Search Results for author: Wei Xiao

Found 38 papers, 13 papers with code

Secure Control of Connected and Automated Vehicles Using Trust-Aware Robust Event-Triggered Control Barrier Functions

1 code implementation4 Jan 2024 H M Sabbir Ahmad, Ehsan Sabouni, Akua Dickson, Wei Xiao, Christos G. Cassandras, Wenchao Li

We address the security of a network of Connected and Automated Vehicles (CAVs) cooperating to safely navigate through a conflict area (e. g., traffic intersections, merging roadways, roundabouts).

Navigate

Drive Anywhere: Generalizable End-to-end Autonomous Driving with Multi-modal Foundation Models

no code implementations26 Oct 2023 Tsun-Hsuan Wang, Alaa Maalouf, Wei Xiao, Yutong Ban, Alexander Amini, Guy Rosman, Sertac Karaman, Daniela Rus

As autonomous driving technology matures, end-to-end methodologies have emerged as a leading strategy, promising seamless integration from perception to control via deep learning.

Autonomous Driving Data Augmentation

Safe Optimal Interactions Between Automated and Human-Driven Vehicles in Mixed Traffic with Event-triggered Control Barrier Functions

no code implementations1 Oct 2023 Anni Li, Christos G. Cassandras, Wei Xiao

This paper studies safe driving interactions between Human-Driven Vehicles (HDVs) and Connected and Automated Vehicles (CAVs) in mixed traffic where the dynamics and control policies of HDVs are unknown and hard to predict.

Safe Neural Control for Non-Affine Control Systems with Differentiable Control Barrier Functions

no code implementations6 Sep 2023 Wei Xiao, Ross Allen, Daniela Rus

To address these challenges, we incorporate higher-order CBFs into neural ordinary differential equation-based learning models as differentiable CBFs to guarantee safety for non-affine control systems.

Autonomous Driving Imitation Learning

Successive one-sided Hodrick-Prescott filter with incremental filtering algorithm for nonlinear economic time series

no code implementations17 Jun 2023 Yuxia Liu, Qi Zhang, Wei Xiao, Tianguang Chu

We propose a successive one-sided Hodrick-Prescott (SOHP) filter from multiple time scale decomposition perspective to derive trend estimate for a time series.

Time Series

SafeDiffuser: Safe Planning with Diffusion Probabilistic Models

no code implementations31 May 2023 Wei Xiao, Tsun-Hsuan Wang, Chuang Gan, Daniela Rus

Diffusion model-based approaches have shown promise in data-driven planning, but there are no safety guarantees, thus making it hard to be applied for safety-critical applications.

Denoising

Trust-Aware Resilient Control and Coordination of Connected and Automated Vehicles

1 code implementation26 May 2023 H M Sabbir Ahmad, Ehsan Sabouni, Wei Xiao, Christos G. Cassandras, Wenchao Li

We address the security of a network of Connected and Automated Vehicles (CAVs) cooperating to navigate through a conflict area.

Navigate

Learning Robust and Correct Controllers from Signal Temporal Logic Specifications Using BarrierNet

no code implementations12 Apr 2023 Wenliang Liu, Wei Xiao, Calin Belta

In this paper, we consider the problem of learning a neural network controller for a system required to satisfy a Signal Temporal Logic (STL) specification.

Learning Feasibility Constraints for Control Barrier Functions

no code implementations10 Mar 2023 Wei Xiao, Christos G. Cassandras, Calin A. Belta

It has been shown that optimizing quadratic costs while stabilizing affine control systems to desired (sets of) states subject to state and control constraints can be reduced to a sequence of Quadratic Programs (QPs) by using Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs).

Autonomous Driving

Learned Risk Metric Maps for Kinodynamic Systems

1 code implementation28 Feb 2023 Ross Allen, Wei Xiao, Daniela Rus

We present Learned Risk Metric Maps (LRMM) for real-time estimation of coherent risk metrics of high dimensional dynamical systems operating in unstructured, partially observed environments.

SWING: Balancing Coverage and Faithfulness for Dialogue Summarization

1 code implementation25 Jan 2023 Kung-Hsiang Huang, Siffi Singh, Xiaofei Ma, Wei Xiao, Feng Nan, Nicholas Dingwall, William Yang Wang, Kathleen McKeown

Missing information is a common issue of dialogue summarization where some information in the reference summaries is not covered in the generated summaries.

