A common issue in learning decision-making policies in data-rich settings is spurious correlations in the offline dataset, which can be caused by hidden confounders. Instrumental variable (IV) regression, which utilis...
详细信息
A common issue in learning decision-making policies in data-rich settings is spurious correlations in the offline dataset, which can be caused by hidden confounders. Instrumental variable (IV) regression, which utilises a key unconfounded variable known as the instrument, is a standard technique for learning causal relationships between confounded action, outcome, and context variables. Most recent IV regression algorithms use a two-stage approach, where a deep neural network (DNN) estimator learnt in the first stage is directly plugged into the second stage, in which another DNN is used to estimate the causal effect. Naively plugging the estimator can cause heavy bias in the second stage, especially when regularisation bias is present in the first stage estimator. We propose DML-IV, a non-linear IV regression method that reduces the bias in two-stage IV regressions and effectively learns high-performing policies. We derive a novel learning objective to reduce bias and design the DML-IV algorithm following the double/debiased machine learning (DML) framework. The learnt DML-IV estimator has strong convergence rate and O(N−1/2) suboptimality guarantees that match those when the dataset is unconfounded. DML-IV outperforms state-of-the-art IV regression methods on IV regression benchmarks and learns high-performing policies in the presence of instruments. Copyright 2024 by the author(s)
The rapidly changing urban landscape introduces unprecedented challenges to mobility and security, especially for the visually impaired and surveillance operators. All existing assistive technologies and monitoring sy...
详细信息
Interacting with object instances is crucial in specific embodied tasks such as rescue and industrial services, not just navigating to the target. Previous research on Object Goal Navigation (ObjNav) has only addresse...
详细信息
This paper presents an integrated framework for the comprehensive analysis of diseases affecting pomegranate fruit. The suggested system, which makes use of deep learning techniques, includes semantic segmentation for...
详细信息
Precision agriculture is responsible for the agricultural industry's recent boom;this paper discusses the creation of the Cloud Based Agricultural Monitoring System Precision Farming (CAMS-PF). To fully use of clo...
详细信息
In urban environments, efficient ambulance response times are critical for saving lives. This paper proposes a novel approach utilizing a multi-sensor integration system for improving ambulance control and traffic man...
详细信息
ISBN:
(纸本)9798350364828
In urban environments, efficient ambulance response times are critical for saving lives. This paper proposes a novel approach utilizing a multi-sensor integration system for improving ambulance control and traffic management. The system combines Radio Frequency Identification (RFID) sensors, cameras, and microphones to enhance the responsiveness of ambulance drivers and alleviate traffic congestion. The RFID sensors are strategically placed along the ambulance route to facilitate seamless communication between the ambulance and traffic signals. When an ambulance approaches, the RFID sensors trigger pre-programmed traffic signal adjustments, such as extending green lights or halting conflicting traffic flow, to expedite the ambulance's passage. Simultaneously, the camera-based detection system identifies the presence of ambulances in traffic and assesses congestion levels in real-time. Utilizing computer vision algorithms, the system analyzes live camera feeds to detect ambulance vehicles and evaluate traffic density and movement patterns. This information enables dynamic rerouting of ambulances to less congested routes, optimizing response times and minimizing delays. Furthermore, a microphone array is employed to detect the distinct audio signature of ambulance sirens. By leveraging sound analysis techniques, the system accurately identifies the approach of an ambulance and triggers additional traffic management measures, such as prioritizing ambulance lanes or temporarily rerouting vehicles to clear a path. Integration of these sensor technologies into a unified control system offers a comprehensive solution for improving ambulance navigation through urban traffic. Through proactive traffic signal adjustments, dynamic route optimization, and real-time siren detection, the proposed system enhances overall emergency response effectiveness while reducing the risk of traffic-related delays and accidents. Moreover, the system's adaptability and scalability make it suit
Fake Facebook accounts can be used to spread misinformation or invade privacy. Traditional methods of identifying fake accounts are time- consuming, inefficient, and unreliable. Black-box AI models can make biased or ...
详细信息
Skin lesions encompass a broad spectrum of skin abnormalities, including benign moles, cysts, and various types of skin cancer. Skin lesion is amongst the most common group of cancer diagnosed worldwide with several t...
详细信息
Impulse radio ultra-wideband (IR-UWB) radars are increasingly utilized for human fall detection owing to their non-contact, high precision, and high privacy attributes. However, the existing single-branch networks-bas...
详细信息
暂无评论