Search Results for author: Scott Alfeld

Found 8 papers, 4 papers with code

A Visual Active Search Framework for Geospatial Exploration

1 code implementation28 Nov 2022 Anindya Sarkar, Michael Lanier, Scott Alfeld, Jiarui Feng, Roman Garnett, Nathan Jacobs, Yevgeniy Vorobeychik

Many problems can be viewed as forms of geospatial search aided by aerial imagery, with examples ranging from detecting poaching activity to human trafficking.

Domain Adaptation

Training-Time Attacks against k-Nearest Neighbors

no code implementations15 Aug 2022 Ara Vartanian, Will Rosenbaum, Scott Alfeld

We distill this goal to the task of performing a training-set data insertion attack against $k$-Nearest Neighbor classification ($k$NN).

Classification Dimensionality Reduction

Approximate Data Deletion in Generative Models

no code implementations29 Jun 2022 Zhifeng Kong, Scott Alfeld

Using this framework, we introduce a fast method for approximate data deletion and a statistical test for estimating whether or not training points have been deleted.

Hard to Forget: Poisoning Attacks on Certified Machine Unlearning

1 code implementation17 Sep 2021 Neil G. Marchant, Benjamin I. P. Rubinstein, Scott Alfeld

The right to erasure requires removal of a user's information from data held by organizations, with rigorous interpretations extending to downstream products such as learned models.

Machine Unlearning

RAWLSNET: Altering Bayesian Networks to Encode Rawlsian Fair Equality of Opportunity

no code implementations16 Mar 2021 David Liu, Zohair Shafi, William Fleisher, Tina Eliassi-Rad, Scott Alfeld

We present RAWLSNET, a system for altering Bayesian Network (BN) models to satisfy the Rawlsian principle of fair equality of opportunity (FEO).

Optimizing Graph Structure for Targeted Diffusion

1 code implementation12 Aug 2020 Sixie Yu, Leonardo Torres, Scott Alfeld, Tina Eliassi-Rad, Yevgeniy Vorobeychik

However, in many applications, such as targeted vulnerability assessment or clinical therapies, one aspires to affect a targeted subset of a network, while limiting the impact on the rest.

Social and Information Networks Physics and Society

Adversarial Regression with Multiple Learners

1 code implementation ICML 2018 Liang Tong, Sixie Yu, Scott Alfeld, Yevgeniy Vorobeychik

We present an algorithm for computing this equilibrium, and show through extensive experiments that equilibrium models are significantly more robust than conventional regularized linear regression.

regression

Contamination Estimation via Convex Relaxations

no code implementations13 Jun 2015 Matthew L. Malloy, Scott Alfeld, Paul Barford

Our approach considers the normal condition of the data to be specified by a model consisting of a set of distributions.

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