John P. Dickerson

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 179

Top Venues

Publications

Juan Luque, Sharmila Duppala, John P. Dickerson, Aravind Srinivasan
Barter Exchange with Shared Item Valuations. WWW (2024)
Angelina Wang, Teresa Datta, John P. Dickerson
Strategies for Increasing Corporate Responsible AI Prioritization. CoRR (2024)
John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu, Yifan Xu
Matching Tasks and Workers under Known Arrival Distributions: Online Task Assignment with Two-sided Arrivals. ACM Trans. Economics and Comput. 12 (2) (2024)
Angelina Wang, Jamie Morgenstern, John P. Dickerson
Large language models cannot replace human participants because they cannot portray identity groups. CoRR (2024)
John P. Dickerson, Seyed A. Esmaeili, Jamie H. Morgenstern, Claire Jie Zhang
Doubly Constrained Fair Clustering. NeurIPS (2023)
Sahil Verma, Gantavya Bhatt, Avi Schwarzschild, Soumye Singhal, Arnav Mohanty Das, Chirag Shah, John P. Dickerson, Jeff A. Bilmes
Effective Backdoor Mitigation Depends on the Pre-training Objective. CoRR (2023)
Vedant Nanda, Ayan Majumdar, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Bradley C. Love, Adrian Weller
Do Invariances in Deep Neural Networks Align with Human Perception? AAAI (2023)
Sahil Verma, Ashudeep Singh, Varich Boonsanong, John P. Dickerson, Chirag Shah
RecRec: Algorithmic Recourse for Recommender Systems. CoRR (2023)
Christine Herlihy, John P. Dickerson
Networked Restless Bandits with Positive Externalities. AAAI (2023)
Michael J. Curry, Tuomas Sandholm, John P. Dickerson
Differentiable Economics for Randomized Affine Maximizer Auctions. IJCAI (2023)
Ryan Sullivan, Akarsh Kumar, Shengyi Huang, John P. Dickerson, Joseph Suarez
Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks. CoRR (2023)
John P. Dickerson, Bistra Dilkina, Yu Ding, Swati Gupta, Pascal Van Hentenryck, Sven Koenig, Ramayya Krishnan, Radhika Kulkarni, Catherine Gill, Haley Griffin, Maddy Hunter, Ann Schwartz
Artificial Intelligence/Operations Research Workshop 2 Report Out. CoRR (2023)
Teresa Datta, John P. Dickerson
Who's Thinking? A Push for Human-Centered Evaluation of LLMs using the XAI Playbook. CoRR (2023)
Alex Stein, Avi Schwarzschild, Michael J. Curry, Tom Goldstein, John P. Dickerson
Neural Auctions Compromise Bidder Information. CoRR (2023)
Duncan C. McElfresh, Christian Kroer, Sergey Pupyrev, Eric Sodomka, Karthik Abinav Sankararaman, Zack Chauvin, Neil Dexter, John P. Dickerson
Matching algorithms for blood donation. Nat. Mac. Intell. 5 (10) (2023)
John P. Dickerson, Seyed A. Esmaeili, Jamie Morgenstern, Claire Jie Zhang
Doubly Constrained Fair Clustering. CoRR (2023)
Sharmila Duppala, Juan Luque, John P. Dickerson, Aravind Srinivasan
Group Fairness in Set Packing Problems. IJCAI (2023)
Marina Knittel, Max Springer, John P. Dickerson, MohammadTaghi Hajiaghayi
Fair, Polylog-Approximate Low-Cost Hierarchical Clustering. NeurIPS (2023)
Marina Knittel, Max Springer, John P. Dickerson, MohammadTaghi Hajiaghayi
Fair Polylog-Approximate Low-Cost Hierarchical Clustering. CoRR (2023)
Avi Schwarzschild, Max Cembalest, Karthik Rao, Keegan Hines, John P. Dickerson
Reckoning with the Disagreement Problem: Explanation Consensus as a Training Objective. CoRR (2023)
