Uncertain programming model for multi-item solid transportation problem

31 May 2016

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

50 / 138 papers shown

Title
Bayesian Counterfactual Mean Embeddings and Off-Policy Evaluation Diego Martinez-Taboada Dino Sejdinovic CML OffRL 23 0 0 02 Nov 2022
Minimum Kernel Discrepancy Estimators Chris J. Oates 30 10 0 28 Oct 2022
Geometry of Radial Basis Neural Networks for Safety Biased Approximation of Unsafe Regions Ahmad Abuaish Mohit Srinivasan Patricio A. Vela 44 3 0 11 Oct 2022
Minimax Optimal Kernel Operator Learning via Multilevel Training Jikai Jin Yiping Lu Jose H. Blanchet Lexing Ying 23 11 0 28 Sep 2022
Automatic and effective discovery of quantum kernels Massimiliano Incudini Daniele Lizzio Bosco F. Martini Michele Grossi Giuseppe Serra Alessandra Di Pierro 31 4 0 22 Sep 2022
Sharp Analysis of Sketch-and-Project Methods via a Connection to Randomized Singular Value Decomposition Michal Derezinski E. Rebrova 27 16 0 20 Aug 2022
Equivariant Disentangled Transformation for Domain Generalization under Combination Shift Yivan Zhang Jindong Wang Xingxu Xie Masashi Sugiyama OOD 42 1 0 03 Aug 2022
Optimal Rates for Regularized Conditional Mean Embedding Learning Zhu Li D. Meunier Mattes Mollenhauer A. Gretton 30 46 0 02 Aug 2022
Self-supervised learning with rotation-invariant kernels Léon Zheng Gilles Puy E. Riccietti Patrick Pérez Rémi Gribonval SSL 16 2 0 28 Jul 2022
Semi-supervised Deep Multi-view Stereo Hongbin Xu Wei-Han Cheng Yang Liu Zhipeng Zhou Haihong Xiao Baigui Sun Xuansong Xie Wenxiong Kang 38 7 0 24 Jul 2022
Adapting to Online Label Shift with Provable Guarantees Yong Bai Yu-Jie Zhang Peng Zhao Masashi Sugiyama Zhi-Hua Zhou OOD 27 25 0 05 Jul 2022
Distribution-based Sketching of Single-Cell Samples Vishal Baskaran Jolene S Ranek Siyuan Shan Natalie Stanley Junier B. Oliva 11 13 0 30 Jun 2022
Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces Vladimir Kostic P. Novelli Andreas Maurer C. Ciliberto Lorenzo Rosasco Massimiliano Pontil 18 60 0 27 May 2022
Maximum Mean Discrepancy on Exponential Windows for Online Change Detection Florian Kalinke Marco Heyden Edouard Fouché Klemens Bohm Klemens Böhm 24 0 0 25 May 2022
Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents Alessandro Barp Lancelot Da Costa G. Francca Karl J. Friston Mark Girolami Michael I. Jordan G. Pavliotis 31 25 0 20 Mar 2022
Generalized Label Shift Correction via Minimum Uncertainty Principle: Theory and Algorithm You-Wei Luo Chuan-Xian Ren 27 2 0 26 Feb 2022
Stochastic Causal Programming for Bounding Treatment Effects Kirtan Padh Jakob Zeitler David S. Watson Matt J. Kusner Ricardo M. A. Silva Niki Kilbertus CML 30 26 0 22 Feb 2022
Information Theory with Kernel Methods Francis R. Bach 32 40 0 17 Feb 2022
Investigation of Alternative Measures for Mutual Information Bulut Kuskonmaz Jaron Skovsted Gundersen R. Wisniewski 21 4 0 02 Feb 2022
Deep Layer-wise Networks Have Closed-Form Weights Chieh-Tsai Wu A. Masoomi A. Gretton Jennifer Dy 29 3 0 01 Feb 2022
Graph Representation Learning via Aggregation Enhancement Maxim Fishman Chaim Baskin Evgenii Zheltonozhskii Almog David Ron Banner A. Mendelson 24 0 0 30 Jan 2022
Change Detection of Markov Kernels with Unknown Pre and Post Change Kernel Hao Chen Jiacheng Tang Abhishek Gupta 33 7 0 27 Jan 2022
Supervised learning of sheared distributions using linearized optimal transport Varun Khurana Harish Kannan A. Cloninger Caroline Moosmüller OT 19 16 0 25 Jan 2022
