Search Results for author: Hari Prasanna Das

Found 9 papers, 0 papers with code

Machine Learning for Smart and Energy-Efficient Buildings

no code implementations27 Nov 2022 Hari Prasanna Das, Yu-Wen Lin, Utkarsha Agwan, Lucas Spangher, Alex Devonport, Yu Yang, Jan Drgona, Adrian Chong, Stefano Schiavon, Costas J. Spanos

In this work, we review the ways in which machine learning has been leveraged to make buildings smart and energy-efficient.

Conditional Synthetic Data Generation for Personal Thermal Comfort Models

no code implementations10 Mar 2022 Hari Prasanna Das, Costas J. Spanos

Recently, machine learning algorithms have proven to be having enormous potential as a candidate for personal thermal comfort models.

BIG-bench Machine Learning Privacy Preserving +1

Multi-source Few-shot Domain Adaptation

no code implementations25 Sep 2021 Xiangyu Yue, Zangwei Zheng, Colorado Reed, Hari Prasanna Das, Kurt Keutzer, Alberto Sangiovanni Vincentelli

Multi-source Domain Adaptation (MDA) aims to transfer predictive models from multiple, fully-labeled source domains to an unlabeled target domain.

Domain Adaptation Self-Supervised Learning

Conditional Synthetic Data Generation for Robust Machine Learning Applications with Limited Pandemic Data

no code implementations14 Sep 2021 Hari Prasanna Das, Ryan Tran, Japjot Singh, Xiangyu Yue, Geoff Tison, Alberto Sangiovanni-Vincentelli, Costas J. Spanos

To tackle the challenges of limited data, and label scarcity in the available data, we propose generating conditional synthetic data, to be used alongside real data for developing robust ML models.

BIG-bench Machine Learning Computed Tomography (CT) +2

CDCGen: Cross-Domain Conditional Generation via Normalizing Flows and Adversarial Training

no code implementations25 Aug 2021 Hari Prasanna Das, Ryan Tran, Japjot Singh, Yu-Wen Lin, Costas J. Spanos

We also learn the joint distribution of the data samples and attributes in the source domain by employing an encoder to map attributes to the latent space via adversarial training.

Attribute Synthetic Data Generation +1

Design, Benchmarking and Explainability Analysis of a Game-Theoretic Framework towards Energy Efficiency in Smart Infrastructure

no code implementations16 Oct 2019 Ioannis C. Konstantakopoulos, Hari Prasanna Das, Andrew R. Barkan, Shiying He, Tanya Veeravalli, Huihan Liu, Aummul Baneen Manasawala, Yu-Wen Lin, Costas J. Spanos

In this paper, we propose a gamification approach as a novel framework for smart building infrastructure with the goal of motivating human occupants to reconsider personal energy usage and to have positive effects on their environment.

Benchmarking Decision Making

A Novel Graphical Lasso based approach towards Segmentation Analysis in Energy Game-Theoretic Frameworks

no code implementations5 Oct 2019 Hari Prasanna Das, Ioannis C. Konstantakopoulos, Aummul Baneen Manasawala, Tanya Veeravalli, Huihan Liu, Costas J. Spanos

A number of such frameworks have been introduced over the years which formulate the energy saving process as a competitive game with appropriate incentives for energy efficient players.

Decision Making Segmentation

Likelihood Contribution based Multi-scale Architecture for Generative Flows

no code implementations5 Aug 2019 Hari Prasanna Das, Pieter Abbeel, Costas J. Spanos

Deep generative modeling using flows has gained popularity owing to the tractable exact log-likelihood estimation with efficient training and synthesis process.

Dimensionality Reduction

Segmentation Analysis in Human Centric Cyber-Physical Systems using Graphical Lasso

no code implementations24 Oct 2018 Hari Prasanna Das, Ioannis C. Konstantakopoulos, Aummul Baneen Manasawala, Tanya Veeravalli, Huihan Liu, Costas J. Spanos

A generalized gamification framework is introduced as a form of smart infrastructure with potential to improve sustainability and energy efficiency by leveraging humans-in-the-loop strategy.

Decision Making Segmentation

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