Hannah K. Bako, Alisha Varma, Anuoluwapo Faboro, Mahreen Haider, Favour Nerrise, Bissaka Kenah, John P. Dickerson, Leilani Battle
User-Driven Support for Visualization Prototyping in D3. IUI (2023)
Vedant Nanda, Till Speicher, John P. Dickerson, Soheil Feizi, Krishna P. Gummadi, Adrian Weller
Diffused Redundancy in Pre-trained Representations. CoRR (2023)
Ryan Sullivan, Akarsh Kumar, Shengyi Huang, John P. Dickerson, Joseph Suarez
Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks. NeurIPS (2023)
Christine Herlihy, Aviva Prins, Aravind Srinivasan, John P. Dickerson
Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting. KDD (2023)
Avi Schwarzschild, Max Cembalest, Karthik Rao, Keegan Hines, John P. Dickerson
Reckoning with the Disagreement Problem: Explanation Consensus as a Training Objective. AIES (2023)
Marina Knittel, Max Springer, John P. Dickerson, MohammadTaghi Hajiaghayi
Generalized Reductions: Making any Hierarchical Clustering Fair and Balanced with Low Cost. ICML (2023)
Valeriia Cherepanova, Steven Reich, Samuel Dooley, Hossein Souri, John P. Dickerson, Micah Goldblum, Tom Goldstein
A Deep Dive into Dataset Imbalance and Bias in Face Identification. AIES (2023)
Seyed A. Esmaeili, Sharmila Duppala, Davidson Cheng, Vedant Nanda, Aravind Srinivasan, John P. Dickerson
Rawlsian Fairness in Online Bipartite Matching: Two-Sided, Group, and Individual. AAAI (2023)
Sanmay Das, Nicholas Mattei, John P. Dickerson, Sven Koenig, Louise A. Dennis, Larry R. Medsker, Ziyu Yao, Anuj Karpatne, Alan Tsang, Matt Luckcuck
SIGAI Annual Report: July 1 2022 - August 30 2023. AI Matters 9 (3) (2023)
Vedant Nanda, Till Speicher, John P. Dickerson, Krishna P. Gummadi, Soheil Feizi, Adrian Weller
Diffused Redundancy in Pre-trained Representations. NeurIPS (2023)
Samuel Dooley, Rhea Sukthanker, John P. Dickerson, Colin White, Frank Hutter, Micah Goldblum
Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition. NeurIPS (2023)
Sahil Verma, Ashudeep Singh, Varich Boonsanong, John P. Dickerson, Chirag Shah
RecRec: Algorithmic Recourse for Recommender Systems. CIKM (2023)
Sanmay Das, Nicholas Mattei, John P. Dickerson, Sven Koenig, Louise A. Dennis, Larry R. Medsker, Ziyu Yao, Anuj Karpatne, Alan Tsang, Matt Luckcuck
SIGAI Annual Report: July 1 2021 - June 30 2022. AI Matters 8 (3) (2022)
Stephanie Allen, Steven A. Gabriel, John P. Dickerson
Using inverse optimization to learn cost functions in generalized Nash games. Comput. Oper. Res. 142 (2022)
Marina Knittel, Samuel Dooley, John P. Dickerson
The Dichotomous Affiliate Stable Matching Problem: Approval-Based Matching with Applicant-Employer Relations. IJCAI (2022)
Samuel Dooley, George Z. Wei, Tom Goldstein, John P. Dickerson
Are Commercial Face Detection Models as Biased as Academic Models? CoRR (2022)
Seyed A. Esmaeili, Sharmila Duppala, Vedant Nanda, Aravind Srinivasan, John P. Dickerson
Rawlsian Fairness in Online Bipartite Matching: Two-sided, Group, and Individual. CoRR (2022)
Christine Herlihy, John P. Dickerson
Networked Restless Bandits with Positive Externalities. CoRR (2022)
Vedant Nanda, Till Speicher, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Adrian Weller
Measuring Representational Robustness of Neural Networks Through Shared Invariances. CoRR (2022)
