A graph-theoretic approach to protect static and moving targets from adversaries. - John P. Dickerson; Gerardo I. Simari; V. S. Subrahmanian; Sarit Kraus (AAMAS, 2010)

Cost-Based Query Answering in Action Probabilistic Logic Programs. - Gerardo I. Simari; John P. Dickerson; V. S. Subrahmanian (SUM, 2010)

Dealing with Lashkar-e-Taiba: A Multi-player Game-Theoretic Perspective. - John P. Dickerson; Aaron Mannes; V. S. Subrahmanian (EISIC, 2011)

Dynamic Matching via Weighted Myopia with Application to Kidney Exchange. - John P. Dickerson; Ariel D. Procaccia; Tuomas Sandholm (AAAI, 2012)

Optimizing kidney exchange with transplant chains: theory and reality. - John P. Dickerson; Ariel D. Procaccia; Tuomas Sandholm (AAMAS, 2012)

Speeding Up Particle Trajectory Simulations Under Moving Force Fields using Graphic Processing Units. - Robert Patro; John P. Dickerson; Sujal Bista; Satyandra K. Gupta; Amitabh Varshney (J. Comput. Inf. Sci. Eng., 2012)

Adversarial Geospatial Abduction Problems. - Paulo Shakarian; John P. Dickerson; V. S. Subrahmanian (ACM Trans. Intell. Syst. Technol., 2012)

Throwing Darts: Random Sampling Helps Tree Search when the Number of Short Certificates is Moderate. - John Paul Dickerson; Tuomas Sandholm (AAAI (Late-Breaking Developments), 2013)

PREVE: a policy recommendation engine based on vector equilibria applied to reducing LeT's attacks. - John P. Dickerson; Anshul Sawant; Mohammad Taghi Hajiaghayi; V. S. Subrahmanian (ASONAM, 2013)

Parallel Abductive Query Answering in Probabilistic Logic Programs. - Gerardo I. Simari; John P. Dickerson; Amy Sliva; V. S. Subrahmanian (ACM Trans. Comput. Log., 2013)

The Computational Rise and Fall of Fairness. - John P. Dickerson; Jonathan R. Goldman; Jeremy Karp; Ariel D. Procaccia; Tuomas Sandholm (AAAI, 2014)

Multi-Organ Exchange: The Whole Is Greater than the Sum of its Parts. - John P. Dickerson; Tuomas Sandholm (AAAI, 2014)

Balancing Efficiency and Fairness in Dynamic Kidney Exchange. - John Paul Dickerson; Tuomas Sandholm (AAAI Workshop: Modern Artificial Intelligence for Health Analytics, 2014)

Using sentiment to detect bots on Twitter: Are humans more opinionated than bots? - John P. Dickerson; Vadim Kagan; V. S. Subrahmanian (ASONAM, 2014)

Robust dynamic optimization with application to kidney exchange. - John P. Dickerson (AAMAS, 2014)

Price of fairness in kidney exchange. - John P. Dickerson; Ariel D. Procaccia; Tuomas Sandholm (AAMAS, 2014)

Endogenously- but not Exogenously-driven Selective Sustained Attention is Related to Learning in a Classroom-like Setting in Kindergarten Children. - Lucy Erickson; Erik D. Thiessen; Karrie E. Godwin; John P. Dickerson; Anna V. Fisher (CogSci, 2014)

Forecasting Country Stability in North Africa. - Steven Banaszak; Elizabeth K. Bowman; John P. Dickerson; V. S. Subrahmanian (JISIC, 2014)

FutureMatch: Combining Human Value Judgments and Machine Learning to Match in Dynamic Environments. - John P. Dickerson; Tuomas Sandholm (AAAI, 2015)

Strategy-Proof and Efficient Kidney Exchange Using a Credit Mechanism. - Chen Hajaj; John P. Dickerson; Avinatan Hassidim; Tuomas Sandholm; David Sarne (AAAI, 2015)

Automated Generation of Counterterrorism Policies Using Multiexpert Input. - Anshul Sawant; John P. Dickerson; Mohammad Taghi Hajiaghayi; V. S. Subrahmanian (ACM Trans. Intell. Syst. Technol., 2015)

Fast Optimal Clearing of Capped-Chain Barter Exchanges. - Benjamin Plaut; John P. Dickerson; Tuomas Sandholm (AAAI, 2016)

Position-Indexed Formulations for Kidney Exchange. - John P. Dickerson; David F. Manlove; Benjamin Plaut; Tuomas Sandholm; James Trimble 001 (EC, 2016)

