b'Arun Kumar'

research

∙ 12/01/2021

Processing Analytical Queries in the AWESOME Polystore [Information Systems Architectures]

Modern big data applications usually involve heterogeneous data sources ...

Xiuwen Zheng, et al. ∙

research

∙ 11/12/2021

The expectation-maximization algorithm for autoregressive models with normal inverse Gaussian innovations

The autoregressive (AR) models are used to represent the time-varying ra...

Monika S. Dhull, et al. ∙

research

∙ 10/16/2021

Hydra: A System for Large Multi-Model Deep Learning

In many deep learning (DL) applications, the desire for ever higher accu...

Kabir Nagrecha, et al. ∙

research

∙ 06/06/2021

Tempered Stable Autoregressive Models

In this article, we introduce and study a one sided tempered stable auto...

Niharika Bhootna, et al. ∙

research

∙ 05/30/2021

Normal Inverse Gaussian Autoregressive Model Using EM Algorithm

In this article, normal inverse Gaussian (NIG) autoregressive model is i...

Monika Singh Dhull, et al. ∙

research

∙ 08/13/2020

Fractional Poisson Processes of Order K

In this article, we introduce and study time- and space-fractional Poiss...

Neha Gupta, et al. ∙

research

∙ 05/16/2020

A Methodology to Assess the Human Factors Associated with Lunar Teleoperated Assembly Tasks

Low-latency telerobotics can enable more intricate surface tasks on extr...

Arun Kumar, et al. ∙

research

∙ 11/12/2019

Morphological Segmentation Inside-Out

Morphological segmentation has traditionally been modeled with non-hiera...

Ryan Cotterell, et al. ∙

research

∙ 10/02/2019

Understanding and Benchmarking the Impact of GDPR on Database Systems

The General Data Protection Regulation (GDPR) was introduced in Europe t...

Supreeth Shastri, et al. ∙

research

∙ 08/14/2019

Predicting Eating Events in Free Living Individuals -- A Technical Report

This technical report records the experiments of applying multiple machi...

Jiayi Wang, et al. ∙

research

∙ 03/29/2019

SysML: The New Frontier of Machine Learning Systems

Machine learning (ML) techniques are enjoying rapidly increasing adoptio...

Alexander Ratner, et al. ∙

research

∙ 02/02/2019

Belief dynamics extraction

Animal behavior is not driven simply by its current observations, but is...

Arun Kumar, et al. ∙

research

∙ 11/30/2018

Document Structure Measure for Hypernym discovery

Hypernym discovery is the problem of finding terms that have is-a relati...

Aswin Kannan, et al. ∙

research

∙ 11/23/2018

Fine Grained Classification of Personal Data Entities

Entity Type Classification can be defined as the task of assigning categ...

Riddhiman Dasgupta, et al. ∙

research

∙ 10/20/2018

Temporal Proximity induces Attributes Similarity

Users consume their favorite content in temporal proximity of consumptio...

Arun Kumar, et al. ∙

research

∙ 09/20/2018

Deep Domain Adaptation under Deep Label Scarcity

The goal behind Domain Adaptation (DA) is to leverage the labeled exampl...

Amar Prakash Azad, et al. ∙

research

∙ 08/23/2018

Fractional Risk Process in Insurance

Important models in insurance, for example the Carmér--Lundberg theory a...

Arun Kumar, et al. ∙

research

∙ 07/16/2018

Bipedal Walking Robot using Deep Deterministic Policy Gradient

Machine learning algorithms have found several applications in the field...

Arun Kumar, et al. ∙

research

∙ 05/26/2018

Model-based Pricing for Machine Learning in a Data Marketplace

Data analytics using machine learning (ML) has become ubiquitous in scie...

Lingjiao Chen, et al. ∙

research

∙ 01/08/2018

In-RDBMS Hardware Acceleration of Advanced Analytics

The data revolution is fueled by advances in several areas, including da...

Divya Mahajan, et al. ∙

research

∙ 09/13/2017

Dialogue Act Sequence Labeling using Hierarchical encoder with CRF

Dialogue Act recognition associate dialogue acts (i.e., semantic labels)...

Harshit Kumar, et al. ∙

research

∙ 02/22/2017

When Lempel-Ziv-Welch Meets Machine Learning: A Case Study of Accelerating Machine Learning using Coding

In this paper we study the use of coding techniques to accelerate machin...

Fengan Li, et al. ∙

research

∙ 06/15/2016

Bolt-on Differential Privacy for Scalable Stochastic Gradient Descent-based Analytics

While significant progress has been made separately on analytics systems...

Xi Wu, et al. ∙

research

∙ 08/21/2012

The MADlib Analytics Library or MAD Skills, the SQL

MADlib is a free, open source library of in-database analytic methods. I...

Joe Hellerstein, et al. ∙

Arun Kumar

Featured Co-authors

Michael I. Jordan

Hinrich Schütze

Ryan Cotterell

Ce Zhang

Christopher Ré

Dawn Song

Jing Li

Martin Jaggi

Joseph E. Gonzalez

Andrew Gordon Wilson

Song Han

Processing Analytical Queries in the AWESOME Polystore [Information Systems Architectures]

The expectation-maximization algorithm for autoregressive models with normal inverse Gaussian innovations

Hydra: A System for Large Multi-Model Deep Learning

Tempered Stable Autoregressive Models

Normal Inverse Gaussian Autoregressive Model Using EM Algorithm

Fractional Poisson Processes of Order K

A Methodology to Assess the Human Factors Associated with Lunar Teleoperated Assembly Tasks

Morphological Segmentation Inside-Out

Understanding and Benchmarking the Impact of GDPR on Database Systems

Predicting Eating Events in Free Living Individuals -- A Technical Report

SysML: The New Frontier of Machine Learning Systems

Belief dynamics extraction

Document Structure Measure for Hypernym discovery

Fine Grained Classification of Personal Data Entities

Temporal Proximity induces Attributes Similarity

Deep Domain Adaptation under Deep Label Scarcity

Fractional Risk Process in Insurance

Bipedal Walking Robot using Deep Deterministic Policy Gradient

Model-based Pricing for Machine Learning in a Data Marketplace

In-RDBMS Hardware Acceleration of Advanced Analytics

Dialogue Act Sequence Labeling using Hierarchical encoder with CRF

When Lempel-Ziv-Welch Meets Machine Learning: A Case Study of Accelerating Machine Learning using Coding

Bolt-on Differential Privacy for Scalable Stochastic Gradient Descent-based Analytics

The MADlib Analytics Library or MAD Skills, the SQL