Natural Language Inference

Interpreting Neural Policies with Disentangled Tree Representations

no code implementations13 Oct 2022 Tsun-Hsuan Wang, Wei Xiao, Tim Seyde, Ramin Hasani, Daniela Rus

The advancement of robots, particularly those functioning in complex human-centric environments, relies on control solutions that are driven by machine learning.

Disentanglement

On the Forward Invariance of Neural ODEs

no code implementations10 Oct 2022 Wei Xiao, Tsun-Hsuan Wang, Ramin Hasani, Mathias Lechner, Yutong Ban, Chuang Gan, Daniela Rus

We propose a new method to ensure neural ordinary differential equations (ODEs) satisfy output specifications by using invariance set propagation.

Autonomous Vehicles Collision Avoidance +2

Optimal Control of Connected Automated Vehicles with Event/Self-Triggered Control Barrier Functions

no code implementations26 Sep 2022 Ehsan Sabouni, Christos G. Cassandras, Wei Xiao, Nader Meskin

We address the problem of controlling Connected and Automated Vehicles (CAVs) in conflict areas of a traffic network subject to hard safety constraints.

Learning Dialogue Representations from Consecutive Utterances

1 code implementation NAACL 2022 Zhihan Zhou, Dejiao Zhang, Wei Xiao, Nicholas Dingwall, Xiaofei Ma, Andrew O. Arnold, Bing Xiang

In this paper, we introduce Dialogue Sentence Embedding (DSE), a self-supervised contrastive learning method that learns effective dialogue representations suitable for a wide range of dialogue tasks.

Contrastive Learning Conversational Question Answering +14

Self-Triggered Coordination Control of Connected Automated Vehicles in Traffic Networks

no code implementations24 Mar 2022 Nader Meskin, Ehsan Sabouni, Wei Xiao, Christos G. Cassandras

The safety constraints and the vehicle limitations are considered using the Control Barrier Function (CBF) framework and a self-triggered scheme is proposed using the CBF constraints.

Optimal Control of Connected Automated Vehicles with Event-Triggered Control Barrier Functions

no code implementations22 Mar 2022 Ehsan Sabouni, Christos G. Cassandras, Wei Xiao, Nader Meskin

We address the problem of controlling Connected and Automated Vehicles (CAVs) in conflict areas of a traffic network subject to hard safety constraints.

Feasibility Guaranteed Traffic Merging Control Using Control Barrier Functions

no code implementations8 Mar 2022 Kaiyuan Xu, Wei Xiao, Christos G. Cassandras

We consider the merging control problem for Connected and Automated Vehicles (CAVs) aiming to jointly minimize travel time and energy consumption while providing speed-dependent safety guarantees and satisfying velocity and acceleration constraints.

Differentiable Control Barrier Functions for Vision-based End-to-End Autonomous Driving

no code implementations4 Mar 2022 Wei Xiao, Tsun-Hsuan Wang, Makram Chahine, Alexander Amini, Ramin Hasani, Daniela Rus

They are interpretable at scale, achieve great test performance under limited training data, and are safety guaranteed in a series of autonomous driving scenarios such as lane keeping and obstacle avoidance.

Autonomous Driving

QaNER: Prompting Question Answering Models for Few-shot Named Entity Recognition

1 code implementation3 Mar 2022 Andy T. Liu, Wei Xiao, Henghui Zhu, Dejiao Zhang, Shang-Wen Li, Andrew Arnold

Recently, prompt-based learning for pre-trained language models has succeeded in few-shot Named Entity Recognition (NER) by exploiting prompts as task guidance to increase label efficiency.

Few-shot NER Named Entity Recognition +2

BarrierNet: A Safety-Guaranteed Layer for Neural Networks

no code implementations22 Nov 2021 Wei Xiao, Ramin Hasani, Xiao Li, Daniela Rus

This paper introduces differentiable higher-order control barrier functions (CBF) that are end-to-end trainable together with learning systems.

Virtual Augmentation Supported Contrastive Learning of Sentence Representations

1 code implementation Findings (ACL) 2022 Dejiao Zhang, Wei Xiao, Henghui Zhu, Xiaofei Ma, Andrew O. Arnold

We then define an instance discrimination task regarding this neighborhood and generate the virtual augmentation in an adversarial training manner.

