Seth Neel

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All published works
Action Title Year Authors
+ PDF Chat Attribute-to-Delete: Machine Unlearning via Datamodel Matching 2024 Kristian Georgiev
Roy Rinberg
Sung Min Park
Shivam Garg
Andrew Ilyas
Aleksander Mądry
Seth Neel
+ PDF Chat Machine Unlearning Fails to Remove Data Poisoning Attacks 2024 Martin Pawelczyk
Jimmy Z. Di
Yiwei Lu
Gautam Kamath
Ayush Sekhari
Seth Neel
+ Model Explanation Disparities as a Fairness Diagnostic 2023 Peter Wushou Chang
Leor Fishman
Seth Neel
+ PRIMO: Private Regression in Multiple Outcomes 2023 Seth Neel
+ The Potential of Quantum Techniques for Stock Price Prediction 2023 Subh Naman
Gaurang Bansal
Seth Neel
Aswath Babu H
+ In-Context Unlearning: Language Models as Few Shot Unlearners 2023 Martin Pawelczyk
Seth Neel
Himabindu Lakkaraju
+ Black-Box Training Data Identification in GANs via Detector Networks 2023 Lukman Olagoke
Salil Vadhan
Seth Neel
+ MoPe: Model Perturbation-based Privacy Attacks on Language Models 2023 Marvin Li
Jason Wang
Jeffrey Wang
Seth Neel
+ PDF Chat MoPe: Model Perturbation based Privacy Attacks on Language Models 2023 Marvin Li
Jason Wang
Jeffrey Wang
Seth Neel
+ Privacy Issues in Large Language Models: A Survey 2023 Seth Neel
Peter H. Chang
+ On the Privacy Risks of Algorithmic Recourse 2022 Martin Pawelczyk
Himabindu Lakkaraju
Seth Neel
+ Adaptive Machine Unlearning 2021 Varun Gupta
Christopher Jung
Seth Neel
Aaron Roth
Saeed Sharifi-Malvajerdi
Chris Waites
+ Optimal, truthful, and private securities lending 2020 Emily Diana
Michael Kearns
Seth Neel
Aaron Roth
+ Descent-to-Delete: Gradient-Based Methods for Machine Unlearning 2020 Seth Neel
Aaron Roth
Saeed Sharifi-Malvajerdi
+ Optimal, Truthful, and Private Securities Lending 2019 Emily Diana
Michael Kearns
Seth Neel
Aaron Roth
+ PDF Chat How to Use Heuristics for Differential Privacy 2019 Seth Neel
Aaron Roth
Zhiwei Steven Wu
+ PDF Chat The Role of Interactivity in Local Differential Privacy 2019 Matthew Joseph
Jieming Mao
Seth Neel
Aaron Roth
+ PDF Chat Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM 2019 Steven Y. Wu
Aaron Roth
Katrina Ligett
Bo Waggoner
Seth Neel
+ A New Analysis of Differential Privacy's Generalization Guarantees 2019 Christopher Jung
Katrina Ligett
Seth Neel
Aaron Roth
Saeed Sharifi-Malvajerdi
Moshe Shenfeld
+ Differentially Private Objective Perturbation: Beyond Smoothness and Convexity 2019 Seth Neel
Aaron Roth
Giuseppe Vietri
Zhiwei Steven Wu
+ Eliciting and Enforcing Subjective Individual Fairness. 2019 Christopher Jung
Michael Kearns
Seth Neel
Aaron Roth
Logan Stapleton
Zhiwei Steven Wu
+ The Role of Interactivity in Local Differential Privacy 2019 Matthew Joseph
Jieming Mao
Seth Neel
Aaron Roth
+ PDF Chat Fair Algorithms for Learning in Allocation Problems 2019 Hadi Elzayn
Shahin Jabbari
Christopher Jung
Michael Kearns
Seth Neel
Aaron Roth
Zachary Schutzman