Seyed A. Esmaeili, Sharmila Duppala, Vedant Nanda, Aravind Srinivasan, John P. Dickerson
Rawlsian Fairness in Online Bipartite Matching: Two-sided, Group, and Individual. AAMAS (2022)
Arpit Bansal, Ping-yeh Chiang, Michael J. Curry, Rajiv Jain, Curtis Wigington, Varun Manjunatha, John P. Dickerson, Tom Goldstein
Certified Neural Network Watermarks with Randomized Smoothing. CoRR (2022)
Darshan Chakrabarti, John P. Dickerson, Seyed A. Esmaeili, Aravind Srinivasan, Leonidas Tsepenekas
A New Notion of Individually Fair Clustering: α-Equitable k-Center. AISTATS (2022)
Kweku Kwegyir-Aggrey, Jessica Dai, John P. Dickerson, Keegan Hines
Achieving Downstream Fairness with Geometric Repair. CoRR (2022)
Vedant Nanda, Till Speicher, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Adrian Weller
Measuring Representational Robustness of Neural Networks Through Shared Invariances. ICML (2022)
Sahil Verma, Keegan Hines, John P. Dickerson
Amortized Generation of Sequential Algorithmic Recourses for Black-Box Models. AAAI (2022)
Seyed A. Esmaeili, Sharmila Duppala, John P. Dickerson, Brian Brubach
Fair Labeled Clustering. CoRR (2022)
I. Elizabeth Kumar, Keegan E. Hines, John P. Dickerson
Equalizing Credit Opportunity in Algorithms: Aligning Algorithmic Fairness Research with U.S. Fair Lending Regulation. AIES (2022)
Ryan Sullivan, Justin K. Terry, Benjamin Black, John P. Dickerson
Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments. CoRR (2022)
Rhea Sukthanker, Samuel Dooley, John P. Dickerson, Colin White, Frank Hutter, Micah Goldblum
On the Importance of Architectures and Hyperparameters for Fairness in Face Recognition. CoRR (2022)
Arpit Bansal, Ping-Yeh Chiang, Michael J. Curry, Rajiv Jain, Curtis Wigington, Varun Manjunatha, John P. Dickerson, Tom Goldstein
Certified Neural Network Watermarks with Randomized Smoothing. ICML (2022)
Vishnu Dutt Sharma, John P. Dickerson, Pratap Tokekar
Interpretable Deep Reinforcement Learning for Green Security Games with Real-Time Information. CoRR (2022)
Michael J. Curry, Tuomas Sandholm, John P. Dickerson
Differentiable Economics for Randomized Affine Maximizer Auctions. CoRR (2022)
Teresa Datta, Daniel Nissani, Max Cembalest, Akash Khanna, Haley Massa, John P. Dickerson
Tensions Between the Proxies of Human Values in AI. CoRR (2022)
Marina Knittel, John P. Dickerson, MohammadTaghi Hajiaghayi
Generalized Reductions: Making any Hierarchical Clustering Fair and Balanced with Low Cost. CoRR (2022)
Michael J. Curry, Uro Lyi, Tom Goldstein, John P. Dickerson
Learning Revenue-Maximizing Auctions With Differentiable Matching. AISTATS (2022)
Marina Knittel, Samuel Dooley, John P. Dickerson
The Dichotomous Affiliate Stable Matching Problem: Approval-Based Matching with Applicant-Employer Relations. CoRR (2022)
Samuel Dooley, Dana Turjeman, John P. Dickerson, Elissa M. Redmiles
Field Evidence of the Effects of Privacy, Data Transparency, and Pro-social Appeals on COVID-19 App Attractiveness. CHI (2022)
Ryan Sullivan, Jordan K. Terry, Benjamin Black, John P. Dickerson
Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments. ICML (2022)
I. Elizabeth Kumar, Keegan E. Hines, John P. Dickerson
Equalizing Credit Opportunity in Algorithms: Aligning Algorithmic Fairness Research with U.S. Fair Lending Regulation. CoRR (2022)
