7.4k citations · 22.9k across the 86 of their papers we have counts for
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Loss-sensitive Training of Probabilistic Conditional Random Fields
Maksims N. Volkovs, Hugo Larochelle, Richard S. Zemel
We consider the problem of training probabilistic conditional random fields (CRFs) in the context of a task where performance is measured using a specific loss function. While maxi…
Ranking via Sinkhorn Propagation
Ryan Prescott Adams, Richard S. Zemel
It is of increasing importance to develop learning methods for ranking. In contrast to many learning objectives, however, the ranking problem presents difficulties due to the fact…
Interpreting Graph Cuts as a Max-Product Algorithm
Daniel Tarlow, Inmar E. Givoni, Richard S. Zemel +1
The maximum a posteriori (MAP) configuration of binary variable models with submodular graph-structured energy functions can be found efficiently and exactly by graph cuts. Max-pro…
Fairness Through Awareness
Cynthia Dwork, Moritz Hardt, Toniann Pitassi +2
We study fairness in classification, where individuals are classified, e.g., admitted to a university, and the goal is to prevent discrimination against individuals based on their…