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
Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Ninh Pham Rasmus Pagh 27 0 0 13 May 2025
From Two Sample Testing to Singular Gaussian Discrimination Leonardo P. M. Santoro Kartik G. Waghmare V. Panaretos 31 0 0 07 May 2025
A Dictionary of Closed-Form Kernel Mean Embeddings F. Briol A. Gessner Toni Karvonen Maren Mahsereci BDL 78 1 0 26 Apr 2025
Ultra-fast feature learning for the training of two-layer neural networks in the two-timescale regime Raphael Barboni Gabriel Peyré François-Xavier Vialard MLT 34 0 0 25 Apr 2025
General reproducing properties in RKHS with application to derivative and integral operators Fatima-Zahrae El-Boukkouri Josselin Garnier Olivier Roustant 39 0 0 20 Mar 2025
What's in a Latent? Leveraging Diffusion Latent Space for Domain Generalization Xavier Thomas Deepti Ghadiyaram DiffM 92 0 0 09 Mar 2025
Improved learning theory for kernel distribution regression with two-stage sampling F. Bachoc Louis Bethune Alberto González Sanz Jean-Michel Loubes 96 1 0 28 Jan 2025
Towards Scalable Topological Regularizers Hiu-Tung Wong Darrick Lee Hong Yan BDL 59 0 0 24 Jan 2025
Theoretically Guaranteed Distribution Adaptable Learning Chao Xu Xijia Tang Guoqing Liu Yuhua Qian Chenping Hou OOD 44 0 0 05 Nov 2024
Unpacking Failure Modes of Generative Policies: Runtime Monitoring of Consistency and Progress Christopher Agia Rohan Sinha Jingyun Yang Zi-ang Cao Rika Antonova Marco Pavone Jeannette Bohg 28 7 0 06 Oct 2024
An Online Automatic Modulation Classification Scheme Based on Isolation Distributional Kernel Xinpeng Li Zile Jiang Kai Ming Ting Ye Zhu 27 0 0 03 Oct 2024
Distributed Clustering based on Distributional Kernel Hang Zhang Yang Xu Lei Gong Ye Zhu Kai Ming Ting 18 0 0 14 Sep 2024
Leveraging Unlabeled Data Sharing through Kernel Function Approximation in Offline Reinforcement Learning Yen-Ru Lai Fu-Chieh Chang Pei-Yuan Wu OffRL 76 1 0 22 Aug 2024
Efficient and Accurate Explanation Estimation with Distribution Compression Hubert Baniecki Giuseppe Casalicchio Bernd Bischl Przemyslaw Biecek FAtt 46 3 0 26 Jun 2024
Nyström Kernel Stein Discrepancy Florian Kalinke Zoltan Szabo Bharath K. Sriperumbudur 46 1 0 12 Jun 2024
Submodular Framework for Structured-Sparse Optimal Transport Piyushi Manupriya Pratik Jawanpuria Karthik S. Gurumoorthy SakethaNath Jagarlapudi Bamdev Mishra OT 97 0 0 07 Jun 2024
Spectral Truncation Kernels: Noncommutativity in $C^*$ -algebraic Kernel Machines Yuka Hashimoto Ayoub Hafid Masahiro Ikeda Hachem Kadri 41 1 0 28 May 2024
Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method Edoardo Caldarelli Antoine Chatalic Adrià Colomé C. Molinari C. Ocampo‐Martinez Carme Torras Lorenzo Rosasco 36 0 0 05 Mar 2024
Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes Georg Manten Cecilia Casolo E. Ferrucci Søren Wengel Mogensen C. Salvi Niki Kilbertus CML BDL 44 8 0 28 Feb 2024
Domain Generalization with Small Data Kecheng Chen Elena Gal Hong Yan Haoliang Li OOD 27 5 0 09 Feb 2024
Wasserstein Gradient Flows for Moreau Envelopes of f-Divergences in Reproducing Kernel Hilbert Spaces Viktor Stein Sebastian Neumayer Gabriele Steidl Nicolaj Rux 50 9 0 07 Feb 2024
M3D: Dataset Condensation by Minimizing Maximum Mean Discrepancy Hansong Zhang Shikun Li Pengju Wang Dan Zeng Shiming Ge DD 19 21 0 26 Dec 2023
Distribution-Based Trajectory Clustering Zijing Wang Ye Zhu Kai Ming Ting OOD 13 0 0 08 Oct 2023
Spectral Regularized Kernel Goodness-of-Fit Tests Omar Hagrass Bharath K. Sriperumbudur Bing Li 29 3 0 08 Aug 2023