Transparent Single-Cell Set Classification with Kernel Mean Embeddings Siyuan Shan Vishal Baskaran Haidong Yi Jolene S Ranek Natalie Stanley Junier Oliva 19 11 0 18 Jan 2022
Minimax risk classifiers with 0-1 loss Santiago Mazuelas Mauricio Romero Peter Grünwald 32 6 0 17 Jan 2022
Local permutation tests for conditional independence Ilmun Kim Matey Neykov Sivaraman Balakrishnan Larry A. Wasserman 31 27 0 22 Dec 2021
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks Marvin Schmitt Paul-Christian Bürkner Ullrich Kothe Stefan T. Radev 24 34 0 16 Dec 2021
Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves Rahul Singh Liyuan Xu A. Gretton 32 3 0 06 Nov 2021
RKHS-SHAP: Shapley Values for Kernel Methods Siu Lun Chau Robert Hu Javier I. González Dino Sejdinovic FAtt 26 15 0 18 Oct 2021
Offline Reinforcement Learning with Soft Behavior Regularization Haoran Xu Xianyuan Zhan Jianxiong Li Honglei Yin OffRL 23 31 0 14 Oct 2021
Topology, Convergence, and Reconstruction of Predictive States S. Loomis James P. Crutchfield AI4CE 24 7 0 19 Sep 2021
Minimum Discrepancy Methods in Uncertainty Quantification Chris J. Oates 36 2 0 13 Sep 2021
From the Greene--Wu Convolution to Gradient Estimation over Riemannian Manifolds Tianyu Wang Yifeng Huang Didong Li 17 8 0 17 Aug 2021
How many moments does MMD compare? Rustem Takhanov 21 0 0 27 Jun 2021
Standardisation-function Kernel Stein Discrepancy: A Unifying View on Kernel Stein Discrepancy Tests for Goodness-of-fit Wenkai Xu 32 4 0 23 Jun 2021
A Note on Optimizing Distributions using Kernel Mean Embeddings Boris Muzellec Francis R. Bach Alessandro Rudi 11 4 0 18 Jun 2021
Reproducing Kernel Hilbert Space, Mercer's Theorem, Eigenfunctions, Nyström Method, and Use of Kernels in Machine Learning: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley 9 35 0 15 Jun 2021
A Neural Tangent Kernel Perspective of GANs Jean-Yves Franceschi Emmanuel de Bézenac Ibrahim Ayed Mickaël Chen Sylvain Lamprier Patrick Gallinari 31 26 0 10 Jun 2021
The Inductive Bias of Quantum Kernels Jonas M. Kubler Simon Buchholz Bernhard Schölkopf 19 119 0 07 Jun 2021
Adaptive Methods for Real-World Domain Generalization Abhimanyu Dubey Vignesh Ramanathan Alex Pentland D. Mahajan OOD 30 88 0 29 Mar 2021
Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression Junhyung Park Uri Shalit Bernhard Schölkopf Krikamol Muandet CML 21 31 0 16 Feb 2021
On the Convergence of Gradient Descent in GANs: MMD GAN As a Gradient Flow Youssef Mroueh Truyen V. Nguyen 29 25 0 04 Nov 2020
Linear Optimal Transport Embedding: Provable Wasserstein classification for certain rigid transformations and perturbations Caroline Moosmüller A. Cloninger OT 17 43 0 20 Aug 2020
Probabilistic Neighbourhood Component Analysis: Sample Efficient Uncertainty Estimation in Deep Learning Ankur Mallick Chaitanya Dwivedi B. Kailkhura Gauri Joshi T. Y. Han UQCV BDL 39 6 0 18 Jul 2020
Estimating Barycenters of Measures in High Dimensions Samuel N. Cohen Michael Arbel M. Deisenroth 26 22 0 14 Jul 2020
Robust Persistence Diagrams using Reproducing Kernels Siddharth Vishwanath Kenji Fukumizu S. Kuriki Bharath K. Sriperumbudur 21 7 0 17 Jun 2020
Universal Robust Regression via Maximum Mean Discrepancy Pierre Alquier Mathieu Gerber 38 15 0 01 Jun 2020
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 20 105 0 01 May 2020
Similarity of Neural Networks with Gradients Shuai Tang Wesley J. Maddox Charlie Dickens Tom Diethe Andreas C. Damianou 14 25 0 25 Mar 2020