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MIT SafePaths Card (MiSaCa): Augmenting Paper Based Vaccination Cards with Printed Codes
In this early draft, we describe a user-centric, card-based system for v...
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COVID-19 Tests Gone Rogue: Privacy, Efficacy,Mismanagement and Misunderstandings
COVID-19 testing, the cornerstone for effective screening and identifica...
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Spatial K-anonymity: A Privacy-preserving Method for COVID-19 Related Geospatial Technologies
There is a growing need for spatial privacy considerations in the many g...
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COVID-19 Outbreak Prediction and Analysis using Self Reported Symptoms
The COVID-19 pandemic has challenged scientists and policy-makers intern...
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DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for deep neural networks
Recent deep learning models have shown remarkable performance in image c...
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Verifiable Proof of Health using Public Key Cryptography
In the current pandemic, testing continues to be the most important tool...
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Digital Landscape of COVID-19 Testing: Challenges and Opportunities
The COVID-19 Pandemic has left a devastating trail all over the world, i...
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Proximity Inference with Wifi-Colocation during the COVID-19 Pandemic
In this work we propose a WiFi colocation methodology for digital contac...
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Target Privacy Threat Modeling for COVID-19 Exposure Notification Systems
The adoption of digital contact tracing (DCT) technology during the COVI...
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Bluetooth based Proximity, Multi-hop Analysis and Bi-directional Trust: Epidemics and More
In this paper, we propose a trust layer on top of Bluetooth and similar ...
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Proximity Sensing for Contact Tracing
The TC4TL (Too Close For Too Long) challenge is aimed towards designing ...
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NoPeek: Information leakage reduction to share activations in distributed deep learning
For distributed machine learning with sensitive data, we demonstrate how...
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PPContactTracing: A Privacy-Preserving Contact Tracing Protocol for COVID-19 Pandemic
Several contact tracing solutions have been proposed and implemented all...
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Comparing manual contact tracing and digital contact advice
Manual contact tracing is a top-down solution that starts with contact t...
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SplitNN-driven Vertical Partitioning
In this work, we introduce SplitNN-driven Vertical Partitioning, a confi...
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Splintering with distributions: A stochastic decoy scheme for private computation
Performing computations while maintaining privacy is an important proble...
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Adding Location and Global Context to the Google/Apple Exposure Notification Bluetooth API
Contact tracing requires a strong understanding of the context of a user...
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Adding Location and other Context to the Google/Apple Exposure Notification Bluetooth API
Contact tracing requires a strong understanding of the context of a user...
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COVID-19 Contact-Tracing Mobile Apps: Evaluation and Assessment for Decision Makers
A number of groups, from governments to non-profits, have quickly acted ...
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Automatic Differentiation for All Photons Imaging to See Inside Volumetric Scattering Media
Imaging through dense scattering media - such as biological tissue, fog,...
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Privacy Guidelines for Contact Tracing Applications
Contact tracing is a very powerful method to implement and enforce socia...
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Privacy in Deep Learning: A Survey
The ever-growing advances of deep learning in many areas including visio...
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Assessing Disease Exposure Risk With Location Histories And Protecting Privacy: A Cryptographic Approach In Response To A Global Pandemic
Governments and researchers around the world are implementing digital co...
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Apps Gone Rogue: Maintaining Personal Privacy in an Epidemic
Containment, the key strategy in quickly halting an epidemic, requires r...
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Split Learning for collaborative deep learning in healthcare
Shortage of labeled data has been holding the surge of deep learning in ...
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Advances and Open Problems in Federated Learning
Federated learning (FL) is a machine learning setting where many clients...
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Recent Advances in Imaging Around Corners
Seeing around corners, also known as non-line-of-sight (NLOS) imaging is...
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ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations
Recently, there has been the development of Split Learning, a framework ...
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ExpertMatcher: Automating ML Model Selection for Users in Resource Constrained Countries
In this work we introduce ExpertMatcher, a method for automating deep le...
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Maximal adversarial perturbations for obfuscation: Hiding certain attributes while preserving rest
In this paper we investigate the usage of adversarial perturbations for ...
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Detailed comparison of communication efficiency of split learning and federated learning
We compare communication efficiencies of two compelling distributed mach...
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Data Markets to support AI for All: Pricing, Valuation and Governance
We discuss a data market technique based on intrinsic (relevance and uni...
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On Unlimited Sampling and Reconstruction
Shannon's sampling theorem is one of the cornerstone topics that is well...
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Light-Field for RF
Most computer vision systems and computational photography systems are v...
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No Peek: A Survey of private distributed deep learning
We survey distributed deep learning models for training or inference wit...
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A Review of Homomorphic Encryption Libraries for Secure Computation
In this paper we provide a survey of various libraries for homomorphic e...
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Split learning for health: Distributed deep learning without sharing raw patient data
Can health entities collaboratively train deep learning models without s...
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Addressing the Invisible: Street Address Generation for Developing Countries with Deep Learning
More than half of the world's roads lack adequate street addressing syst...
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3D Traffic Simulation for Autonomous Vehicles in Unity and Python
Over the recent years, there has been an explosion of studies on autonom...
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Flash Photography for Data-Driven Hidden Scene Recovery
Vehicles, search and rescue personnel, and endoscopes use flash lights t...
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Distributed learning of deep neural network over multiple agents
In domains such as health care and finance, shortage of labeled data and...
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Maximum-Entropy Fine-Grained Classification
Fine-Grained Visual Classification (FGVC) is an important computer visio...
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DeepGlobe 2018: A Challenge to Parse the Earth through Satellite Images
We present the DeepGlobe 2018 Satellite Image Understanding Challenge, w...
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Economic Impact of Discoverability of Localities and Addresses in India
Most of the earth's population has a poorly defined addressing system, t...
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What is the right addressing scheme for India?
Computer generated addresses are coming to your neighborhood because mos...
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Accelerating Neural Architecture Search using Performance Prediction
Methods for neural network hyperparameter optimization and meta-modeling...
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Training with Confusion for Fine-Grained Visual Classification
Research in Fine-Grained Visual Classification has focused on tackling t...
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Sampling Without Time: Recovering Echoes of Light via Temporal Phase Retrieval
This paper considers the problem of sampling and reconstruction of a con...
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Lensless Imaging with Compressive Ultrafast Sensing
Lensless imaging is an important and challenging problem. One notable so...
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Deep Learning the City : Quantifying Urban Perception At A Global Scale
Computer vision methods that quantify the perception of urban environmen...
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