no code implementations • 20 Feb 2025 • Yannick Wölker, Arash Hajisafi, Cyrus Shahabi, Matthias Renz
Unlike typical GNN methods that treat each traffic sensor as an individual graph node, DeepStateGNN clusters sensors into higher-level graph nodes, dubbed Deep State Nodes, based on various similarity criteria, resulting in a fixed number of nodes in a Deep State graph.
no code implementations • 14 Dec 2024 • Arash Hajisafi, Maria Despoina Siampou, Bita Azarijoo, Cyrus Shahabi
Accurately modeling and analyzing time series data is crucial for downstream applications across various fields, including healthcare, finance, astronomy, and epidemiology.
no code implementations • 22 Nov 2024 • Ziyao Li, Shang-Ling Hsu, Cyrus Shahabi
To address this challenge, we propose a model designed to predict a new POI outside the training data as long as its context is aligned with the user's interests.
no code implementations • 9 Nov 2024 • Sepanta Zeighami, Cyrus Shahabi
Machine learning models have demonstrated substantial performance enhancements over non-learned alternatives in various fundamental data management operations, including indexing (locating items in an array), cardinality estimation (estimating the number of matching records in a database), and range-sum estimation (estimating aggregate attribute values for query-matched records).
1 code implementation • 7 Nov 2024 • Shang-Ling Hsu, Emmanuel Tung, John Krumm, Cyrus Shahabi, Khurram Shafique
TrajGPT integrates the spatial and temporal models in a transformer architecture through a Bayesian probability model that ensures that the gaps in a visit sequence are filled in a spatiotemporally consistent manner.
no code implementations • 27 Aug 2024 • Maria Despoina Siampou, Jialiang Li, John Krumm, Cyrus Shahabi, Hua Lu
Encoding geospatial data is crucial for enabling machine learning (ML) models to perform tasks that require spatial reasoning, such as identifying the topological relationships between two different geospatial objects.
1 code implementation • 25 Aug 2024 • Siyu Li, Toan Tran, Haowen Lin, John Krumm, Cyrus Shahabi, Li Xiong
Simulating human mobility data is essential for various application domains, including transportation, urban planning, and epidemic control, since real data are often inaccessible to researchers due to expensive costs and privacy issues.
no code implementations • 24 Aug 2024 • Sina Shaham, Gabriel Ghinita, Bhaskar Krishnamachari, Cyrus Shahabi
We introduce {\em STPT (Spatio-Temporal Private Timeseries)}, a novel method for DP-compliant publication of electricity consumption data that analyzes spatio-temporal attributes and captures both micro and macro patterns by leveraging RNNs.
1 code implementation • 8 May 2024 • Arash Hajisafi, Haowen Lin, Yao-Yi Chiang, Cyrus Shahabi
This paper introduces NeuroGNN, a dynamic Graph Neural Network (GNN) framework that captures the dynamic interplay between the EEG electrode locations and the semantics of their corresponding brain regions.
no code implementations • 17 Feb 2024 • Sepanta Zeighami, Cyrus Shahabi
We show that statistical debiasing, although in some cases useful, often fails to improve accuracy.
no code implementations • 28 Jul 2023 • Sina Shaham, Arash Hajisafi, Minh K Quan, Dinh C Nguyen, Bhaskar Krishnamachari, Charith Peris, Gabriel Ghinita, Cyrus Shahabi, Pubudu N. Pathirana
Privacy and fairness are two crucial pillars of responsible Artificial Intelligence (AI) and trustworthy Machine Learning (ML).