+ An Empirical Study of Rich Subgroup Fairness for Machine Learning 2019 Michael Kearns
Seth Neel
Aaron Roth
Zhiwei Steven Wu
+ A New Analysis of Differential Privacy's Generalization Guarantees 2019 Christopher Jung
Katrina Ligett
Seth Neel
Aaron Roth
Saeed Sharifi-Malvajerdi
Moshe Shenfeld
+ Oracle Efficient Private Non-Convex Optimization 2019 Seth Neel
Aaron Roth
Giuseppe Vietri
Zhiwei Steven Wu
+ An Algorithmic Framework for Fairness Elicitation 2019 Christopher Jung
Michael Kearns
Seth Neel
Aaron Roth
Logan Stapleton
Zhiwei Steven Wu
+ PDF Chat Optimal, Truthful, and Private Securities Lending 2019 Emily Diana
Michael Kearns
Seth Neel
Aaron Roth
+ Optimal, Truthful, and Private Securities Lending 2019 Emily Diana
Michael Kearns
Seth Neel
Aaron Roth
+ The Role of Interactivity in Local Differential Privacy 2019 Matthew Joseph
Jieming Mao
Seth Neel
Aaron Roth
+ How to Use Heuristics for Differential Privacy 2018 Seth Neel
Aaron Roth
Zhiwei Steven Wu
+ Fair Algorithms for Learning in Allocation Problems 2018 Hadi Elzayn
Shahin Jabbari
Christopher Jung
Michael Kearns
Seth Neel
Aaron Roth
Zachary Schutzman
+ Mitigating Bias in Adaptive Data Gathering via Differential Privacy 2018 Seth Neel
Aaron Roth
+ How to Use Heuristics for Differential Privacy 2018 Seth Neel
Aaron Roth
Zhiwei Steven Wu
+ Fair Algorithms for Learning in Allocation Problems 2018 Hadi Elzayn
Shahin Jabbari
Christopher Jung
Michael Kearns
Seth Neel
Aaron Roth
Zachary Schutzman
+ An Empirical Study of Rich Subgroup Fairness for Machine Learning 2018 Michael Kearns
Seth Neel
Aaron Roth
Zhiwei Steven Wu
+ Mitigating Bias in Adaptive Data Gathering via Differential Privacy 2018 Seth Neel
Aaron Roth
+ Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM 2017 Katrina Ligett
Seth Neel
Aaron Roth
Bo Waggoner
Zhiwei Steven Wu
+ Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM 2017 Katrina Ligett
Seth Neel
Aaron Roth
Bo Waggoner
Zhiwei Steven Wu
+ A Convex Framework for Fair Regression 2017 Richard A. Berk
Hoda Heidari
Shahin Jabbari
Matthew Joseph
Michael Kearns
Jamie Morgenstern
Seth Neel
Aaron Roth
+ Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness 2017 Michael Kearns
Seth Neel
Aaron Roth
Zhiwei Steven Wu
+ Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM 2017 Katrina Ligett
Seth Neel
Aaron Roth
Bo Waggoner
Z. Steven Wu
+ Rawlsian Fairness for Machine Learning. 2016 Matthew Joseph
Michael Kearns
Jamie Morgenstern
Seth Neel
Aaron Roth
+ Fair Algorithms for Infinite and Contextual Bandits 2016 Matthew Joseph
Michael Kearns
Jamie Morgenstern
Seth Neel
Aaron Roth
+ Fair Algorithms for Infinite and Contextual Bandits 2016 Matthew Joseph
Michael Kearns
Jamie Morgenstern
Seth Neel
Aaron Roth
+ PDF Chat Aztec castles and the dP3 quiver 2014 Megan Leoni
Gregg Musiker
Seth Neel
Paxton Turner
+ Aztec Castles and the dP3 Quiver 2013 Megan Leoni
Gregg Musiker
Seth Neel
Paxton Turner
+ Aztec Castles and the dP3 Quiver 2013 Megan Leoni
Gregg Musiker
Seth Neel
