43 citations · 78 across the 20 of their papers we have counts for
24 papers
A scalable solution for the extended multi-channel facility location problem
Etika Agarwal, Karthik S. Gurumoorthy, Ankit Ajit Jain +1
We study the extended version of the non-uniform, capacitated facility location problem with multiple fulfilment channels between the facilities and clients, each with their own ch…
Cooperative Multi-Agent Reinforcement Learning for Inventory Management
Madhav Khirwar, Karthik S. Gurumoorthy, Ankit Ajit Jain +1
With Reinforcement Learning (RL) for inventory management (IM) being a nascent field of research, approaches tend to be limited to simple, linear environments with implementations…
Estimating Joint Probability Distribution With Low-Rank Tensor Decomposition, Radon Transforms and Dictionaries
Pranava Singhal, Waqar Mirza, Ajit Rajwade +1
In this paper, we describe a method for estimating the joint probability density from data samples by assuming that the underlying distribution can be decomposed as a mixture of pr…
Signal Reconstruction from Samples at Unknown Locations with Application to 2D Unknown View Tomography
Sheel Shah, Kaishva Shah, Karthik S. Gurumoorthy +1
It is well known that a band-limited signal can be reconstructed from its uniformly spaced samples if the sampling rate is sufficiently high. More recently, it has been proved that…
Joint Probability Estimation Using Tensor Decomposition and Dictionaries
Shaan ul Haque, Ajit Rajwade, Karthik S. Gurumoorthy
In this work, we study non-parametric estimation of joint probabilities of a given set of discrete and continuous random variables from their (empirically estimated) 2D marginals,…
A decision-tree framework to select optimal box-sizes for product shipments
Karthik S. Gurumoorthy, Abhiraj Hinge
In package-handling facilities, boxes of varying sizes are used to ship products. Improperly sized boxes with box dimensions much larger than the product dimensions create wastage…
Individual Treatment Effect Estimation Through Controlled Neural Network Training in Two Stages
Naveen Nair, Karthik S. Gurumoorthy, Dinesh Mandalapu
We develop a Causal-Deep Neural Network (CDNN) model trained in two stages to infer causal impact estimates at an individual unit level. Using only the pre-treatment features in st…
SPOT: A framework for selection of prototypes using optimal transport
Karthik S. Gurumoorthy, Pratik Jawanpuria, Bamdev Mishra
In this work, we develop an optimal transport (OT) based framework to select informative prototypical examples that best represent a given target dataset. Summarizing a given targe…
Recovery of Joint Probability Distribution from one-way marginals: Low rank Tensors and Random Projections
Jian Vora, Karthik S. Gurumoorthy, Ajit Rajwade
Joint probability mass function (PMF) estimation is a fundamental machine learning problem. The number of free parameters scales exponentially with respect to the number of random…
Think out of the package: Recommending package types for e-commerce shipments
Karthik S. Gurumoorthy, Subhajit Sanyal, Vineet Chaoji
Multiple product attributes like dimensions, weight, fragility, liquid content etc. determine the package type used by e-commerce companies to ship products. Sub-optimal package ty…
Streaming Methods for Restricted Strongly Convex Functions with Applications to Prototype Selection
Karthik S. Gurumoorthy, Amit Dhurandhar
In this paper, we show that if the optimization function is restricted-strongly-convex (RSC) and restricted-smooth (RSM) -- a rich subclass of weakly submodular functions -- then a…
Signal Recovery in Perturbed Fourier Compressed Sensing
Eeshan Malhotra, Himanshu Pandotra, Ajit Rajwade +1
In many applications in compressed sensing, the measurement matrix is a Fourier matrix, i.e., it measures the Fourier transform of the underlying signal at some specified `base' fr…
Efficient Data Representation by Selecting Prototypes with Importance Weights
Karthik S. Gurumoorthy, Amit Dhurandhar, Guillermo Cecchi +1
Prototypical examples that best summarizes and compactly represents an underlying complex data distribution communicate meaningful insights to humans in domains where simple explan…
Degenerate Kalman filter error covariances and their convergence onto the unstable subspace
Marc Bocquet, Karthik S. Gurumoorthy, Amit Apte +3
The characteristics of the model dynamics are critical in the performance of (ensemble) Kalman filters. In particular, as emphasized in the seminal work of Anna Trevisan and co-aut…
Sensitivity Analysis for additive STDP rule
Subhajit Sengupta, Karthik S. Gurumoorthy, Arunava Banerjee
Spike Timing Dependent Plasticity (STDP) is a Hebbian like synaptic learning rule. The basis of STDP has strong experimental evidences and it depends on precise input and output sp…
Rank deficiency of Kalman error covariance matrices in linear time-varying system with deterministic evolution
Karthik S. Gurumoorthy, Colin Grudzien, Amit Apte +2
We prove that for linear, discrete, time-varying, deterministic system (perfect model) with noisy outputs, the Riccati transformation in the Kalman filter asymptotically bounds the…
Symmetric Submodular Clustering with Actionable Constraint
Amit Dhurandhar, Karthik Gurumoorthy
Clustering with submodular functions has been of interest over the last few years. Symmetric submodular functions are of particular interest as minimizing them is significantly mor…
Error bounds for gradient density estimation computed from a finite sample set using the method of stationary phase
Karthik S. Gurumoorthy, Anand Rangarajan
For a twice continuously differentiable function , we define the density function of its gradient (derivative in one dimension) as a random variable transformat…
A fast eikonal equation solver using the Schrodinger wave equation
Karthik S. Gurumoorthy, Adrian M. Peter, Birmingham Hang Guan +1
We use a Schrödinger wave equation formalism to solve the eikonal equation. In our framework, a solution to the eikonal equation is obtained in the limit as Planck's constant $\hba…
On the dynamic compressibility of sets
Karthik S. Gurumoorthy
We define a new notion of compressibility of a set of numbers through the dynamics of a polynomial function. We provide approaches to solve the problem by reducing it to the multi-…
Gradient density estimation in arbitrary finite dimensions using the method of stationary phase
Karthik S. Gurumoorthy, Anand Rangarajan, John Corring
We prove that the density function of the gradient of a sufficiently smooth function , obtained via a random variable transformati…
A new variational principle for the Euclidean distance function: Linear approach to the non-linear eikonal problem
Karthik S. Gurumoorthy, Anand Rangarajan
We present a fast convolution-based technique for computing an approximate, signed Euclidean distance function on a set of 2D and 3D grid locations. Instead of solving the non-…
An application of the stationary phase method for estimating probability densities of function derivatives
Karthik S. Gurumoorthy, Anand Rangarajan, Arunava Banerjee
We prove a novel result wherein the density function of the gradients---corresponding to density function of the derivatives in one dimension---of a thrice differentiable function…
Distance Transform Gradient Density Estimation using the Stationary Phase Approximation
Karthik S. Gurumoorthy, Anand Rangarajan
The complex wave representation (CWR) converts unsigned 2D distance transforms into their corresponding wave functions. Here, the distance transform S(X) appears as the phase of th…