Machine learning

Honorable mention to Amazon researchers for ICML test-of-time award

Amazon's Bernhard Schölkopf and Dominik Janzing are first and second authors on "breakthrough 2012 paper".

By Staff writer

July 22, 2022

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AmazonScience_Bernhard&Dominik_220727114545.jpg — Amazon vice president and distinguished scientist Bernhard Schölkopf (left) and principal research scientist Dominik Janzing.

At the 2022 International Conference on Machine Learning (ICML), the program committee announced that the 2012 paper "On causal and anticausal learning", whose first two authors are Amazon vice president and distinguished scientist Bernhard Schölkopf and principal research scientist Dominik Janzing, had received an honorable mention for the conference's Test of Time award. Schölkopf and Janzing are joined on the paper by Jonas Peters, Eleni Sgouritsa, and Kun Zhang, who at the time were their colleagues at the Max Planck Institute for Intelligent Systems, and by Joris Mooij, now a professor of mathematical statistics at the University of Amsterdam.

On learning of the honor, Schölkopf posted his thoughts in a Twitter thread. His first tweet in the thread, followed by a screenshot of the thread it its entirety, are below.

Our 2012 paper ‘On causal and anticausal learning’ just received a Test of Time Honorable Mention at @icmlconf #ICML2022: https://t.co/gc1FZYSOyP. I am really grateful, and would like to use this occasion for some thoughts on causality and machine learning:
— Bernhard Schölkopf (@bschoelkopf) July 20, 2022

Schoelkopf Twitter thread

Judea Pearl, a Turing Award winner whose pioneering work on causal reasoning laid much of the groundwork for Schölkopf and Janzing's later research, also took to Twitter to congratulate Schölkopf and his colleagues:

Congratulations to @bschoelkopf on a well-deserved recognition and, more importantly, on a breakthrough 2012 paper that has built bridges between causality and machine learning. https://t.co/W1ExAjg33x
— Judea Pearl (@yudapearl) July 21, 2022

About the Author

Staff writer

A quick guide to Amazon’s papers at ICML 2024

Staff writer

July 17, 2024

Learning algorithms and reinforcement learning are areas of focus, while LLM-related research — on topics such as continual learning, hallucination mitigation, and privacy — remains well represented.

Machine learning
Removing selection bias from evaluation of recommendations

Özalp Özer, Serdar Şimşek

October 21, 2024

Causal machine learning provides a powerful tool for estimating the effectiveness of Fulfillment by Amazon’s recommendations to selling partners.

Operations research and optimization
Interpretable ensemble models improve product retrieval

Nurendra Choudhary

July 03, 2024

Gradient-boosted decision trees aggregate model outputs, and Shapley values help identify the most useful models for the ensemble.

Search and information retrieval

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BR, SP, Sao Paulo

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