Uncertain programming model for multi-item solid transportation problem

31 May 2016

Papers citing "Uncertain programming model for multi-item solid transportation problem"

43 / 143 papers shown

Title
Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression Domagoj Cevid Loris Michel Jeffrey Näf N. Meinshausen Peter Buhlmann 35 39 0 29 May 2020
Bullseye Polytope: A Scalable Clean-Label Poisoning Attack with Improved Transferability H. Aghakhani Dongyu Meng Yu-Xiang Wang Christopher Kruegel Giovanni Vigna AAML 23 105 0 01 May 2020
Similarity of Neural Networks with Gradients Shuai Tang Wesley J. Maddox Charlie Dickens Tom Diethe Andreas C. Damianou 19 25 0 25 Mar 2020
Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning Ali Mousavi Lihong Li Qiang Liu Denny Zhou OffRL 21 32 0 24 Mar 2020
Reward Shaping for Human Learning via Inverse Reinforcement Learning Mark Rucker L.T. Watson M. Gerber Laura E. Barnes OffRL 19 2 0 25 Feb 2020
Learning Deep Kernels for Non-Parametric Two-Sample Tests Feng Liu Wenkai Xu Jie Lu Guangquan Zhang Arthur Gretton Danica J. Sutherland 19 176 0 21 Feb 2020
A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings Junhyung Park Krikamol Muandet 35 77 0 10 Feb 2020
The reproducing Stein kernel approach for post-hoc corrected sampling Liam Hodgkinson R. Salomone Fred Roosta 32 27 0 25 Jan 2020
Model Reuse with Reduced Kernel Mean Embedding Specification Xi-Zhu Wu Wen-qi Xu Song Liu Zhi-Hua Zhou 28 24 0 20 Jan 2020
Constrained Polynomial Likelihood Caio Almeida Ricardo Masini P. Schneider 28 4 0 30 Oct 2019
Kernels over Sets of Finite Sets using RKHS Embeddings, with Application to Bayesian (Combinatorial) Optimization Poompol Buathong D. Ginsbourger Tipaluck Krityakierne BDL 29 22 0 09 Oct 2019
MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy Badr-Eddine Chérief-Abdellatif Pierre Alquier 56 72 0 29 Sep 2019
Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi's Entropy and Tensor Kernels Kristoffer Wickstrøm Sigurd Løkse Michael C. Kampffmeyer Shujian Yu José C. Príncipe Robert Jenssen 24 31 0 25 Sep 2019
Stochastic Bandits with Context Distributions Johannes Kirschner Andreas Krause 21 30 0 06 Jun 2019
Kernel Instrumental Variable Regression Rahul Singh M. Sahani Arthur Gretton 28 168 0 01 Jun 2019
A Kernel Loss for Solving the Bellman Equation Yihao Feng Lihong Li Qiang Liu 30 70 0 25 May 2019
Distribution Calibration for Regression Hao Song Tom Diethe Meelis Kull Peter A. Flach UQCV 33 108 0 15 May 2019
Dimensionality Reduction of Complex Metastable Systems via Kernel Embeddings of Transition Manifolds A. Bittracher Stefan Klus B. Hamzi P. Koltai Christof Schütte 14 22 0 18 Apr 2019
The Born Supremacy: Quantum Advantage and Training of an Ising Born Machine Brian Coyle Daniel Mills V. Danos E. Kashefi 27 155 0 03 Apr 2019
Semi-Parametric Uncertainty Bounds for Binary Classification Balázs Csanád Csáji Tamás Ambrus 27 6 0 23 Mar 2019
Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic Likelihood-Free Inference Kelvin Hsu F. Ramos 30 12 0 03 Mar 2019
Fast Approximation and Estimation Bounds of Kernel Quadrature for Infinitely Wide Models Sho Sonoda 16 0 0 02 Feb 2019
Signature moments to characterize laws of stochastic processes I. Chevyrev Harald Oberhauser 13 108 0 25 Oct 2018
Hyperparameter Learning via Distributional Transfer H. Law P. Zhao Lucian Chan Junzhou Huang Dino Sejdinovic 19 25 0 15 Oct 2018
Multimodal Sentiment Analysis To Explore the Structure of Emotions Anthony Hu Seth Flaxman 26 110 0 25 May 2018
Markov Chain Importance Sampling -- a highly efficient estimator for MCMC Ingmar Schuster I. Klebanov 35 24 0 18 May 2018
Large-scale Nonlinear Variable Selection via Kernel Random Features Magda Gregorova Jason Ramapuram Alexandros Kalousis Stéphane Marchand-Maillet 28 5 0 19 Apr 2018
A Kernel Theory of Modern Data Augmentation Tri Dao Albert Gu Alexander J. Ratner Virginia Smith Christopher De Sa Christopher Ré 24 190 0 16 Mar 2018
Kernel Recursive ABC: Point Estimation with Intractable Likelihood T. Kajihara Motonobu Kanagawa Keisuke Yamazaki Kenji Fukumizu 34 13 0 23 Feb 2018
MONK -- Outlier-Robust Mean Embedding Estimation by Median-of-Means M. Lerasle Z. Szabó Gaspar Massiot Guillaume Lecué 34 34 0 13 Feb 2018
Near-Optimal Coresets of Kernel Density Estimates J. M. Phillips W. Tai 28 72 0 06 Feb 2018
Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces Stefan Klus Ingmar Schuster Krikamol Muandet 26 121 0 05 Dec 2017
Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings Motonobu Kanagawa Bharath K. Sriperumbudur Kenji Fukumizu 20 45 0 01 Sep 2017
Kernel method for persistence diagrams via kernel embedding and weight factor G. Kusano Kenji Fukumizu Y. Hiraoka 17 83 0 12 Jun 2017
Comparison of Maximum Likelihood and GAN-based training of Real NVPs Ivo Danihelka Balaji Lakshminarayanan Benigno Uria Daan Wierstra Peter Dayan GAN 24 53 0 15 May 2017
Testing and Learning on Distributions with Symmetric Noise Invariance H. Law C. Yau Dino Sejdinovic 24 7 0 22 Mar 2017
The Statistical Recurrent Unit Junier B. Oliva Barnabás Póczós J. Schneider 18 50 0 01 Mar 2017
Consistent Kernel Mean Estimation for Functions of Random Variables Carl-Johann Simon-Gabriel Adam Scibior Ilya O. Tolstikhin Bernhard Schölkopf 40 14 0 19 Oct 2016
A Kernel Test of Goodness of Fit Kacper P. Chwialkowski Heiko Strathmann Arthur Gretton BDL 109 324 0 09 Feb 2016
Sharp analysis of low-rank kernel matrix approximations Francis R. Bach 86 277 0 09 Aug 2012
Determinantal point processes for machine learning Alex Kulesza B. Taskar 165 1,123 0 25 Jul 2012
Conditional mean embeddings as regressors - supplementary Steffen Grunewalder Guy Lever Luca Baldassarre Sam Patterson Arthur Gretton Massimiliano Pontil 85 143 0 21 May 2012
Measuring and testing dependence by correlation of distances G. Székely Maria L. Rizzo N. K. Bakirov 182 2,578 0 28 Mar 2008