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cs.AI2018
Loss Functions, Axioms, and Peer Review
Ritesh Noothigattu, Nihar B. Shah, Ariel D. Procaccia
It is common to see a handful of reviewers reject a highly novel paper, because they view, say, extensive experiments as far more important than novelty, whereas the community as a…
cs.AI2017
Non-Count Symmetries in Boolean & Multi-Valued Prob. Graphical Models
Ankit Anand, Ritesh Noothigattu, Parag Singla +1
Lifted inference algorithms commonly exploit symmetries in a probabilistic graphical model (PGM) for efficient inference. However, existing algorithms for Boolean-valued domains ca…