Entropy-regularized Wasserstein distributionally robust shape and topology optimizationRobust optimizationDistributional robustnessWassertstein distanceEntropic regularizationShape optimizationTopology optimizationLinear elasticityThis brief note aims to introduce the recent paradigm of distributional robustness in the field...
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In contrast to most previous approaches, which directly convert locally averaged image ellipticities to mass maps (direct methods), our entropy-regularized maximum-likelihood method is an inverse approach. Albeit somewhat more expensive computationally, our method allows high spatial resolution in those ...
We consider both entropy-regularized N-stage and entropy-regularized discounted stochastic games, and establish the existence of a value in both games. Moreover, we prove the sufficiency of Markovian and stationary mixed strategies to attain the value, respectively, in N-stage and discounted games....
All Points Matter: Entropy-Regularized Distribution Alignment for Weakly-supervised 3D Segmentation (NeurIPS 2023) - PointCloudYC/ERDA
Weighted Entropy: Hpw=−∑k=1Kwkpklogpk 贡献 promising improvements in both performance and sample-efficiency 做法 简述 1 提出基于加权的熵的多目标rl, 鼓励智能体最大化回报的同时,完成更多的目标 2 提出最大熵的prioritization框架 具体 每一个回合,给定一个 gs ,考虑goal_conditioned policy, 轨...
[IEEE 2009 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) - Jeju Island, South Korea (2009.08.20-2009.08.24)] 2009 IEEE International Conferenc... [IEEE 2009 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) - Jeju Island, South Korea (2009.08.20-2009.08.24)] 2009 IEEE...
Efficient multiclass implementations of L1-regularized maximum entropy. E-print arXiv:cs/0506101.P. Haffner, S. Phillips, and R. Schapire, "Efficient multiclass implementations of L1-regularized maximum entropy," Com- puter Science, abs/cs/0506101, 2005....
If the value of one these invariants is less than 1 then the logarithm of the inverse of its value is a positive lower bound for the regularized minimum entropy of an output quantum channel. We give a few examples in which one of these invariants is less than 1. We also study the ...
This paper presents a new approach to estimating mixture models based on a recent inference principle we have proposed: the latent maximum entropy principle (LME). LME is different from Jaynes' maximum entropy principle, standard maximum likelihood, and maximum aposteriori probability estimation. We ...