DSNC learns binary stochastic codes and input mappings jointly in an end-to-end neural model to enable efficient large-scale multi-class classification.
IEEE Transactions on Pattern Analysis and Machine Intelligence 36(3) (2014) 507–520
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Binary Stochastic Representations for Large Multi-class Classification
DSNC learns binary stochastic codes and input mappings jointly in an end-to-end neural model to enable efficient large-scale multi-class classification.