Search Results for author: Xin Qin

Found 21 papers, 6 papers with code

Economic Capacity Withholding Bounds of Competitive Energy Storage Bidders

no code implementations8 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.

Data-Driven Reachability Analysis of Stochastic Dynamical Systems with Conformal Inference

no code implementations17 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.

Conformance Testing for Stochastic Cyber-Physical Systems

no code implementations12 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.

Conformal Prediction

Conformal Prediction for STL Runtime Verification

no code implementations3 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.

Conformal Prediction Uncertainty Quantification

Risk-Awareness in Learning Neural Controllers for Temporal Logic Objectives

no code implementations14 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.

Domain Generalization for Activity Recognition via Adaptive Feature Fusion

1 code implementation21 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.

Domain Generalization Human Activity Recognition

Energy Storage State-of-Charge Market Model

no code implementations14 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.

MetaFed: Federated Learning among Federations with Cyclic Knowledge Distillation for Personalized Healthcare

2 code implementations17 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.

Federated Learning Knowledge Distillation

Semantic-Discriminative Mixup for Generalizable Sensor-based Cross-domain Activity Recognition

no code implementations14 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.

Cross-Domain Activity Recognition Domain Adaptation +2

When Video Classification Meets Incremental Classes

no code implementations30 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.

Classification Class Incremental Learning +3

Composite Localization for Human Pose Estimation

no code implementations15 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.

Distance regression Pose Estimation

PcmNet: Position-Sensitive Context Modeling Network for Temporal Action Localization

no code implementations9 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.

Boundary Detection Position +3

Cross-domain Activity Recognition via Substructural Optimal Transport

1 code implementation29 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.

Clustering Cross-Domain Activity Recognition +3

What and Where: Learn to Plug Adapters via NAS for Multi-Domain Learning

no code implementations24 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.

Neural Architecture Search

Statistical Verification of Autonomous Systems using Surrogate Models and Conformal Inference

no code implementations1 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.

Autonomous Vehicles Prediction Intervals

FOCUS: Dealing with Label Quality Disparity in Federated Learning

1 code implementation29 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.

Federated Learning Privacy Preserving

Automatic Testing With Reusable Adversarial Agents

no code implementations30 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.

Self-Driving Cars

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