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Uncertain programming model for multi-item solid transportation problem

Uncertain programming model for multi-item solid transportation problem

31 May 2016
Hasan Dalman
ArXivPDFHTML

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

38 / 138 papers shown
Title
Black-box Off-policy Estimation for Infinite-Horizon Reinforcement
  Learning
Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning
Ali Mousavi
Lihong Li
Qiang Liu
Denny Zhou
OffRL
13
32
0
24 Mar 2020
Reward Shaping for Human Learning via Inverse Reinforcement Learning
Reward Shaping for Human Learning via Inverse Reinforcement Learning
Mark Rucker
L.T. Watson
M. Gerber
Laura E. Barnes
OffRL
14
2
0
25 Feb 2020
Learning Deep Kernels for Non-Parametric Two-Sample Tests
Learning Deep Kernels for Non-Parametric Two-Sample Tests
Feng Liu
Wenkai Xu
Jie Lu
Guangquan Zhang
A. Gretton
Danica J. Sutherland
19
176
0
21 Feb 2020
A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings
A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings
Junhyung Park
Krikamol Muandet
33
77
0
10 Feb 2020
The reproducing Stein kernel approach for post-hoc corrected sampling
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
Model Reuse with Reduced Kernel Mean Embedding Specification
Xi-Zhu Wu
Wen-qi Xu
Song Liu
Zhi-Hua Zhou
20
24
0
20 Jan 2020
Constrained Polynomial Likelihood
Constrained Polynomial Likelihood
Caio Almeida
Ricardo Masini
P. Schneider
20
4
0
30 Oct 2019
Kernels over Sets of Finite Sets using RKHS Embeddings, with Application
  to Bayesian (Combinatorial) Optimization
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
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
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
Stochastic Bandits with Context Distributions
Johannes Kirschner
Andreas Krause
21
30
0
06 Jun 2019
Kernel Instrumental Variable Regression
Kernel Instrumental Variable Regression
Rahul Singh
M. Sahani
A. Gretton
17
168
0
01 Jun 2019
A Kernel Loss for Solving the Bellman Equation
A Kernel Loss for Solving the Bellman Equation
Yihao Feng
Lihong Li
Qiang Liu
25
70
0
25 May 2019
Distribution Calibration for Regression
Distribution Calibration for Regression
Hao Song
Tom Diethe
Meelis Kull
Peter A. Flach
UQCV
27
108
0
15 May 2019
The Born Supremacy: Quantum Advantage and Training of an Ising Born
  Machine
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
Semi-Parametric Uncertainty Bounds for Binary Classification
Balázs Csanád Csáji
Tamás Ambrus
19
6
0
23 Mar 2019
Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic
  Likelihood-Free Inference
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
Fast Approximation and Estimation Bounds of Kernel Quadrature for Infinitely Wide Models
Sho Sonoda
13
0
0
02 Feb 2019
Signature moments to characterize laws of stochastic processes
Signature moments to characterize laws of stochastic processes
I. Chevyrev
Harald Oberhauser
10
108
0
25 Oct 2018
Hyperparameter Learning via Distributional Transfer
Hyperparameter Learning via Distributional Transfer
H. Law
P. Zhao
Lucian Chan
Junzhou Huang
Dino Sejdinovic
9
25
0
15 Oct 2018
Multimodal Sentiment Analysis To Explore the Structure of Emotions
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
Markov Chain Importance Sampling -- a highly efficient estimator for MCMC
Ingmar Schuster
I. Klebanov
30
24
0
18 May 2018
Large-scale Nonlinear Variable Selection via Kernel Random Features
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
A Kernel Theory of Modern Data Augmentation
Tri Dao
Albert Gu
Alexander J. Ratner
Virginia Smith
Christopher De Sa
Christopher Ré
19
190
0
16 Mar 2018
Kernel Recursive ABC: Point Estimation with Intractable Likelihood
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
MONK -- Outlier-Robust Mean Embedding Estimation by Median-of-Means
M. Lerasle
Z. Szabó
Gaspar Massiot
Guillaume Lecué
31
34
0
13 Feb 2018
Near-Optimal Coresets of Kernel Density Estimates
Near-Optimal Coresets of Kernel Density Estimates
J. M. Phillips
W. Tai
23
72
0
06 Feb 2018
Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert
  Spaces
Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces
Stefan Klus
Ingmar Schuster
Krikamol Muandet
24
121
0
05 Dec 2017
Kernel method for persistence diagrams via kernel embedding and weight
  factor
Kernel method for persistence diagrams via kernel embedding and weight factor
G. Kusano
Kenji Fukumizu
Y. Hiraoka
12
83
0
12 Jun 2017
Comparison of Maximum Likelihood and GAN-based training of Real NVPs
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
Testing and Learning on Distributions with Symmetric Noise Invariance
H. Law
C. Yau
Dino Sejdinovic
19
7
0
22 Mar 2017
The Statistical Recurrent Unit
The Statistical Recurrent Unit
Junier B. Oliva
Barnabás Póczós
J. Schneider
16
50
0
01 Mar 2017
Consistent Kernel Mean Estimation for Functions of Random Variables
Consistent Kernel Mean Estimation for Functions of Random Variables
Carl-Johann Simon-Gabriel
Adam Scibior
Ilya O. Tolstikhin
Bernhard Schölkopf
37
14
0
19 Oct 2016
A Kernel Test of Goodness of Fit
A Kernel Test of Goodness of Fit
Kacper P. Chwialkowski
Heiko Strathmann
A. Gretton
BDL
107
324
0
09 Feb 2016
Sharp analysis of low-rank kernel matrix approximations
Sharp analysis of low-rank kernel matrix approximations
Francis R. Bach
86
277
0
09 Aug 2012
Determinantal point processes for machine learning
Determinantal point processes for machine learning
Alex Kulesza
B. Taskar
162
1,123
0
25 Jul 2012
Conditional mean embeddings as regressors - supplementary
Conditional mean embeddings as regressors - supplementary
Steffen Grunewalder
Guy Lever
Luca Baldassarre
Sam Patterson
A. Gretton
Massimiliano Pontil
85
143
0
21 May 2012
Measuring and testing dependence by correlation of distances
Measuring and testing dependence by correlation of distances
G. Székely
Maria L. Rizzo
N. K. Bakirov
179
2,577
0
28 Mar 2008
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