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Found 15 papers, 1 papers with code
Machine Learning for Smart and Energy-Efficient Buildings
In this work, we review the ways in which machine learning has been leveraged to make buildings smart and energy-efficient.
Personalized Federated Hypernetworks for Privacy Preservation in Multi-Task Reinforcement Learning
We develop the first application of Personalized Federated Hypernetworks (PFH) to Reinforcement Learning (RL).
Multi-agent Reinforcement Learning
Personalized Federated Learning
+3
Asset Participation and Aggregation in Incentive-Based Demand Response Programs
We develop a probabilistic model for the curtailment capability of these assets, and use it to derive analytic expressions for the optimal participation (i. e., promised curtailment) and profitability from the DR asset perspective.
Conditional Synthetic Data Generation for Personal Thermal Comfort Models
Recently, machine learning algorithms have proven to be having enormous potential as a candidate for personal thermal comfort models.
Conditional Synthetic Data Generation for Robust Machine Learning Applications with Limited Pandemic Data
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.
CDCGen: Cross-Domain Conditional Generation via Normalizing Flows and Adversarial Training
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.
Optimal Sharing and Fair Cost Allocation of Community Energy Storage
Further, we demonstrate both the building-wise and community-wise economic benefits are enhanced with the ES sharing model over the individual ES (IES) model.
Fairness
Computer Science and Game Theory
Design, Benchmarking and Explainability Analysis of a Game-Theoretic Framework towards Energy Efficiency in Smart Infrastructure
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.
A Novel Graphical Lasso based approach towards Segmentation Analysis in Energy Game-Theoretic Frameworks
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.
Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms
The most surprising result is that for unweighted $K$NN classifiers and regressors, the Shapley value of all $N$ data points can be computed, exactly, in $O(N\log N)$ time -- an exponential improvement on computational complexity!
Likelihood Contribution based Multi-scale Architecture for Generative Flows
Deep generative modeling using flows has gained popularity owing to the tractable exact log-likelihood estimation with efficient training and synthesis process.
Segmentation Analysis in Human Centric Cyber-Physical Systems using Graphical Lasso
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.
Causal meets Submodular: Subset Selection with Directed Information
We study causal subset selection with Directed Information as the measure of prediction causality.
Sequential Logistic Principal Component Analysis (SLPCA): Dimensional Reduction in Streaming Multivariate Binary-State System
Sequential or online dimensional reduction is of interests due to the explosion of streaming data based applications and the requirement of adaptive statistical modeling, in many emerging fields, such as the modeling of energy end-use profile.
Environmental Sensing by Wearable Device for Indoor Activity and Location Estimation
We present results from a set of experiments in this pilot study to investigate the causal influence of user activity on various environmental parameters monitored by occupant carried multi-purpose sensors.