Naveen Durvasula, Aravind Srinivasan, John P. Dickerson
Forecasting Patient Outcomes in Kidney Exchange. IJCAI (2022)
Candice Schumann, Zhi Lang, Nicholas Mattei, John P. Dickerson
Group Fairness in Bandits with Biased Feedback. AAMAS (2022)
Duncan C. McElfresh, Sujay Khandagale, Jonathan Valverde, John P. Dickerson, Colin White
On the Generalizability and Predictability of Recommender Systems. CoRR (2022)
Seyed A. Esmaeili, Sharmila Duppala, John P. Dickerson, Brian Brubach
Fair Labeled Clustering. KDD (2022)
Samuel Dooley, George Z. Wei, Tom Goldstein, John P. Dickerson
Robustness Disparities in Face Detection. CoRR (2022)
John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu
Allocation Problems in Ride-sharing Platforms: Online Matching with Offline Reusable Resources. ACM Trans. Economics and Comput. 9 (3) (2021)
Vedant Nanda, Ayan Majumdar, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Bradley C. Love, Adrian Weller
Exploring Alignment of Representations with Human Perception. CoRR (2021)
Duncan C. McElfresh, Christian Kroer, Sergey Pupyrev, Eric Sodomka, Karthik Abinav Sankararaman, Zack Chauvin, Neil Dexter, John P. Dickerson
Matching Algorithms for Blood Donation. CoRR (2021)
Neehar Peri, Michael J. Curry, Samuel Dooley, John P. Dickerson
PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning. CoRR (2021)
Sahil Verma, Keegan Hines, John P. Dickerson
Amortized Generation of Sequential Counterfactual Explanations for Black-box Models. CoRR (2021)
Mucong Ding, Kezhi Kong, Jingling Li, Chen Zhu, John P. Dickerson, Furong Huang, Tom Goldstein
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization. CoRR (2021)
Vedant Nanda, Samuel Dooley, Sahil Singla, Soheil Feizi, John P. Dickerson
Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning. FAccT (2021)
Avi Schwarzschild, Micah Goldblum, Arjun Gupta, John P. Dickerson, Tom Goldstein
Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks. ICML (2021)
Darshan Chakrabarti, John P. Dickerson, Seyed A. Esmaeili, Aravind Srinivasan, Leonidas Tsepenekas
A New Notion of Individually Fair Clustering: α-Equitable k-Center. CoRR (2021)
Duncan C. McElfresh, John P. Dickerson, Ke Ren, Hoda Bidkhori
Distributionally Robust Cycle and Chain Packing With Application To Organ Exchange. WSC (2021)
Seyed A. Esmaeili, Brian Brubach, Aravind Srinivasan, John P. Dickerson
Fair Clustering Under a Bounded Cost. CoRR (2021)
Samuel Dooley, Tom Goldstein, John P. Dickerson
Robustness Disparities in Commercial Face Detection. CoRR (2021)
Hannah K. Bako, Alisha Varma, Anuoluwapo Faboro, Mahreen Haider, Favour Nerrise, John P. Dickerson, Leilani Battle
User-Driven Programming Support for Rapid Visualization Authoring in D3. CoRR (2021)
Samuel Dooley, Ryan Downing, George Z. Wei, Nathan Shankar, Bradon Thymes, Gudrun Thorkelsdottir, Tiye Kurtz-Miott, Rachel Mattson, Olufemi Obiwumi, Valeriia Cherepanova, Micah Goldblum, John P. Dickerson, Tom Goldstein
Comparing Human and Machine Bias in Face Recognition. CoRR (2021)
Sahil Verma, Aditya Lahiri, John P. Dickerson, Su-In Lee
Pitfalls of Explainable ML: An Industry Perspective. CoRR (2021)
Haris Aziz, Ágnes Cseh, John P. Dickerson, Duncan C. McElfresh
Optimal Kidney Exchange with Immunosuppressants. CoRR (2021)
Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Aravind Srinivasan, Leonidas Tsepenekas
Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints. CoRR (2021)
Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Aravind Srinivasan, Leonidas Tsepenekas
Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints. AAAI (2021)
Sanmay Das, Nicholas Mattei, John P. Dickerson, Sven Koenig, Louise A. Dennis, Larry R. Medsker, Todd W. Neller, Iolanda Leite, Anuj Karpatne, Alan Tsang
SIGAI annual report: July 1 2020 - June 30 2021. AI Matters 7 (3) (2021)
Valeriia Cherepanova, Vedant Nanda, Micah Goldblum, John P. Dickerson, Tom Goldstein
Technical Challenges for Training Fair Neural Networks. CoRR (2021)
Valeriia Cherepanova, Micah Goldblum, Harrison Foley, Shiyuan Duan, John P. Dickerson, Gavin Taylor, Tom Goldstein
LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition. ICLR (2021)
Valeriia Cherepanova, Micah Goldblum, Harrison Foley, Shiyuan Duan, John P. Dickerson, Gavin Taylor, Tom Goldstein
LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition. CoRR (2021)
Sahil Verma, John P. Dickerson, Keegan Hines
Counterfactual Explanations for Machine Learning: Challenges Revisited. CoRR (2021)
Stephanie Allen, John P. Dickerson, Steven A. Gabriel
Using Inverse Optimization to Learn Cost Functions in Generalized Nash Games. CoRR (2021)
Naveen Raman, Sanket Shah, John P. Dickerson
Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling. IJCAI (2021)
Fotini Christia, Michael J. Curry, Constantinos Daskalakis, Erik D. Demaine, John P. Dickerson, MohammadTaghi Hajiaghayi, Adam Hesterberg, Marina Knittel, Aidan Milliff
Scalable Equilibrium Computation in Multi-agent Influence Games on Networks. AAAI (2021)
Duncan C. McElfresh, Lok Chan, Kenzie Doyle, Walter Sinnott-Armstrong, Vincent Conitzer, Jana Schaich Borg, John P. Dickerson
Indecision Modeling. AAAI (2021)
Haris Aziz, Ágnes Cseh, John P. Dickerson, Duncan C. McElfresh
Optimal Kidney Exchange with Immunosuppressants. AAAI (2021)
Seyed A. Esmaeili, Brian Brubach, Leonidas Tsepenekas, John P. Dickerson
Probabilistic Fair Clustering. CoRR (2020)
Michael Albert, John P. Dickerson
AAAI/ACM SIGAI job fair 2020: a retrospective. AI Matters 6 (1) (2020)
Vedant Nanda, Samuel Dooley, Sahil Singla, Soheil Feizi, John P. Dickerson
Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning. CoRR (2020)
Debjani Saha, Candice Schumann, Duncan C. McElfresh, John P. Dickerson, Michelle L. Mazurek, Michael Carl Tschantz
Human Comprehension of Fairness in Machine Learning. AIES (2020)
Kevin Kuo, Anthony Ostuni, Elizabeth Horishny, Michael J. Curry, Samuel Dooley, Ping-Yeh Chiang, Tom Goldstein, John P. Dickerson
ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning. CoRR (2020)
Michael J. Curry, Ping-Yeh Chiang, Tom Goldstein, John P. Dickerson
Certifying Strategyproof Auction Networks. CoRR (2020)
Avrim Blum, John P. Dickerson, Nika Haghtalab, Ariel D. Procaccia, Tuomas Sandholm, Ankit Sharma
Ignorance Is Almost Bliss: Near-Optimal Stochastic Matching with Few Queries. Oper. Res. 68 (1) (2020)
Saba Ahmadi, Faez Ahmed, John P. Dickerson, Mark D. Fuge, Samir Khuller
An Algorithm for Multi-Attribute Diverse Matching. IJCAI (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

John P. Dickerson