1 code implementation • 28 Jun 2023 • Arash Hajisafi, Haowen Lin, Sina Shaham, Haoji Hu, Maria Despoina Siampou, Yao-Yi Chiang, Cyrus Shahabi
Forecasting the number of visits to Points-of-Interest (POI) in an urban area is critical for planning and decision-making for various application domains, from urban planning and transportation management to public health and social studies.
no code implementations • 19 Jun 2023 • Sepanta Zeighami, Cyrus Shahabi
In this paper, we significantly strengthen this result, showing that under mild assumptions on data distribution, and the same space complexity as non-learned methods, learned indexes can answer queries in $O(\log\log n)$ expected query time.
no code implementations • 5 Feb 2023 • Sina Shaham, Gabriel Ghinita, Cyrus Shahabi
We propose techniques to mitigate location bias in machine learning.
no code implementations • 4 Apr 2022 • Sina Shaham, Gabriel Ghinita, Cyrus Shahabi
We introduce the concept of spatial data fairness to address the specific challenges of location data and spatial queries.
no code implementations • 7 Oct 2021 • Kien Nguyen, John Krumm, Cyrus Shahabi
The Gaussian process is a powerful and flexible technique for interpolating spatiotemporal data, especially with its ability to capture complex trends and uncertainty from the input signal.
no code implementations • 27 Sep 2021 • Chenyu Wang, Zongyu Lin, Xiaochen Yang, Jiao Sun, Mingxuan Yue, Cyrus Shahabi
Based on the homophily assumption of GNN, we propose a homophily-aware constraint to regularize the optimization of the region graph so that neighboring region nodes on the learned graph share similar crime patterns, thus fitting the mechanism of diffusion convolution.
no code implementations • 21 Aug 2021 • Haowen Lin, Jian Lou, Li Xiong, Cyrus Shahabi
Federated learning enables multiple clients, such as mobile phones and organizations, to collaboratively learn a shared model for prediction while protecting local data privacy.
no code implementations • ICCV 2021 • Haowen Lin, Jian Lou, Li Xiong, Cyrus Shahabi
Adversarial data examples have drawn significant attention from the machine learning and security communities.
1 code implementation • 14 Dec 2020 • Sirisha Rambhatla, Sepanta Zeighami, Kameron Shahabi, Cyrus Shahabi, Yan Liu
As countries look towards re-opening of economic activities amidst the ongoing COVID-19 pandemic, ensuring public health has been challenging.
no code implementations • 7 Oct 2020 • Sasan Tavakkol, Feng Han, Brandon Mayer, Mark Phillips, Cyrus Shahabi, Yao-Yi Chiang, Raimondas Kiveris
We introduce the modular and scalable design of Kartta Labs, an open source, open data, and scalable system for virtually reconstructing cities from historical maps and photos.
no code implementations • 25 Aug 2020 • Kien Nguyen, John Krumm, Cyrus Shahabi
Users concerned about privacy may want to charge more for data that pinpoints their location accurately, but may charge less for data that is more vague.
no code implementations • 3 Mar 2020 • Mingxuan Yue, Yaguang Li, Haoze Yang, Ritesh Ahuja, Yao-Yi Chiang, Cyrus Shahabi
Identifying mobility behaviors in rich trajectory data is of great economic and social interest to various applications including urban planning, marketing and intelligence.
1 code implementation • 27 Jun 2019 • Chaoyang He, Tian Xie, Yu Rong, Wenbing Huang, Junzhou Huang, Xiang Ren, Cyrus Shahabi
Existing techniques either cannot be scaled to large-scale bipartite graphs that have limited labels or cannot exploit the unique structure of bipartite graphs, which have distinct node features in two domains.
no code implementations • 26 Aug 2017 • Minh Nguyen, Sanjay Purushotham, Hien To, Cyrus Shahabi
Multivariate time series (MTS) have become increasingly common in healthcare domains where human vital signs and laboratory results are collected for predictive diagnosis.
18 code implementations • ICLR 2018 • Yaguang Li, Rose Yu, Cyrus Shahabi, Yan Liu
Spatiotemporal forecasting has various applications in neuroscience, climate and transportation domain.
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1 code implementation • 4 May 2017 • Hien To, Sumeet Agrawal, Seon Ho Kim, Cyrus Shahabi
Social media such as tweets are emerging as platforms contributing to situational awareness during disasters.
no code implementations • 21 Jan 2017 • Dingxiong Deng, Fan Bai, Yiqi Tang, Shuigeng Zhou, Cyrus Shahabi, Linhong Zhu
In this paper, for the first time, we study label propagation in heterogeneous graphs under heterophily assumption.