have been a mainstay of climate research for several  ...  Acknowledgments VB is supported by the Cooperative Institute for Modeling the Earth System, Princeton University (Award NA18OAR4320123 from the National Oceanic and Atmospheric Administration, U.S.  ... 
arXiv:2204.06957v1 fatcat:mn2me3zfdbhvtnimalruuf3lwm

37th Annual Meeting of the Society for Mathematical Psychology

2005 Journal of Mathematical Psychology  
For exponential families, and more generally for dually flat manifolds, the divergence possess a (dual) Pythagorean relationship that is useful for giving geometric expression to maximum likelihood estimation  ...  theoretical properties such as parameter estimates that are sufficient.  ...  Sci., 2003] , any TxtFex 1 -learnable class C can be so learned without recourse to U-shaped learning behavior.  ... 
doi:10.1016/ fatcat:buxuwbxh7vdrppbqnuma7b5mje

A Survey on Bias in Deep NLP

Ismael Garrido-Muñoz, Arturo Montejo-Ráez, Fernando Martínez-Santiago, L. Alfonso Ureña-López
2021 Applied Sciences  
"), versatile and performing models are released continuously for every new network design.  ...  Deep neural networks are hegemonic approaches to many machine learning areas, including natural language processing (NLP).  ...  In machine learning evaluation, discrimination can be estimated looking at the confusion matrices for different protected groups.  ... 
doi:10.3390/app11073184 fatcat:cdaihoicdzeolovw77yltdmpeq

Randomized Markdowns and Online Monitoring

Ken Moon, Kostas Bimpikis, Haim Mendelson
2018 Management science  
Our estimation results have important implications for retail operations.  ...  We develop a structural model of consumers' dynamic monitoring to find substantial heterogeneity, with consumers' opportunity costs for an online visit ranging from $2 to $25 in inverse relation to their  ...  For estimation, Proposition 1 allows us to search only the subspace of Markov stationary strategy profiles, while immediately implying that any equilibrium found in this subspace remains a valid equilibrium  ... 
doi:10.1287/mnsc.2016.2661 fatcat:mowrud6adbhhpdty3c2hbl3s7i

Semi-Supervised Off Policy Reinforcement Learning [article]

Aaron Sonabend-W, Nilanjana Laha, Ashwin N. Ananthakrishnan, Tianxi Cai, Rajarshi Mukherjee
2021 arXiv   pre-print
Reinforcement learning (RL) has shown great success in estimating sequential treatment strategies which take into account patient heterogeneity.  ...  Generalizing SSL to sequential treatment regimes brings interesting challenges: 1) Feature distribution for Q-learning is unknown as it includes previous outcomes. 2) The surrogate variables we leverage  ...  Q-and A-learning methods for estimating optimal dynamic treatment regimes. Statist. Sci., 29(4):640-661, 11 2014. doi: 10.1214/13-STS450. URL 13-STS450.  ... 
arXiv:2012.04809v5 fatcat:szfryhgwbza7fo22tltxasr7yu

Algorithmic Fairness Datasets: the Story so Far [article]

Alessandro Fabris, Stefano Messina, Gianmaria Silvello, Gian Antonio Susto
2022 arXiv   pre-print
Progress in fair Machine Learning hinges on data, which can be appropriately used only if adequately documented.  ...  Moreover we rigorously identify the three most popular fairness datasets, namely Adult, COMPAS and German Credit, for which we compile in-depth documentation.  ...  Acknowledgements The authors would like to thank the following researchers and dataset creators for the useful feedback on the data briefs: Alain Barrat, Luc Behaghel, Asia Biega, Marko Bohanec, Chris  ... 
arXiv:2202.01711v3 fatcat:kd546yklwjhvtkrbhtzgbzb2xm

Conference Program

2021 2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)  
His research experience falls within the areas of risk management, data mining, alternative contracting methods, preconstruction/construction cost estimating, asset management, and decision-making procedures  ...  Lina has received a research grant from Prince Mohammad Bin Fahd Center for Futuristic Studies (PMFCFS) and World Futures Studies Federation (WFSF).  ...  Lina is from Saudi Arabia and has been working as a faculty member within the College of Sciences and Human Studies at Prince Mohammad Bin Fahd University for more than 6 years.  ... 
doi:10.1109/3ict53449.2021.9581455 fatcat:zgaclsoapjbhbmjmki7bjltre4

