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04/18/2023
Cooperative Multi-Agent Reinforcement Learning for Inventory Management
With Reinforcement Learning (RL) for inventory management (IM) being a n...
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04/18/2023
Estimating Joint Probability Distribution With Low-Rank Tensor Decomposition, Radon Transforms and Dictionaries
In this paper, we describe a method for estimating the joint probability...
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04/13/2023
Analysis of Tomographic Reconstruction of 2D Images using the Distribution of Unknown Projection Angles
It is well known that a band-limited signal can be reconstructed from it...
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03/03/2022
Joint Probability Estimation Using Tensor Decomposition and Dictionaries
In this work, we study non-parametric estimation of joint probabilities ...
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02/09/2022
A decision-tree framework to select optimal box-sizes for product shipments
In package-handling facilities, boxes of varying sizes are used to ship ...
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01/21/2022
Individual Treatment Effect Estimation Through Controlled Neural Network Training in Two Stages
We develop a Causal-Deep Neural Network (CDNN) model trained in two stag...
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03/22/2021
Recovery of Joint Probability Distribution from one-way marginals: Low rank Tensors and Random Projections
Joint probability mass function (PMF) estimation is a fundamental machin...
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03/18/2021
SPOT: A framework for selection of prototypes using optimal transport
In this work, we develop an optimal transport (OT) based framework to se...
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06/05/2020
Think out of the package: Recommending package types for e-commerce shipments
Multiple product attributes like dimensions, weight, fragility, liquid c...
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07/21/2018
Streaming Methods for Restricted Strongly Convex Functions with Applications to Prototype Selection
In this paper, we show that if the optimization function is restricted-s...
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07/05/2017
ProtoDash: Fast Interpretable Prototype Selection
In this paper we propose an efficient algorithm ProtoDash for selecting ...
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02/28/2015
Sensitivity Analysis for additive STDP rule
Spike Timing Dependent Plasticity (STDP) is a Hebbian like synaptic lear...
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11/13/2012
Gradient density estimation in arbitrary finite dimensions using the method of stationary phase
We prove that the density function of the gradient of a sufficiently smo...
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12/13/2011
A new variational principle for the Euclidean distance function: Linear approach to the non-linear eikonal problem
We present a fast convolution-based technique for computing an approxima...
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08/08/2011
An application of the stationary phase method for estimating probability densities of function derivatives
We prove a novel result wherein the density function of the gradients---...
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04/19/2011
