Search Results for author: Sina Shaham

Found 8 papers, 0 papers with code

Holistic Survey of Privacy and Fairness in Machine Learning

no code implementations28 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).

Fairness

Learning Dynamic Graphs from All Contextual Information for Accurate Point-of-Interest Visit Forecasting

no code implementations28 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.

Decision Making Management +2

Models and Mechanisms for Spatial Data Fairness

no code implementations4 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.

Decision Making Fairness

Multi-modal Misinformation Detection: Approaches, Challenges and Opportunities

no code implementations25 Mar 2022 Sara Abdali, Sina Shaham, Bhaskar Krishnamachari

As social media platforms are evolving from text-based forums into multi-modal environments, the nature of misinformation in social media is also transforming accordingly.

Misinformation

When Machine Learning Meets Privacy: A Survey and Outlook

no code implementations24 Nov 2020 Bo Liu, Ming Ding, Sina Shaham, Wenny Rahayu, Farhad Farokhi, Zihuai Lin

The newly emerged machine learning (e. g. deep learning) methods have become a strong driving force to revolutionize a wide range of industries, such as smart healthcare, financial technology, and surveillance systems.

BIG-bench Machine Learning

Privacy Preserving Location Data Publishing: A Machine Learning Approach

no code implementations24 Feb 2019 Sina Shaham, Ming Ding, Bo Liu, Shuping Dang, Zihuai Lin, Jun Li

By introducing a new formulation of the problem, we are able to apply machine learning algorithms for clustering the trajectories and propose to use $k$-means algorithm for this purpose.

BIG-bench Machine Learning Clustering +2

Privacy Preservation in Location-Based Services: A Novel Metric and Attack Model

no code implementations16 May 2018 Sina Shaham, Ming Ding, Bo Liu, Zihuai Lin, Jun Li

In this paper, we incorporate a new type of side information based on consecutive location changes of users and propose a new metric called transition-entropy to investigate the location privacy preservation, followed by two algorithms to improve the transition-entropy for a given dummy generation algorithm.

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