Abstracts of Working Papers in Economics

1997 Abstracts of Working Papers in Economics  
AB This paper reports quarterly ex ante forecasts of macroeconomic activity for the U.S.A., Japan and Australia for the period 1995 -1997.  ...  The forecasts are based on automated time series models of vector autoregressions (VAR's), reduced rank regressions (RRR's), error correction models (ECM's) and Bayesian vector autoregressions (BVAR's)  ...  The evaluation is based on a randomized design that will follow 6,000 individuals for five years.  ... 
doi:10.1017/s0951007900003508 fatcat:sjk3leigpvgdfeuxuh5dsgiuaa

Pathological Outcomes of Observational Learning

Lones Smith, Peter Sorensen
2000 Econometrica  
The usenet group sci. math. research has also proved invaluable. All errors remain our responsibility.  ...  It may well be impossible to draw any further inference from history even while it continues to accumulate privately-informed decisions!  ...  If for some q, cars are equilikely in states R and L to merge right, or r «(?) = r L{q), then no inference can be drawn from additional decisions, and all learning stops!  ... 
doi:10.1111/1468-0262.00113 fatcat:po3nyrdb55cybdgngfx6y64oty

Bibliographic guide to the foundations of quantum mechanics and quantum information [article]

Adan Cabello
2004 arXiv   pre-print
Specifically, it covers hidden variables ("no-go" theorems, experiments), interpretations of quantum mechanics, entanglement, quantum effects (quantum Zeno effect, quantum erasure, "interaction-free" measurements  ...  Bub, "On the non-locality of 421 (1982). probability, and inference", Philos. Sci. 49, ?, 402-976. [Bub 82]: J. Bub, "Quantum logic, conditional [Humphreys 80]. 149-153. Comment on [Demopoulos 80].  ...  a cloner based on QED), [Bruß-Ekert-Macchiavello 98], [Gisin 98] (maximum fidelity of a cloner, supposing that it cannot serve for superluminial transmission of information), [Mor 98 a] (if the individual  ... 
arXiv:quant-ph/0012089v12 fatcat:npzn2ah6fvd6bgmlwnh6xmcdl4

Nuclear-electronic spin systems, magnetic resonance, and quantum information processing [article]

M. H. Mohammady
2013 arXiv   pre-print
A promising platform for quantum information processing is that of silicon impurities, where the quantum states are manipulated by magnetic resonance.  ...  Most notable amongst these is that magnetic field-dependent two-dimensional decoherence free subspaces, called optimal working points, have been identified to exist in Si:Bi, but not Si:P.  ...  For a particular physical realisation, with usually an exponential coherence time of T 2 and the longest quantum gate taking ∆t to perform, we may estimate the upper bound for P for a single gate to be  ... 
arXiv:1305.0039v2 fatcat:o2fvkjykjfed3c2pfur3vujppm

Dagstuhl Reports, Volume 8, Issue 9, September 2018, Complete Issue [article]

for Lifelong Machine Learning (on-going), collocated with NIPS18; AutoDL challenge (coming soon), more details to be announced.  ...  under the more general context of automation in the workplace, we explored how we can identify and map the skills in data science with the capabilities of AI and ML, in order to know when tasks can be effectively  ...  Counterfactual prediction requires understanding causal relationships between so-called treatment and outcome variables.  ... 
doi:10.4230/dagrep.8.9 fatcat:5qvmtdru7banpoucejfabfjqdu

Proceedings of the 2022 Joint Workshop of the German Research Training Groups in Computer Science

Felix Freiling, Helmut Seidl, 2022 2022 Joint Workshop Of The German Research Training Groups In Computer Science June 12–June 15
Informatics, one of the world's premier venues for computer science-related seminars.  ...  traditional annual meeting of the German Research Training Groups (RTGs) funded by the Deutsche Forschungsgemeinschaft (DFG) in the field of computer science returns to Schloss Dagstuhl --– Leibniz Center for  ...  A first approach is based on the prediction of side effects. openEHR models of side effects and associated biomarkers are used to make patient-specific predictions based on electronic health record data  ... 
doi:10.25593/opus4-fau-19321 fatcat:ry4vd32xxbgldirrvymuaxxqwi

Algorithmic Fairness Datasets: the Story so Far [article]

Alessandro Fabris, Stefano Messina, Gianmaria Silvello, Gian Antonio Susto
In this work, we survey over two hundred datasets employed in algorithmic fairness research, producing standardized and searchable documentation for each of them, along with in-depth documentation for  ...  We discuss different approaches and levels of attention to these topics, making them tangible, and distill them into a set of best practices for the curation of novel datasets.  ...  Acknowledgements The authors would like to thank the following researchers and dataset creators for the useful feedback on the data briefs: Alain Barrat, Luc  ... 
doi:10.48550/arxiv.2202.01711 fatcat:mav36x3w5namjhurzpevtsmsju
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