Finding an attribute to explain the relationships between a given pair of entities is valuable in many ***,many direct solutions fail,owing to its low precision caused by heavy dependence on text and low recall by evi...
详细信息
Finding an attribute to explain the relationships between a given pair of entities is valuable in many ***,many direct solutions fail,owing to its low precision caused by heavy dependence on text and low recall by evidence ***,we propose a generalization-and-inference framework and implement it to build a system:entity-relationship finder(ERF).Our main idea is conceptualizing entity pairs into proper concept pairs,as intermediate random variables to form the *** entity conceptualization has been studied,it has new challenges of collective optimization for multiple relationship instances,joint optimization for both entities,and aggregation of diluted observations into the head concepts defining the *** propose conceptualization solutions and validate them as well as the framework with extensive experiments.
The accessibility and readability of Generative Artificial Intelligence systems like GPT and Google BARD are crucial factors that require thorough examination. In today’s digitally connected world, where AI-generated...
详细信息
This paper studies the performative prediction problem where a learner aims to minimize the expected loss with a decision-dependent data distribution. Such setting is motivated when outcomes can be affected by the pre...
详细信息
This paper studies the performative prediction problem where a learner aims to minimize the expected loss with a decision-dependent data distribution. Such setting is motivated when outcomes can be affected by the prediction model, e.g., strategic classification. We consider a state-dependent setting where the data distribution evolves according to a controlled Markov chain. We focus on stochastic derivative free optimization (DFO) where the learner is given access to a loss function evaluation oracle with the above Markovian data. We propose a two-timescale DFO(λ) algorithm that features (i) a sample accumulation mechanism that utilizes every observed sample to estimate the gradient of performative risk, (ii) a two-timescale diminishing step size that balances the rates of DFO updates and bias reduction. Under a non-convex optimization setting, we show that DFO(λ) requires O(1/Ε3) samples (up to a log factor) to attain a near-stationary solution with expected squared gradient norm less than Ε. Numerical experiments verify our analysis. Copyright 2024 by the author(s)
The twenty-first century presents a number of urgent challenges, including global warming, and vehicle-to-vehicle (V2V) communication is one of the key components of an energy-efficient and sustainable transportation ...
详细信息
ISBN:
(纸本)9789819789450
The twenty-first century presents a number of urgent challenges, including global warming, and vehicle-to-vehicle (V2V) communication is one of the key components of an energy-efficient and sustainable transportation system. By adding distance sensors, our research elevates vehicle-to-vehicle (V2V) communication to a new level. This enables vehicles to share not only speed and distance information but also real-time instructions based on their proximity to other vehicles. This system of dynamic control minimizes emissions while optimizing fuel consumption. Beyond the efficiency of a single vehicle, our system uses LoRa technology to integrate with traffic light management. Our method, which treats every car as a node, gathers and analyzes data in the cloud to inform judgments about the length of red lights at intersections. This data-driven traffic analysis streamlines traffic, reduces needless stops, gives commuters time back, and improves overall fuel economy. The application of LoRa technology enhances our traffic analysis's accuracy and effectiveness. Because of its long range, LoRa enables wide-ranging and dependable communication between cars and cloud infrastructure. Because of this improved connectivity, traffic signal timings can be promptly and intelligently adjusted to reflect the dynamically changing patterns of vehicular flow. The end result is a precisely calibrated traffic management system that strategically reduces needless stops while simultaneously optimizing traffic flow and overall fuel efficiency, saving commuters valuable time. Our incorporation of LoRa technology is evidence of the revolutionary potential of sophisticated communication protocols in generating thoughtful and flexible responses to modern transportation problems. To put it briefly, our study offers a novel and comprehensive use of vehicle-to-vehicle (V2V) communication, utilizing LoRa and distance sensors to solve energy-saving issues and transform traffic control for a more env
With the advancing technology, it becomes difficult to cope up with novel trends and configurations. Similarly, it is difficult to secure the systems against each emerging threat. With this the loopholes in convention...
详细信息
In response to the escalating demand for machine learning techniques capable of handling real-time data streams, particularly in applications like stock markets, this research dives deep into the domain of stream regr...
详细信息
In recent years, the edge computing paradigm enables the movement of processing units and storage nearer to the data available locations. The mechanism completes the computation in a short span of time in minimum band...
详细信息
The task of condensing large chunks of textual information into concise and structured tables has gained attention recently due to the emergence of Large Language Models (LLMs) and their potential benefit for downstre...
详细信息
As the smart grid develops rapidly,abundant connected devices offer various trading *** raises higher requirements for secure and effective data *** centralized data management does not meet the above ***,smart grid w...
详细信息
As the smart grid develops rapidly,abundant connected devices offer various trading *** raises higher requirements for secure and effective data *** centralized data management does not meet the above ***,smart grid with conventional consortium blockchain can solve the above ***,in the face of a large number of nodes,existing consensus algorithms often perform poorly in terms of efficiency and *** this paper,we propose a trust-based hierarchical consensus mechanism(THCM)to solve this ***,we design a hierarchical mechanism to improve the efficiency and ***,intra-layer nodes use an improved Raft consensus algorithm and inter-layer nodes use the Byzantine Fault Tolerance ***,we propose a trust evaluation method to improve the election process of ***,we implement a prototype system to evaluate the performance of *** results demonstrate that the consensus efficiency is improved by 19.8%,the throughput is improved by 12.34%,and the storage is reduced by 37.9%.
Cyclone forecasting using satellite pictures involves anticipating the cyclone’s intensity in advance of its arrival. The results of this study can inform people’s preparations for the cyclone. In order to save live...
详细信息
暂无评论