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08/15/2023
A Floating-Point Secure Implementation of the Report Noisy Max with Gap Mechanism
The Noisy Max mechanism and its variations are fundamental private selec...
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05/14/2023
An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions
Noisy marginals are a common form of confidentiality-protecting data rel...
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01/10/2023
Differentiable modeling to unify machine learning and physical models and advance Geosciences
Process-Based Modeling (PBM) and Machine Learning (ML) are often perceiv...
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11/30/2022
Answering Private Linear Queries Adaptively using the Common Mechanism
When analyzing confidential data through a privacy filter, a data scient...
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11/12/2022
ThreshNet: Segmentation Refinement Inspired by Region-Specific Thresholding
We present ThreshNet, a post-processing method to refine the output of n...
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09/08/2022
Reconstruction Attacks on Aggressive Relaxations of Differential Privacy
Differential privacy is a widely accepted formal privacy definition that...
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09/07/2022
Bayesian and Frequentist Semantics for Common Variations of Differential Privacy: Applications to the 2020 Census
The purpose of this paper is to guide interpretation of the semantic pri...
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04/19/2022
The 2020 Census Disclosure Avoidance System TopDown Algorithm
The Census TopDown Algorithm (TDA) is a disclosure avoidance system usin...
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03/30/2022
Geographic Spines in the 2020 Census Disclosure Avoidance System TopDown Algorithm
The TopDown Algorithm (TDA) first produces differentially private counts...
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02/02/2022
Exact Privacy Analysis of the Gaussian Sparse Histogram Mechanism
Sparse histogram methods can be useful for returning differentially priv...
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01/27/2022
Neural JPEG: End-to-End Image Compression Leveraging a Standard JPEG Encoder-Decoder
Recent advances in deep learning have led to superhuman performance acro...
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01/27/2022
An Empirical Analysis of Recurrent Learning Algorithms In Neural Lossy Image Compression Systems
Recent advances in deep learning have resulted in image compression algo...
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10/25/2021
An Uncertainty Principle is a Price of Privacy-Preserving Microdata
Privacy-protected microdata are often the desired output of a differenti...
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09/15/2021
DPGen: Automated Program Synthesis for Differential Privacy
Differential privacy has become a de facto standard for releasing data i...
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05/15/2021
The Permute-and-Flip Mechanism is Identical to Report-Noisy-Max with Exponential Noise
The permute-and-flip mechanism is a recently proposed differentially pri...
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04/19/2021
OmniLayout: Room Layout Reconstruction from Indoor Spherical Panoramas
Given a single RGB panorama, the goal of 3D layout reconstruction is to ...
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04/07/2021
Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units
Automated mathematical reasoning is a challenging problem that requires ...
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01/06/2021
The data synergy effects of time-series deep learning models in hydrology
When fitting statistical models to variables in geoscientific discipline...
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12/07/2020
The Neural Coding Framework for Learning Generative Models
Neural generative models can be used to learn complex probability distri...
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12/02/2020
Free Gap Estimates from the Exponential Mechanism, Sparse Vector, Noisy Max and Related Algorithms
Private selection algorithms, such as the Exponential Mechanism, Noisy M...
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11/30/2020
Optimizing Fitness-For-Use of Differentially Private Linear Queries
In practice, differentially private data releases are designed to suppor...
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10/08/2020
Differentially Private Deep Learning with Direct Feedback Alignment
Standard methods for differentially private training of deep neural netw...
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09/07/2020
Scaling up Differentially Private Deep Learning with Fast Per-Example Gradient Clipping
Recent work on Renyi Differential Privacy has shown the feasibility of a...
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08/17/2020
CheckDP: An Automated and Integrated Approach for Proving Differential Privacy or Finding Precise Counterexamples
We propose CheckDP, the first automated and integrated approach for prov...
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02/10/2020
Guidelines for Implementing and Auditing Differentially Private Systems
Differential privacy is an information theoretic constraint on algorithm...
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02/10/2020
Reducing the Computational Burden of Deep Learning with Recursive Local Representation Alignment
Training deep neural networks on large-scale datasets requires significa...
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06/10/2019
Evaluating aleatoric and epistemic uncertainties of time series deep learning models for soil moisture predictions
Soil moisture is an important variable that determines floods, vegetatio...
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05/25/2019
Lifelong Neural Predictive Coding: Sparsity Yields Less Forgetting when Learning Cumulatively
In lifelong learning systems, especially those based on artificial neura...
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04/29/2019
Free Gap Information from the Differentially Private Sparse Vector and Noisy Max Mechanisms
Noisy Max and Sparse Vector are selection algorithms for differential pr...
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03/28/2019
Proving Differential Privacy with Shadow Execution
Recent work on formal verification of differential privacy shows a trend...
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10/17/2018
Online Learning of Recurrent Neural Architectures by Locally Aligning Distributed Representations
Temporal models based on recurrent neural networks have proven to be qui...
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10/17/2018
Continual Learning of Recurrent Neural Networks by Locally Aligning Distributed Representations
Temporal models based on recurrent neural networks have proven to be qui...
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10/10/2018
ET-Lasso: Efficient Tuning of Lasso for High-Dimensional Data
The L1 regularization (Lasso) has proven to be a versatile tool to selec...
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09/09/2018
TextContourNet: a Flexible and Effective Framework for Improving Scene Text Detection Architecture with a Multi-task Cascade
We study the problem of extracting text instance contour information fro...
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08/28/2018
Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget
Iterative algorithms, like gradient descent, are common tools for solvin...
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08/26/2018
Detecting Outliers in Data with Correlated Measures
Advances in sensor technology have enabled the collection of large-scale...
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05/25/2018
Toward Detecting Violations of Differential Privacy
The widespread acceptance of differential privacy has led to the publica...
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04/23/2018
Guided Attention for Large Scale Scene Text Verification
Many tasks are related to determining if a particular text string exists...
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04/11/2018
Differentially Private Confidence Intervals for Empirical Risk Minimization
The process of data mining with differential privacy produces results th...
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04/02/2018
Differentially Private Hierarchical Count-of-Counts Histograms
We consider the problem of privately releasing a class of queries that w...
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04/02/2018
Differentially Private Hierarchical Group Size Estimation
Consider the problem of estimating, for every integer j, the number of h...
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03/05/2018
Conducting Credit Assignment by Aligning Local Representations
The use of back-propagation and its variants to train deep networks is o...
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07/20/2017
Prolongation of SMAP to Spatio-temporally Seamless Coverage of Continental US Using a Deep Learning Neural Network
The Soil Moisture Active Passive (SMAP) mission has delivered valuable s...
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06/07/2017
Learning to Extract Semantic Structure from Documents Using Multimodal Fully Convolutional Neural Network
We present an end-to-end, multimodal, fully convolutional network for ex...
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01/22/2017
Predicting Demographics of High-Resolution Geographies with Geotagged Tweets
In this paper, we consider the problem of predicting demographics of geo...
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01/26/2016
