no code implementations • 8 Mar 2024 • Xin Qin, Ioannis Lestas, Bolun Xu
This paper derives a theoretical framework to study the economic capacity withholding behavior of storage participating in competitive electricity markets and validate our results in simulations based on the ISO New England system.
no code implementations • 17 Sep 2023 • Navid Hashemi, Xin Qin, Lars Lindemann, Jyotirmoy V. Deshmukh
We consider data-driven reachability analysis of discrete-time stochastic dynamical systems using conformal inference.
no code implementations • 12 Aug 2023 • Xin Qin, Navid Hashemi, Lars Lindemann, Jyotirmoy V. Deshmukh
Ultimately, conformance can capture distance between design models and their real implementations and thus aid in robust system design.
1 code implementation • 25 May 2023 • Xin Qin, Jindong Wang, Shuo Ma, Wang Lu, Yongchun Zhu, Xing Xie, Yiqiang Chen
With the constructed self-supervised learning task, DDLearn enlarges the data diversity and explores the latent activity properties.
no code implementations • 3 Nov 2022 • Lars Lindemann, Xin Qin, Jyotirmoy V. Deshmukh, George J. Pappas
The second algorithm constructs prediction regions for future system states first, and uses these to obtain a prediction region for the satisfaction measure.
no code implementations • 14 Oct 2022 • Navid Hashemi, Xin Qin, Jyotirmoy V. Deshmukh, Georgios Fainekos, Bardh Hoxha, Danil Prokhorov, Tomoya Yamaguchi
In this paper, we consider the problem of synthesizing a controller in the presence of uncertainty such that the resulting closed-loop system satisfies certain hard constraints while optimizing certain (soft) performance objectives.
1 code implementation • 21 Jul 2022 • Xin Qin, Jindong Wang, Yiqiang Chen, Wang Lu, Xinlong Jiang
To this end, we propose \emph{Adaptive Feature Fusion for Activity Recognition~(AFFAR)}, a domain generalization approach that learns to fuse the domain-invariant and domain-specific representations to improve the model's generalization performance.
no code implementations • 14 Jul 2022 • Ningkun Zheng, Xin Qin, Di wu, Gabe Murtaugh, Bolun Xu
Combined with an optimal bidding design algorithm using dynamic programming, our paper shows that the SoC segment market model provides more accurate representations of the opportunity costs of energy storage compared to existing power-based bidding models.
2 code implementations • 17 Jun 2022 • Yiqiang Chen, Wang Lu, Xin Qin, Jindong Wang, Xing Xie
Federated learning has attracted increasing attention to building models without accessing the raw user data, especially in healthcare.
no code implementations • 14 Jun 2022 • Wang Lu, Jindong Wang, Yiqiang Chen, Sinno Jialin Pan, Chunyu Hu, Xin Qin
Training on existing data often makes the model biased towards the distribution of the training data, thus the model might perform terribly on test data with different distributions.
1 code implementation • 1 Dec 2021 • Wang Lu, Jindong Wang, Yiqiang Chen, Xin Qin, Renjun Xu, Dimitrios Dimitriadis, Tao Qin
There is a growing interest in applying machine learning techniques to healthcare.
no code implementations • 30 Jun 2021 • Hanbin Zhao, Xin Qin, Shihao Su, Yongjian Fu, Zibo Lin, Xi Li
With the rapid development of social media, tremendous videos with new classes are generated daily, which raise an urgent demand for video classification methods that can continuously update new classes while maintaining the knowledge of old videos with limited storage and computing resources.
no code implementations • 2 Jun 2021 • Yiqiang Chen, Wang Lu, Jindong Wang, Xin Qin
The success of machine learning applications often needs a large quantity of data.
no code implementations • 15 May 2021 • ZiFan Chen, Xin Qin, Chao Yang, Li Zhang
This work proposes a novel deep learning framework for human pose estimation called composite localization to divide the complex learning objective into two simpler ones: a sparse heatmap to find the keypoint's approximate location and two short-distance offsetmaps to obtain its final precise coordinates.
no code implementations • 9 Mar 2021 • Xin Qin, Hanbin Zhao, Guangchen Lin, Hao Zeng, Songcen Xu, Xi Li
In this paper, we propose a temporal-position-sensitive context modeling approach to incorporate both positional and semantic information for more precise action localization.
1 code implementation • 29 Jan 2021 • Wang Lu, Yiqiang Chen, Jindong Wang, Xin Qin
In this paper, we propose substructure-level matching for domain adaptation (SSDA) to better utilize the locality information of activity data for accurate and efficient knowledge transfer.
no code implementations • 24 Jul 2020 • Hanbin Zhao, Hao Zeng, Xin Qin, Yongjian Fu, Hui Wang, Bourahla Omar, Xi Li
As an important and challenging problem, multi-domain learning (MDL) typically seeks for a set of effective lightweight domain-specific adapter modules plugged into a common domain-agnostic network.
no code implementations • 1 Apr 2020 • Chuchu Fan, Xin Qin, Yuan Xia, Aditya Zutshi, Jyotirmoy Deshmukh
Our technique uses model simulations to learn {\em surrogate models}, and uses {\em conformal inference} to provide probabilistic guarantees on the satisfaction of a given STL property.
1 code implementation • 29 Jan 2020 • Yiqiang Chen, Xiaodong Yang, Xin Qin, Han Yu, Biao Chen, Zhiqi Shen
It maintains a small set of benchmark samples on the FL server and quantifies the credibility of the client local data without directly observing them by computing the mutual cross-entropy between performance of the FL model on the local datasets and that of the client local FL model on the benchmark dataset.
no code implementations • 30 Oct 2019 • Xin Qin, Nikos Aréchiga, Andrew Best, Jyotirmoy Deshmukh
We propose an interactive multi-agent framework where the system-under-design is modeled as an ego agent and its environment is modeled by a number of adversarial (ado) agents.
no code implementations • 22 Jul 2019 • Yiqiang Chen, Jindong Wang, Chaohui Yu, Wen Gao, Xin Qin
It is able to achieve accurate and personalized healthcare without compromising privacy and security.