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TheDilemmaofTriHardLossandan Element-WeightedTriHardLossforPerson Re-Identification

Neural Information Processing Systems

Features ofthese characteristics should beclustered between anchors and positive samples while are also utilized to repel between anchors and hard negative samples. It is harmful for learning mutual features within classes.



UnderstandingtheEffectofStochasticity inPolicyOptimization

Neural Information Processing Systems

Until recently it had generally been assumed thatmethods based onfollowingthepolicygradient (PG)[1]could notbeguaranteed toconverge to globally optimal solutions, given that the policy value function is not concave.


82d3258eb58ceac31744a88005b7ddef-Supplemental-Conference.pdf

Neural Information Processing Systems

Thedistribution as well as mean payoffs for possible worker-job type-pairs are unobservables and the platform's goal is to sequentially match incoming jobs to workers in a way that maximizes its cumulative payoffs over the planning horizon.



Appendix

Neural Information Processing Systems

ThepolytopeP(X,L) is in fact a "twisted sum" of a finite number of lattice polytopes fibering overP(F,L| F) .