Paxton Turner
Common Coauthors
Commonly Cited References
Action Title Year Authors # of times referenced
+ PDF Chat Fairness through awareness 2012 Cynthia Dwork
Moritz Hardt
Toniann Pitassi
Omer Reingold
Richard S. Zemel
8
+ Adaptive Learning with Robust Generalization Guarantees 2016 Rachel Cummings
Katrina Ligett
Kobbi Nissim
Aaron Roth
Zhiwei Steven Wu
6
+ Fairness in Learning: Classic and Contextual Bandits 2016 Matthew Joseph
Michael Kearns
Jamie Morgenstern
Aaron Roth
5
+ What Can We Learn Privately? 2011 Shiva Prasad Kasiviswanathan
Homin K. Lee
Kobbi Nissim
Sofya Raskhodnikova
Adam Smith
5
+ PDF Chat Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment 2017 Muhammad Bilal Zafar
Isabel Valera
Manuel Gomez-Rodriguez
Krishna P. Gummadi
5
+ Learning Non-Discriminatory Predictors 2017 Blake Woodworth
Suriya Gunasekar
Mesrob I. Ohannessian
Nathan Srebro
4
+ Local Privacy and Statistical Minimax Rates 2013 John C. Duchi
Michael I. Jordan
Martin J. Wainwright
4
+ Differentially Private Empirical Risk Minimization. 2011 Kamalika Chaudhuri
Claire Monteleoni
Anand D. Sarwate
4
+ PDF Chat Preserving Statistical Validity in Adaptive Data Analysis 2015 Cynthia Dwork
Vitaly Feldman
Moritz Hardt
Toniann Pitassi
Omer Reingold
Aaron Roth
4
+ Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments 2017 Alexandra Chouldechova
4
+ PDF Chat How to Use Heuristics for Differential Privacy 2019 Seth Neel
Aaron Roth
Zhiwei Steven Wu
4
+ PDF Chat Fairness in Criminal Justice Risk Assessments: The State of the Art 2018 Richard A. Berk
Hoda Heidari
Shahin Jabbari
Michael Kearns
Aaron Roth
3
+ PDF Chat Agnostic Learning of Monomials by Halfspaces Is Hard 2012 Vitaly Feldman
Venkatesan Guruswami
Prasad Raghavendra
Yi Wu
3
+ PDF Chat A learning theory approach to noninteractive database privacy 2013 Avrim Blum
Katrina Ligett
Aaron Roth
3
+ PDF Chat Membership Inference Attacks Against Machine Learning Models 2017 Reza Shokri
Marco Stronati
Congzheng Song
Vitaly Shmatikov
3
+ PDF Chat Algorithmic Decision Making and the Cost of Fairness 2017 Sam Corbett‐Davies
Emma Pierson
Avi Feller
Sharad Goel
Aziz Z. Huq
3
+ On general minimax theorems 1958 Maurice Sion
3
+ Equality of Opportunity in Supervised Learning 2016 Moritz Hardt
Eric Price
Nathan Srebro
3
+ The reusable holdout: Preserving validity in adaptive data analysis 2015 Cynthia Dwork
Vitaly Feldman
Moritz Hardt
Toniann Pitassi
Omer Reingold
Aaron Roth
3
+ Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness 2017 Michael Kearns
Seth Neel
Aaron Roth
Zhiwei Steven Wu
3
+ PDF Chat Dual Query: Practical Private Query Release for High Dimensional Data 2017 Marco Gaboardi
Emilio JesĂșs Gallego Arias
Justin Hsu
Aaron Roth
Zhiwei Steven Wu
2
+ PDF Chat Private matchings and allocations 2014 Justin Hsu
Zhiyi Huang
Aaron Roth
Tim Roughgarden
Zhiwei Steven Wu
2
+ PDF Chat Wall Crossing of BPS States on the Conifold from Seiberg Duality and Pyramid Partitions 2009 Wu-yen Chuang
