16 citations · 32 across the 13 of their papers we have counts for
13 papers
Fine-grained prediction of food insecurity using news streams
Ananth Balashankar, Lakshminarayanan Subramanian, Samuel P. Fraiberger
Anticipating the outbreak of a food crisis is crucial to efficiently allocate emergency relief and reduce human suffering. However, existing food insecurity early warning systems r…
Muzeel: A Dynamic JavaScript Analyzer for Dead Code Elimination in Today's Web
Tofunmi Kupoluyi, Moumena Chaqfeh, Matteo Varvello +3
JavaScript contributes to the increasing complexity of today's web. To support user interactivity and accelerate the development cycle, web developers heavily rely on large general…
The case for model-driven interpretability of delay-based congestion control protocols
Muhammad Khan, Yasir Zaki, Shiva Iyer +5
Analyzing and interpreting the exact behavior of new delay-based congestion control protocols with complex non-linear control loops is exceptionally difficult in highly variable ne…
DICE: Deep Significance Clustering for Outcome-Aware Stratification
Yufang Huang, Kelly M. Axsom, John Lee +2
We present deep significance clustering (DICE), a framework for jointly performing representation learning and clustering for "outcome-aware" stratification. DICE is intended to ge…
Beyond The Text: Analysis of Privacy Statements through Syntactic and Semantic Role Labeling
Yan Shvartzshnaider, Ananth Balashankar, Vikas Patidar +2
This paper formulates a new task of extracting privacy parameters from a privacy policy, through the lens of Contextual Integrity, an established social theory framework for reason…
What is Fair? Exploring Pareto-Efficiency for Fairness Constrained Classifiers
Ananth Balashankar, Alyssa Lees, Chris Welty +1
The potential for learned models to amplify existing societal biases has been broadly recognized. Fairness-aware classifier constraints, which apply equality metrics of performance…
The Case for MUSIC: A Programmable IoT Framework for Mobile Urban Sensing Applications
Shiva R. Iyer, Soumie Kumar, Kate Boxer +2
This vision paper presents the case for MUSIC, a programmable framework for building distributed mobile IoT applications for urban sensing. The Mobile Urban Sensing, Inference and…
Mammography Assessment using Multi-Scale Deep Classifiers
Ulzee An, Khader Shameer, Lakshmi Subramanian
Applying deep learning methods to mammography assessment has remained a challenging topic. Dense noise with sparse expressions, mega-pixel raw data resolution, lack of diverse exam…
The VACCINE Framework for Building DLP Systems
Yan Shvartzshnaider, Zvonimir Pavlinovic, Thomas Wies +3
Conventional Data Leakage Prevention (DLP) systems suffer from the following major drawback: Privacy policies that define what constitutes data leakage cannot be seamlessly defined…
Technical Report: Design, Implementation and Deployment of Intermittency-aware Cellular Edge Services for Rural areas
Talal Ahmad, Alfred Afutu, Kessir Adjaho +2
Rural areas continue to be plagued by limited data connectivity due to poor and unreliable power infrastructure, poor backhaul connectivity and lack of economic incentives for tele…
Secure Mobile Identities
Varun Chandrasekaran, Fareeha Amjad, Ashlesh Sharma +1
The unique identities of every mobile user (phone number,IMSI) and device (IMEI) are far from secure and are increasingly vulnerable to a variety of network-level threats. The exce…
Crowdsourced, Actionable and Verifiable Contextual Informational Norms
Yan Shvartzshnaider, Schrasing Tong, Thomas Wies +4
There is often a fundamental mismatch between programmable privacy frameworks, on the one hand, and the ever shifting privacy expectations of computer system users, on the other ha…
TrackMeNot: Enhancing the privacy of Web Search
Vincent Toubiana, Lakshminarayanan Subramanian, Helen Nissenbaum
Most search engines can potentially infer the preferences and interests of a user based on her history of search queries. While search engines can use these inferences for a variet…