Asia
MonteCarloTreeSearchbasedVariableSelection forHighDimensionalBayesianOptimization
Our regret bound generalizes that of GP-UCB [38] which always selects all variables, aswellasthatofDropout [21]whichselectsdvariables randomly ineachiteration.
Probabilistic Logic Neural Networks for Reasoning
Neural Information Processing Systems http://nips.cc/
Onthe Algorithmic Stabilityof Adversarial Training
Theorem 3 presents boundedness and = 0L , when( , T, 0)ischosen( T) !1 and 0 ! The (mean, sd, 99.9%-quantile) are (178.90,
Learning Representations for Time Series Clustering
Qianli Ma, Jiawei Zheng, Sen Li, Gary W. Cottrell
Neural Information Processing Systems http://nips.cc/
Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems T ongtong Fang 1 Nan Lu2,3 Gang Niu
Distribution shift (DS) may have two levels: the distribution itself changes, and the support (i.e., the set where the probability density is non-zero) also changes.