Daniel L. Jafferis
2
+ PDF Chat Privately Releasing Conjunctions and the Statistical Query Barrier 2013 Anupam Gupta
Moritz Hardt
Aaron Roth
Jonathan Ullman
2
+ The computational power of optimization in online learning 2016 Elad Hazan
Tomer Koren
2
+ PDF Chat Perfect matchings and the octahedron recurrence 2006 David E Speyer
2
+ Cluster algebras I: Foundations 2001 Sergey Fomin
Andrei Zelevinsky
2
+ PDF Chat Cluster expansion formulas and perfect matchings 2009 Gregg Musiker
Ralf Schiffler
2
+ A Convex Framework for Fair Regression 2017 Richard A. Berk
Hoda Heidari
Shahin Jabbari
Matthew Joseph
Michael Kearns
Jamie Morgenstern
Seth Neel
Aaron Roth
2
+ Domino shuffling for the Del Pezzo 3 lattice 2010 Cyndie Cottrell
Benjamin Young
2
+ Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias 1965 Stanley L. Warner
2
+ Cluster Variables and Perfect Matchings of Subgraphs of the $dP_3$ Lattice 2015 Sicong Zhang
2
+ PDF Chat Inherent Tradeoffs in the Fair Determination of Risk Scores 2023 Manish Raghavan
2
+ PDF Chat Adaptive estimation of a quadratic functional by model selection 2000 BĂ©atrice Laurent
Pascal Massart
2
+ Algorithmic stability for adaptive data analysis 2016 Raef Bassily
Kobbi Nissim
Adam Smith
Thomas Steinke
Uri Stemmer
Jonathan Ullman
2
+ Controlling Bias in Adaptive Data Analysis Using Information Theory 2016 Daniel Russo
James Zou
2
+ On the (im)possibility of fairness 2016 Sorelle A. Friedler
Carlos Scheidegger
Suresh Venkatasubramanian
2
+ Proof of Blum's conjecture on hexagonal dungeons 2014 Mihai Ciucu
Tri Lai
2
+ PDF Chat A contextual-bandit approach to personalized news article recommendation 2010 Lihong Li
Wei Chu
John Langford
Robert E. Schapire
2
+ PDF Chat The Tropical Totally Positive Grassmannian 2005 David E Speyer
Lauren Williams
2
+ PDF Chat Cluster algebras, quiver representations and triangulated categories 2010 Bernhard Keller
2
+ PDF Chat Faster private release of marginals on small databases 2014 Karthekeyan Chandrasekaran
Justin Thaler
Jonathan Ullman
Andrew Wan
2
+ PDF Chat Differential privacy for the analyst via private equilibrium computation 2013 Justin Hsu
Aaron Roth
Jonathan Ullman
2
+ An introduction to the dimer model 2003 Richard Kenyon
2
+ PDF Chat Oracle-Based Robust Optimization via Online Learning 2015 Aharon Ben‐Tal
Elad Hazan
Tomer Koren
Shie Mannor
2
+ PDF Chat Toric duality as Seiberg duality and brane diamonds 2001 Bo Feng
Amihay Hanany
Yang‐Hui He
Ángel M. Uranga
2
+ PDF Chat Applications of graphical condensation for enumerating matchings and tilings 2004 Eric Kuo
2
+ PDF Chat Concentration of Lipschitz Functionals of Determinantal and Other Strong Rayleigh Measures 2013 Robin Pemantle
Yuval Peres
2
+ PDF Chat A Graph Theoretic Expansion Formula for Cluster Algebras of Classical Type 2011 Gregg Musiker
2
+ PDF Chat Preventing False Discovery in Interactive Data Analysis Is Hard 2014 Moritz Hardt
Jonathan Ullman
2