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CD@KDD
2018
2019
2021
2022
2018
2022
Keyphrases
Publications
2022
Osman Mian
,
David Kaltenpoth
,
Michael Kamp
Regret-based Federated Causal Discovery.
CD@KDD
(2022)
Thuc Duy Le
,
Lin Liu
,
Emre Kiciman
,
Sofia Triantafyllou
,
Huan Liu
Preface: The 2022 ACM SIGKDD Workshop on Causal Discovery.
CD@KDD
(2022)
Konstantina Valogianni
,
Balaji Padmanabhan
Causal ABMs: Learning Plausible Causal Models using Agent-based Modeling.
CD@KDD
(2022)
Christopher Hagedorn
,
Constantin Lange
,
Johannes Huegle
,
Rainer Schlosser
GPU Acceleration for Information-theoretic Constraint-based Causal Discovery.
CD@KDD
(2022)
volume 185, 2022
The KDD'22 Workshop on Causal Discovery, 15 August 2022, Washington DC, USA
CD@KDD
185 (2022)
2021
Laila Melkas
,
Rafael Savvides
,
Suyog Chandramouli
,
Jarmo Mäkelä
,
Tuomo Nieminen
,
Ivan Mammarella
,
Kai Puolamäki
Interactive Causal Structure Discovery in Earth System Sciences.
CD@KDD
(2021)
Keisuke Kiritoshi
,
Tomonori Izumitani
,
Kazuki Koyama
,
Tomomi Okawachi
,
Keisuke Asahara
,
Shohei Shimizu
Estimating individual-level optimal causal interventions combining causal models and machine learning models.
CD@KDD
(2021)
Ehsan Mokhtarian
,
Sina Akbari
,
AmirEmad Ghassami
,
Negar Kiyavash
A Recursive Markov Boundary-Based Approach to Causal Structure Learning.
CD@KDD
(2021)
Eric V. Strobl
,
Shyam Visweswaran
Dirac Delta Regression: Conditional Density Estimation with Clinical Trials.
CD@KDD
(2021)
Thuc Duy Le
,
Jiuyong Li
,
Gregory Cooper
,
Sofia Triantafyllou
,
Elias Bareinboim
,
Huan Liu
,
Negar Kiyavash
Preface: The 2021 ACM SIGKDD Workshop on Causal Discovery.
CD@KDD
(2021)
volume 150, 2021
The KDD 2021 Workshop on Causal Discovery, CD@KDD 2021, Singapore, August 15, 2021.
CD@KDD
150 (2021)
2020
Thuc Duy Le
,
Lin Liu
,
Kun Zhang
,
Emre Kiciman
,
Peng Cui
,
Aapo Hyvärinen
Preface: The 2020 ACM SIGKDD Workshop on Causal Discovery.
CD@KDD
(2020)
Jonathan D. Young
,
Bryan Andrews
,
Gregory F. Cooper
,
Xinghua Lu
Learning Latent Causal Structures with a Redundant Input Neural Network.
CD@KDD
(2020)
Ankit Sharma
,
Garima Gupta
,
Ranjitha Prasad
,
Arnab Chatterjee
,
Lovekesh Vig
,
Gautam Shroff
Hi-CI: Deep Causal Inference in High Dimensions.
CD@KDD
(2020)
Sisi Ma
,
Roshan Tourani
Predictive and Causal Implications of using Shapley Value for Model Interpretation.
CD@KDD
(2020)
Yunzhe Li
,
Kun Kuang
,
Bo Li
,
Peng Cui
,
Jianrong Tao
,
Hongxia Yang
,
Fei Wu
Continuous Treatment Effect Estimation via Generative Adversarial De-confounding.
CD@KDD
(2020)
volume 127, 2020
Proceedings of the 2020 KDD Workshop on Causal Discovery (CD@KDD 2020), San Diego, CA, USA, 24 August 2020.
CD@KDD
127 (2020)
2019
Karim Assaad
,
Emilie Devijver
,
Éric Gaussier
,
Ali Aït-Bachir
Scaling Causal Inference in Additive Noise Models.
CD@KDD
(2019)
Thuc Duy Le
,
Jiuyong Li
,
Kun Zhang
,
Emre Kiciman
,
Peng Cui
,
Aapo Hyvärinen
Preface: The 2019 ACM SIGKDD Workshop on Causal Discovery.
CD@KDD
(2019)
Alexander Lin
,
Amil Merchant
,
Suproteem K. Sarkar
,
Alexander D'Amour
Universal Causal Evaluation Engine: An API for empirically evaluating causal inference models.
CD@KDD
(2019)
Shuyang Du
,
James Lee
,
Farzin Ghaffarizadeh
Improve User Retention with Causal Learning.
CD@KDD
(2019)
Bryan Andrews
,
Joseph D. Ramsey
,
Gregory F. Cooper
Learning High-dimensional Directed Acyclic Graphs with Mixed Data-types.
CD@KDD
(2019)
Christopher Schmidt
,
Johannes Huegle
,
Philipp Bode
,
Matthias Uflacker
Load-Balanced Parallel Constraint-Based Causal Structure Learning on Multi-Core Systems for High-Dimensional Data.
CD@KDD
(2019)
Sandeep Soni
,
Shawn Ling Ramirez
,
Jacob Eisenstein
Detecting Social Influence in Event Cascades by Comparing Discriminative Rankers.
CD@KDD
(2019)
Eric V. Strobl
Improved Causal Discovery from Longitudinal Data Using a Mixture of DAGs.
CD@KDD
(2019)
volume 104, 2019
Proceedings of the 2019 ACM SIGKDD Workshop on Causal Discovery, CD@KDD 2019, Anchorage, Alaska, USA, August 5, 2019
CD@KDD
104 (2019)
2018
Mandar S. Chaudhary
,
Nagiza F. Samatova
Causal Relationship Prediction with Continuous Additive Noise Models.
CD@KDD
(2018)
Vineet K. Raghu
,
Allen Poon
,
Panayiotis V. Benos
Evaluation of Causal Structure Learning Methods on Mixed Data Types.
CD@KDD
(2018)
Thuc Duy Le
,
Kun Zhang
,
Emre Kiciman
,
Aapo Hyvärinen
,
Lin Liu
Preface: The 2018 ACM SIGKDD Workshop on Causal Discovery.
CD@KDD
(2018)
Min Zheng
,
Jan Claassen
,
Samantha Kleinberg
Automated Identification of Causal Moderators in Time-Series Data.
CD@KDD
(2018)
Daniel Malinsky
,
Peter Spirtes
Causal Structure Learning from Multivariate Time Series in Settings with Unmeasured Confounding.
CD@KDD
(2018)
volume 92, 2018
Proceedings of 2018 ACM SIGKDD Workshop on Causal Discovery, CD@KDD 2018, London, UK, 20 August 2018.
CD@KDD
92 (2018)