Contrastive Learning Data Augmentation +2

Pairwise Supervised Contrastive Learning of Sentence Representations

1 code implementation EMNLP 2021 Dejiao Zhang, Shang-Wen Li, Wei Xiao, Henghui Zhu, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang

Many recent successes in sentence representation learning have been achieved by simply fine-tuning on the Natural Language Inference (NLI) datasets with triplet loss or siamese loss.

Contrastive Learning Natural Language Inference +4

Decentralized Time and Energy-Optimal Control of Connected and Automated Vehicles in a Roundabout

no code implementations13 Apr 2021 Kaiyuan Xu, Christos G. Cassandras, Wei Xiao

The paper considers the problem of controlling Connected and Automated Vehicles (CAVs) traveling through a three-entry roundabout so as to jointly minimize both the travel time and the energy consumption while providing speed-dependent safety guarantees, as well as satisfying velocity and acceleration constraints.

Event-Triggered Safety-Critical Control for Systems with Unknown Dynamics

no code implementations29 Mar 2021 Wei Xiao, Calin Belta, Christos G. Cassandras

We define a HOCBF for a safety requirement on the unmodelled system based on the adaptive dynamics and error states, and reformulate the safety-critical control problem as the above mentioned QP.

Rule-based Optimal Control for Autonomous Driving

no code implementations14 Jan 2021 Wei Xiao, Noushin Mehdipour, Anne Collin, Amitai Bin-Nun, Emilio Frazzoli, Radboud Duintjer Tebbens, Calin Belta

We develop optimal control strategies for Autonomous Vehicles (AVs) that are required to meet complex specifications imposed by traffic laws and cultural expectations of reasonable driving behavior.

Autonomous Driving Robotics Systems and Control Systems and Control

Feasibility-Guided Learning for Robust Control in Constrained Optimal Control Problems

no code implementations6 Dec 2019 Wei Xiao, Calin A. Belta, Christos G. Cassandras

In this paper, we further improve the feasibility robustness (i. e., feasibility maintenance in the presence of time-varying and unknown unsafe sets) through the definition of a High Order CBF (HOCBF) that works for arbitrary relative degree constraints; this is achieved by a proposed feasibility-guided learning approach.

Fast and Robust Dynamic Hand Gesture Recognition via Key Frames Extraction and Feature Fusion

1 code implementation15 Jan 2019 Hao Tang, Hong Liu, Wei Xiao, Nicu Sebe

Gesture recognition is a hot topic in computer vision and pattern recognition, which plays a vitally important role in natural human-computer interface.

Clustering Hand Gesture Recognition +1

Deep Micro-Dictionary Learning and Coding Network

1 code implementation11 Sep 2018 Hao Tang, Heng Wei, Wei Xiao, Wei Wang, Dan Xu, Yan Yan, Nicu Sebe

In this paper, we propose a novel Deep Micro-Dictionary Learning and Coding Network (DDLCN).

Dictionary Learning

An Online Algorithm for Nonparametric Correlations

1 code implementation5 Dec 2017 Wei Xiao

This paper investigates the problem of computing nonparametric correlations on the fly for streaming data.

Data Summarization Sequential Correlation Estimation

Online Robust Principal Component Analysis with Change Point Detection

2 code implementations19 Feb 2017 Wei Xiao, Xiaolin Huang, Jorge Silva, Saba Emrani, Arin Chaudhuri

Robust PCA methods are typically batch algorithms which requires loading all observations into memory before processing.

Change Point Detection Two-sample testing

Sampling Method for Fast Training of Support Vector Data Description

no code implementations16 Jun 2016 Arin Chaudhuri, Deovrat Kakde, Maria Jahja, Wei Xiao, Hansi Jiang, Seunghyun Kong, Sergiy Peredriy

Support Vector Data Description (SVDD) is a popular outlier detection technique which constructs a flexible description of the input data.

Outlier Detection

A Probabilistic Machine Learning Approach to Detect Industrial Plant Faults

no code implementations18 Mar 2016 Wei Xiao

Fault detection in industrial plants is a hot research area as more and more sensor data are being collected throughout the industrial process.

BIG-bench Machine Learning Classification +4

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