Hardness of the Pricing Problem for Chains in Barter Exchanges. - Benjamin Plaut; John P. Dickerson; Tuomas Sandholm (CoRR, 2016)

Small Representations of Big Kidney Exchange Graphs. - John P. Dickerson; Aleksandr M. Kazachkov; Ariel D. Procaccia; Tuomas Sandholm (AAAI Workshops, 2017)

Inter-Club Kidney Exchange. - Gabriele Farina; John P. Dickerson; Tuomas Sandholm (AAAI Workshops, 2017)

Diverse Weighted Bipartite b-Matching. - Faez Ahmed; John P. Dickerson; Mark D. Fuge (IJCAI, 2017)

Operation Frames and Clubs in Kidney Exchange. - Gabriele Farina; John P. Dickerson; Tuomas Sandholm (IJCAI, 2017)

Learning to Schedule Deadline- and Operator-Sensitive Tasks. - Hanan Rosemarin; John P. Dickerson; Sarit Kraus (CoRR, 2017)

The Diverse Cohort Selection Problem: Multi-Armed Bandits with Varied Pulls. - Candice Schumann; Samsara N. Counts; Jeffrey S. Foster; John P. Dickerson (CoRR, 2017)

Multi-Organ Exchange. - John P. Dickerson; Tuomas Sandholm (J. Artif. Intell. Res., 2017)

Balancing Lexicographic Fairness and a Utilitarian Objective with Application to Kidney Exchange. - Duncan C. McElfresh; John P. Dickerson (AAAI Workshops, 2018)

Assigning Tasks to Workers based on Historical Data: Online Task Assignment with Two-sided Arrivals. - John P. Dickerson; Karthik Abinav Sankararaman; Aravind Srinivasan; Pan Xu 001 (AAMAS, 2018)

Equitable Security: Optimizing Distribution of Nudges and Resources. - Elissa M. Redmiles; John P. Dickerson; Krishna P. Gummadi; Michelle L. Mazurek (CCS, 2018)

A Muffin-Theorem Generator. - Guangqi Cui; John P. Dickerson; Naveen Durvasula; William Gasarch; Erik Metz; Jacob Prinz; Naveen Raman 001; Daniel Smolyak; Sung Hyun Yoo (FUN, 2018)

Equilibrium Behavior in Competing Dynamic Matching Markets. - Zhuoshu Li; Neal Gupta; Sanmay Das; John P. Dickerson (IJCAI, 2018)

Dancing Pigs or Externalities?: Measuring the Rationality of Security Decisions. - Elissa M. Redmiles; Michelle L. Mazurek; John P. Dickerson (EC, 2018)

AAAI/ACM SIGAI job fair 2018: a retrospective. - John P. Dickerson; Nicholas Mattei (AI Matters, 2018)

ACM SIGAI activity report. - Sven Koenig; Sanmay Das; Rosemary D. Paradis; John P. Dickerson; Yolanda Gil; Katherine Guo; Benjamin Kuipers; Hang Ma 001; Nicholas Mattei; Amy McGovern; Larry R. Medsker; Todd W. Neller; et al. (AI Matters, 2018)

Balancing Relevance and Diversity in Online Bipartite Matching via Submodularity. - John P. Dickerson; Karthik Abinav Sankararaman; Aravind Srinivasan; Pan Xu 001 (AAAI, 2019)

Scalable Robust Kidney Exchange. - Duncan C. McElfresh; Hoda Bidkhori; John P. Dickerson (AAAI, 2019)

A Unified Approach to Online Matching with Conflict-Aware Constraints. - Pan Xu 001; Yexuan Shi; Hao Cheng; John P. Dickerson; Karthik Abinav Sankararaman; Aravind Srinivasan; Yongxin Tong; Leonidas Tsepenekas (AAAI, 2019)

Online Resource Allocation with Matching Constraints. - John P. Dickerson; Karthik Abinav Sankararaman; Kanthi Kiran Sarpatwar; Aravind Srinivasan; Kun-Lung Wu; Pan Xu 001 (AAMAS, 2019)

The Diverse Cohort Selection Problem. - Candice Schumann; Samsara N. Counts; Jeffrey S. Foster; John P. Dickerson (AAMAS, 2019)

Batch-wise Logit-Similarity: Generalizing Logit-Squeezing and Label-Smoothing. - Ali Shafahi; Amin Ghiasi; Mahyar Najibi; Furong Huang; John P. Dickerson; Tom Goldstein (BMVC, 2019)

Making the Cut: A Bandit-based Approach to Tiered Interviewing. - Candice Schumann; Zhi Lang; Jeffrey S. Foster; John P. Dickerson (NeurIPS, 2019)

