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or do we already do that because we are minimising KL with more recency bias rather than over the entire distribution?
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why do we accept approximating distribution from data/model with forward KL (left picture)? why not work towards algos that look like (right picture)?
or do we already do that because we are minimising KL with more recency bias rather than over the entire distribution?
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