2 citations · 3 across the 7 of their papers we have counts for
7 papers
Modeling Coincident Peak Pricing in Electricity Markets: Challenges and Peak Shaving Effectiveness
Qian Zhang, Sadie Zhao, Lucy Diao +4
Coincident Peak (CP) pricing is widely used in U.S. electricity markets to allocate capacity and transmission costs. This paper develops a behavioral game-theoretic framework for C…
Provably Efficient Sensor Allocation for Unknown High-dimensional Systems with Limited Sensing
Yuyang Zhang, Derya Cansever, Na Li
This paper focuses on learning efficient sensor allocations that ensure observability of unknown high-dimensional linear systems using only a small number of sensors. Existing meth…
ViTCAE: ViT-based Class-conditioned Autoencoder
Vahid Jebraeeli, Hamid Krim, Derya Cansever
Vision Transformer (ViT) based autoencoders often underutilize the global Class token and employ static attention mechanisms, limiting both generative control and optimization effi…
Generative Expansion of Small Datasets: An Expansive Graph Approach
Vahid Jebraeeli, Bo Jiang, Hamid Krim +1
Limited data availability in machine learning significantly impacts performance and generalization. Traditional augmentation methods enhance moderately sufficient datasets. GANs st…
Koopcon: A new approach towards smarter and less complex learning
Vahid Jebraeeli, Bo Jiang, Derya Cansever +1
In the era of big data, the sheer volume and complexity of datasets pose significant challenges in machine learning, particularly in image processing tasks. This paper introduces a…
Implicit Bayes Adaptation: A Collaborative Transport Approach
Bo Jiang, Hamid Krim, Tianfu Wu +1
The power and flexibility of Optimal Transport (OT) have pervaded a wide spectrum of problems, including recent Machine Learning challenges such as unsupervised domain adaptation.…
Refining Self-Supervised Learning in Imaging: Beyond Linear Metric
Bo Jiang, Hamid Krim, Tianfu Wu +1
We introduce in this paper a new statistical perspective, exploiting the Jaccard similarity metric, as a measure-based metric to effectively invoke non-linear features in the loss…