2.4k citations · 2.8k across the 17 of their papers we have counts for
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cs.LG2021★ 3 cited
Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces
Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum +4
Negative sampling schemes enable efficient training given a large number of classes, by offering a means to approximate a computationally expensive loss function that takes all lab…
cs.CV2021★ 2 cited
Less is more: Selecting informative and diverse subsets with balancing constraints
Srikumar Ramalingam, Daniel Glasner, Kaushal Patel +3
Deep learning has yielded extraordinary results in vision and natural language processing, but this achievement comes at a cost. Most models require enormous resources during train…