Search Results for author: Haimonti Dutta

Found 7 papers, 3 papers with code

Consensus Based Multi-Layer Perceptrons for Edge Computing

no code implementations9 Feb 2021 Haimonti Dutta, Nitin Nataraj, Saurabh Amarnath Mahindre

Assuming nodes (devices) in the distributed system are arranged in a graph and contain vertically partitioned data, the goal is to learn a global function that minimizes the loss.

Edge-computing

Impact of Community Structure on Consensus Machine Learning

no code implementations2 Nov 2020 Bao Huynh, Haimonti Dutta, Dane Taylor

Here, we analyze the effect on $\tau_\epsilon$ of network community structure, which can arise when compute nodes/sensors are spatially clustered, for example.

BIG-bench Machine Learning

A Machine Learning Approach to Quantitative Prosopography

no code implementations30 Jan 2018 Aayushee Gupta, Haimonti Dutta, Srikanta Bedathur, Lipika Dey

Prosopography is an investigation of the common characteristics of a group of people in history, by a collective study of their lives.

BIG-bench Machine Learning NER

Demo Abstract: NILMTK v0.2: A Non-intrusive Load Monitoring Toolkit for Large Scale Data Sets

2 code implementations20 Sep 2014 Jack Kelly, Nipun Batra, Oliver Parson, Haimonti Dutta, William Knottenbelt, Alex Rogers, Amarjeet Singh, Mani Srivastava

In this demonstration, we present an open source toolkit for evaluating non-intrusive load monitoring research; a field which aims to disaggregate a household's total electricity consumption into individual appliances.

Other Computer Science

Consensus-Based Modelling using Distributed Feature Construction

no code implementations11 Sep 2014 Haimonti Dutta, Ashwin Srinivasan

That is, there is a network of computational units, each of which employs an ILP engine to construct some small number of features and then builds a (local) model.

Inductive logic programming

NILMTK: An Open Source Toolkit for Non-intrusive Load Monitoring

2 code implementations15 Apr 2014 Nipun Batra, Jack Kelly, Oliver Parson, Haimonti Dutta, William Knottenbelt, Alex Rogers, Amarjeet Singh, Mani Srivastava

We demonstrate the range of reproducible analyses which are made possible by our toolkit, including the analysis of six publicly available data sets and the evaluation of both benchmark disaggregation algorithms across such data sets.

Applications

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