Search Results for author: Weijia Zhang

Found 25 papers, 14 papers with code

Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Models

1 code implementation30 Jan 2024 Weijia Zhang, Jindong Han, Zhao Xu, Hang Ni, Hao liu, Hui Xiong

Machine learning techniques are now integral to the advancement of intelligent urban services, playing a crucial role in elevating the efficiency, sustainability, and livability of urban environments.

LLMLight: Large Language Models as Traffic Signal Control Agents

1 code implementation26 Dec 2023 Siqi Lai, Zhao Xu, Weijia Zhang, Hao liu, Hui Xiong

Traffic Signal Control (TSC) is a crucial component in urban traffic management, aiming to optimize road network efficiency and reduce congestion.

Decision Making Management +1

Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability Guarantees

1 code implementation24 Dec 2023 Weijia Zhang, Chun Kai Ling, Xuanhui Zhang

Censoring is the central problem in survival analysis where either the time-to-event (for instance, death), or the time-tocensoring (such as loss of follow-up) is observed for each sample.

Survival Analysis

ODM3D: Alleviating Foreground Sparsity for Semi-Supervised Monocular 3D Object Detection

1 code implementation28 Oct 2023 Weijia Zhang, Dongnan Liu, Chao Ma, Weidong Cai

Monocular 3D object detection (M3OD) is a significant yet inherently challenging task in autonomous driving due to absence of explicit depth cues in a single RGB image.

Autonomous Driving Data Augmentation +5

Chain-of-Choice Hierarchical Policy Learning for Conversational Recommendation

1 code implementation27 Oct 2023 Wei Fan, Weijia Zhang, Weiqi Wang, Yangqiu Song, Hao liu

Conversational Recommender Systems (CRS) illuminate user preferences via multi-round interactive dialogues, ultimately navigating towards precise and satisfactory recommendations.

Attribute Hierarchical Reinforcement Learning +1

Machine Learning for Urban Air Quality Analytics: A Survey

no code implementations14 Oct 2023 Jindong Han, Weijia Zhang, Hao liu, Hui Xiong

In this article, we present a comprehensive survey of ML-based air quality analytics, following a roadmap spanning from data acquisition to pre-processing, and encompassing various analytical tasks such as pollution pattern mining, air quality inference, and forecasting.

Air Quality Inference

Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Network

no code implementations31 Aug 2023 Weijia Zhang, Le Zhang, Jindong Han, Hao liu, Jingbo Zhou, Yu Mei, Hui Xiong

Accurate traffic forecasting at intersections governed by intelligent traffic signals is critical for the advancement of an effective intelligent traffic signal control system.

Time Series Time Series Forecasting

A Preference-aware Meta-optimization Framework for Personalized Vehicle Energy Consumption Estimation

1 code implementation26 Jun 2023 Siqi Lai, Weijia Zhang, Hao liu

To this end, this paper proposes a preference-aware meta-optimization framework Meta-Pec for personalized vehicle energy consumption estimation.

Memorization Total Energy

SegT: A Novel Separated Edge-guidance Transformer Network for Polyp Segmentation

no code implementations19 Jun 2023 Feiyu Chen, Haiping Ma, Weijia Zhang

To address the aforementioned issues, we propose a novel separated edge-guidance transformer (SegT) network that aims to build an effective polyp segmentation model.

Segmentation

Rethinking the Value of Labels for Instance-Dependent Label Noise Learning

no code implementations10 May 2023 Hanwen Deng, Weijia Zhang, Min-Ling Zhang

Label noise widely exists in large-scale datasets and significantly degenerates the performances of deep learning algorithms.

Representation Learning

Transformer-based Multi-Instance Learning for Weakly Supervised Object Detection

no code implementations27 Mar 2023 Zhaofei Wang, Weijia Zhang, Min-Ling Zhang

However, since such approaches only utilize the highest score proposal and discard the potentially useful information from other proposals, their independent MIL backbone often limits models to salient parts of an object or causes them to detect only one object per class.

Object object-detection +1

Multi-Instance Partial-Label Learning: Towards Exploiting Dual Inexact Supervision

1 code implementation18 Dec 2022 Wei Tang, Weijia Zhang, Min-Ling Zhang

MIPLGP first assigns each instance with a candidate label set in an augmented label space, then transforms the candidate label set into a logarithmic space to yield the disambiguated and continuous labels via an exclusive disambiguation strategy, and last induces a model based on the Gaussian processes.

Gaussian Processes Partial Label Learning

MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal

no code implementations12 Jul 2021 Weijia Zhang, Hao liu, Lijun Zha, HengShu Zhu, Ji Liu, Dejing Dou, Hui Xiong

Real estate appraisal refers to the process of developing an unbiased opinion for real property's market value, which plays a vital role in decision-making for various players in the marketplace (e. g., real estate agents, appraisers, lenders, and buyers).

Decision Making Graph Representation Learning +1

Intelligent Electric Vehicle Charging Recommendation Based on Multi-Agent Reinforcement Learning

1 code implementation15 Feb 2021 Weijia Zhang, Hao liu, Fan Wang, Tong Xu, Haoran Xin, Dejing Dou, Hui Xiong

Electric Vehicle (EV) has become a preferable choice in the modern transportation system due to its environmental and energy sustainability.

Multi-agent Reinforcement Learning reinforcement-learning +1

A unified survey of treatment effect heterogeneity modeling and uplift modeling

no code implementations14 Jul 2020 Weijia Zhang, Jiuyong Li, Lin Liu

A central question in many fields of scientific research is to determine how an outcome would be affected by an action, or to measure the effect of an action (a. k. a treatment effect).

Marketing

A general framework for causal classification

no code implementations25 Mar 2020 Jiuyong Li, Weijia Zhang, Lin Liu, Kui Yu, Thuc Duy Le, Jixue Liu

We also propose a general framework for causal classification, by using off-the-shelf supervised methods for flexible implementations.

Classification Decision Making +2

Treatment effect estimation with disentangled latent factors

2 code implementations29 Jan 2020 Weijia Zhang, Lin Liu, Jiuyong Li

Much research has been devoted to the problem of estimating treatment effects from observational data; however, most methods assume that the observed variables only contain confounders, i. e., variables that affect both the treatment and the outcome.

Variational Inference

Semi-Supervised Hierarchical Recurrent Graph Neural Network for City-Wide Parking Availability Prediction

1 code implementation24 Nov 2019 Weijia Zhang, Hao liu, Yanchi Liu, Jingbo Zhou, Hui Xiong

However, it is a non-trivial task for predicting citywide parking availability because of three major challenges: 1) the non-Euclidean spatial autocorrelation among parking lots, 2) the dynamic temporal autocorrelation inside of and between parking lots, and 3) the scarcity of information about real-time parking availability obtained from real-time sensors (e. g., camera, ultrasonic sensor, and GPS).

Clustering

A Deep Neural Information Fusion Architecture for Textual Network Embeddings

no code implementations IJCNLP 2019 Zenan Xu, Qinliang Su, Xiaojun Quan, Weijia Zhang

Textual network embeddings aim to learn a low-dimensional representation for every node in the network so that both the structural and textual information from the networks can be well preserved in the representations.

Robust Multi-instance Learning with Stable Instances

no code implementations13 Feb 2019 Weijia Zhang, Jiuyong Li, Lin Liu

Multi-instance learning (MIL) deals with tasks where data is represented by a set of bags and each bag is described by a set of instances.

Causal Inference Image Classification

Cannot find the paper you are looking for? You can Submit a new open access paper.