Kernel-Based Testing for Single-Cell Differential Analysis Anthony Ozier-Lafontaine Camille Fourneaux G. Durif Polina Arsenteva C. Vallot O. Gandrillon Sandrine Giraud Bertrand Michel Franck Picard 21 5 0 17 Jul 2023
Scalable variable selection for two-view learning tasks with projection operators S. Szedmák Riikka Huusari Tat Hong Duong Le Juho Rousu 19 0 0 04 Jul 2023
Causal survival embeddings: non-parametric counterfactual inference under censoring Carlos García-Meixide Marcos Matabuena CML 38 5 0 20 Jun 2023
SENet: A Spectral Filtering Approach to Represent Exemplars for Few-shot Learning Tao Zhang Wu Huang 13 2 0 30 May 2023
The Representation Jensen-Shannon Divergence J. Hoyos-Osorio Santiago Posso-Murillo L. S. Giraldo 40 6 0 25 May 2023
Consistent Optimal Transport with Empirical Conditional Measures Piyushi Manupriya Rachit Keerti Das Sayantan Biswas S. Jagarlapudi OT 34 3 0 25 May 2023
Explaining the Uncertain: Stochastic Shapley Values for Gaussian Process Models Siu Lun Chau Krikamol Muandet Dino Sejdinovic FAtt 44 11 0 24 May 2023
Supervised learning with probabilistic morphisms and kernel mean embeddings H. Lê GAN 18 1 0 10 May 2023
Error Analysis of Kernel/GP Methods for Nonlinear and Parametric PDEs Pau Batlle Yifan Chen Bamdad Hosseini H. Owhadi Andrew M. Stuart 34 17 0 08 May 2023
An Efficient Doubly-Robust Test for the Kernel Treatment Effect Diego Martinez-Taboada Aaditya Ramdas Edward H. Kennedy OOD 26 5 0 26 Apr 2023
Multimodal Multi-User Surface Recognition with the Kernel Two-Sample Test Behnam Khojasteh Friedrich Solowjow Sebastian Trimpe Katherine J. Kuchenbecker 18 5 0 08 Mar 2023
Reproducing kernel Hilbert spaces in the mean field limit Christian Fiedler Michael Herty M. Rom C. Segala Sebastian Trimpe 27 6 0 28 Feb 2023
Data-Driven Observability Analysis for Nonlinear Stochastic Systems P. Massiani Mona Buisson-Fenet Friedrich Solowjow F. D. Meglio Sebastian Trimpe 6 2 0 23 Feb 2023
Variational Autoencoding Neural Operators Jacob H. Seidman Georgios Kissas George J. Pappas P. Perdikaris DRL AI4CE 27 7 0 20 Feb 2023
Transfer Learning for Bayesian Optimization: A Survey Tianyi Bai Yang Li Yu Shen Xinyi Zhang Wentao Zhang Bin Cui BDL 39 29 0 12 Feb 2023
Confidence and Uncertainty Assessment for Distributional Random Forests Jeffrey Näf Corinne Emmenegger Peter Buhlmann N. Meinshausen 35 3 0 11 Feb 2023
Kernelized Cumulants: Beyond Kernel Mean Embeddings Patric Bonnier Harald Oberhauser Zoltan Szabo 25 5 0 29 Jan 2023
Optimally-Weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference Ayush Bharti Masha Naslidnyk Oscar Key Samuel Kaski F. Briol 40 12 0 27 Jan 2023
Returning The Favour: When Regression Benefits From Probabilistic Causal Knowledge S. Bouabid Jake Fawkes Dino Sejdinovic CML 44 0 0 26 Jan 2023
An Analysis of Attention via the Lens of Exchangeability and Latent Variable Models Yufeng Zhang Boyi Liu Qi Cai Lingxiao Wang Zhaoran Wang 53 11 0 30 Dec 2022
Spectral Regularized Kernel Two-Sample Tests Omar Hagrass Bharath K. Sriperumbudur Bing Li 6 14 0 19 Dec 2022
Proposal Distribution Calibration for Few-Shot Object Detection Bohao Li Chang-rui Liu Mengnan Shi Xiaozhong Chen Xiang Ji QiXiang Ye ObjD 24 5 0 15 Dec 2022
Doubly Robust Kernel Statistics for Testing Distributional Treatment Effects Jake Fawkes Robert Hu R. Evans Dino Sejdinovic OOD 33 3 0 09 Dec 2022
Online Kernel CUSUM for Change-Point Detection S. Wei Yao Xie 27 11 0 28 Nov 2022
Satellite Navigation and Coordination with Limited Information Sharing Sydney I. Dolan Siddharth Nayak H. Balakrishnan 22 5 0 07 Nov 2022
Reinforcement Learning in Non-Markovian Environments Siddharth Chandak Pratik Shah Vivek Borkar Parth Dodhia OOD 22 7 0 03 Nov 2022