
Optimal Stochastic Evasive Maneuvers Using the Schrodinger's Equation
In this paper, preys with stochastic evasion policies are considered. Th...
read it

ZeroError Feedback Capacity of FiniteState Additive Noise Channels for Stabilization of Linear Systems
It is known that for a discrete channel with correlated additive noise, ...
read it

Sharing in a Trustless World: PrivacyPreserving Data Analytics with Potentially Cheating Participants
Lack of trust between organisations and privacy concerns about their dat...
read it

Safe Learning of Uncertain Environments for Nonlinear ControlAffine Systems
In many learning based control methodologies, learning the unknown dynam...
read it

A Linear Reduction Method for Local Differential Privacy and Loglift
This paper considers the problem of publishing data X while protecting c...
read it

Optimal PreProcessing to Achieve Fairness and Its Relationship with Total Variation Barycenter
We use disparate impact, i.e., the extent that the probability of observ...
read it

Gradient Sparsification Can Improve Performance of DifferentiallyPrivate Convex Machine Learning
We use gradient sparsification to reduce the adverse effect of different...
read it

When Machine Learning Meets Privacy: A Survey and Outlook
The newly emerged machine learning (e.g. deep learning) methods have bec...
read it

NonStochastic Private Function Evaluation
We consider private function evaluation to provide query responses based...
read it

Deconvoluting Kernel Density Estimation and Regression for Locally Differentially Private Data
Local differential privacy has become the goldstandard of privacy liter...
read it

Security Versus Privacy
Linear queries can be submitted to a server containing private data. The...
read it

DistributionallyRobust Machine Learning Using Locally DifferentiallyPrivate Data
We consider machine learning, particularly regression, using locallydif...
read it

Online Stochastic Convex Optimization: Wasserstein Distance Variation
Distributionallyrobust optimization is often studied for a fixed set of...
read it

An Explicit Formula for the ZeroError Feedback Capacity of a Class of FiniteState Additive Noise Channels
It is known that for a discrete channel with correlated additive noise, ...
read it

Measuring Information Leakage in Nonstochastic BruteForce Guessing
We propose an operational measure of information leakage in a nonstocha...
read it

Bounded state Estimation over FiniteState Channels: Relating Topological Entropy and ZeroError Capacity
We investigate bounded state estimation of linear systems over finitest...
read it

Predicting Performance of Asynchronous DifferentiallyPrivate Learning
We consider training machine learning models using Training data located...
read it

Data and Model Dependencies of Membership Inference Attack
Machine Learning (ML) techniques are used by most datadriven organisati...
read it

Regularization Helps with Mitigating Poisoning Attacks: DistributionallyRobust Machine Learning Using the Wasserstein Distance
We use distributionallyrobust optimization for machine learning to miti...
read it

Modelling and Quantifying Membership Information Leakage in Machine Learning
Machine learning models have been shown to be vulnerable to membership i...
read it

PrivacyPreserving Public Release of Datasets for Support Vector Machine Classification
We consider the problem of publicly releasing a dataset for support vect...
read it

Developing NonStochastic PrivacyPreserving Policies Using Agglomerative Clustering
We consider a nonstochastic privacypreserving problem in which an adve...
read it

Noiseless Privacy
In this paper, we define noiseless privacy, as a nonstochastic rival to...
read it

A Fundamental Bound on Performance of NonIntrusive Load Monitoring with Application to Smart Meter Privacy
We prove that the expected estimation error of nonintrusive load monito...
read it

Differential Privacy for Evolving AlmostPeriodic Datasets with Continual Linear Queries: Application to Energy Data Privacy
For evolving datasets with continual reports, the composition rule for d...
read it

Taking a Lesson from Quantum Particles for Statistical Data Privacy
Privacy is under threat from artificial intelligence revolution fueled b...
read it

Discounted Differential Privacy: Privacy of Evolving Datasets over an Infinite Horizon
In this paper, we define discounted differential privacy, as an alternat...
read it

A GameTheoretic Approach to Adversarial Linear Support Vector Classification
In this paper, we employ a gametheoretic model to analyze the interacti...
read it

The Value of Collaboration in Convex Machine Learning with Differential Privacy
In this paper, we apply machine learning to distributed private data own...
read it

NonStochastic Hypothesis Testing with Application to Privacy Against HypothesisTesting Adversary
In this paper, we consider privacy against hypothesis testing adversarie...
read it

Implementing Homomorphic Encryption Based Secure Feedback Control for Physical Systems
This paper is about an encryption based approach to the secure implement...
read it

State Estimation over WorstCase Erasure and Symmetric Channels with Memory
Worstcase models of erasure and symmetric channels are investigated, in...
read it

Secure and Private Implementation of Dynamic Controllers Using SemiHomomorphic Encryption
This paper presents a secure and private implementation of linear timei...
read it

Development and Analysis of Deterministic PrivacyPreserving Policies Using NonStochastic Information Theory
A nonstochastic privacy metric using nonstochastic information theory ...
read it

Ensuring Privacy with Constrained Additive Noise by Minimizing Fisher Information
The problem of preserving the privacy of individual entries of a databas...
read it
Farhad Farokhi
is this you? claim profile