Adversarial training for free! - Ali Shafahi; Mahyar Najibi; Amin Ghiasi; Zheng Xu 002; John P. Dickerson; Christoph Studer; Larry S. Davis; Gavin Taylor; Tom Goldstein (NeurIPS, 2019)

Mix and Match: Markov Chains and Mixing Times for Matching in Rideshare. - Michael J. Curry; John P. Dickerson; Karthik Abinav Sankararaman; Aravind Srinivasan; Yuhao Wan; Pan Xu 001 (WINE, 2019)

AAAI/ACM SIGAI job fair 2019: a retrospective. - Christopher Amato; John P. Dickerson (AI Matters, 2019)

ACM SIGAI activity report. - Sven Koenig; Sanmay Das; Rosemary D. Paradis; John P. Dickerson; Yolanda Gil; Katherine Guo; Benjamin Kuipers; Iolanda Leite; Hang Ma 001; Nicholas Mattei; Amy McGovern; Larry R. Medsker; et al. (AI Matters, 2019)

Algorithms for Optimal Diverse Matching. - Saba Ahmadi; Faez Ahmed; John P. Dickerson; Mark D. Fuge; Samir Khuller (CoRR, 2019)

Strong Baseline Defenses Against Clean-Label Poisoning Attacks. - Neal Gupta; W. Ronny Huang; Liam Fowl; Chen Zhu 001; Soheil Feizi; Tom Goldstein; John P. Dickerson (CoRR, 2019)

Mix and Match: Markov Chains & Mixing Times for Matching in Rideshare. - Michael J. Curry; John P. Dickerson; Karthik Abinav Sankararaman; Aravind Srinivasan; Yuhao Wan; Pan Xu 001 (CoRR, 2019)

Group Fairness in Bandit Arm Selection. - Candice Schumann; Zhi Lang; Nicholas Mattei; John P. Dickerson (CoRR, 2019)

Failure-Aware Kidney Exchange. - John P. Dickerson; Ariel D. Procaccia; Tuomas Sandholm (Manag. Sci., 2019)

Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms during High-Demand Hours. - Vedant Nanda; Pan Xu 001; Karthik Abinav Sankararaman; John P. Dickerson; Aravind Srinivasan (AAAI, 2020)

Universal Adversarial Training. - Ali Shafahi; Mahyar Najibi; Zheng Xu 002; John P. Dickerson; Larry S. Davis; Tom Goldstein (AAAI, 2020)

Clearing Kidney Exchanges via Graph Neural Network Guided Tree Search (Student Abstract). - Zeyu Zhao 002; John P. Dickerson (AAAI, 2020)

Artificial Artificial Intelligence: Measuring Influence of AI 'Assessments' on Moral Decision-Making. - Lok Chan; Kenzie Doyle; Duncan C. McElfresh; Vincent Conitzer; John P. Dickerson; Jana Schaich Borg; Walter Sinnott-Armstrong (AIES, 2020)

Human Comprehension of Fairness in Machine Learning. - Debjani Saha; Candice Schumann; Duncan C. McElfresh; John P. Dickerson; Michelle L. Mazurek; Michael Carl Tschantz (AIES, 2020)

We Need Fairness and Explainability in Algorithmic Hiring. - Candice Schumann; Jeffrey S. Foster; Nicholas Mattei; John P. Dickerson (AAMAS, 2020)

Deep k-NN Defense Against Clean-Label Data Poisoning Attacks. - Neehar Peri; Neal Gupta; W. Ronny Huang; Liam Fowl; Chen Zhu 001; Soheil Feizi; Tom Goldstein; John P. Dickerson (ECCV Workshops (1), 2020)

A Pairwise Fair and Community-preserving Approach to k-Center Clustering. - Brian Brubach; Darshan Chakrabarti; John P. Dickerson; Samir Khuller; Aravind Srinivasan; Leonidas Tsepenekas (ICML, 2020)

Measuring Non-Expert Comprehension of Machine Learning Fairness Metrics. - Debjani Saha; Candice Schumann; Duncan C. McElfresh; John P. Dickerson; Michelle L. Mazurek; Michael Carl Tschantz (ICML, 2020)

An Algorithm for Multi-Attribute Diverse Matching. - Saba Ahmadi; Faez Ahmed; John P. Dickerson; Mark D. Fuge; Samir Khuller (IJCAI, 2020)

Detection as Regression: Certified Object Detection with Median Smoothing. - Ping-yeh Chiang; Michael J. Curry; Ahmed Abdelkader; Aounon Kumar; John Dickerson 001; Tom Goldstein (NeurIPS, 2020)

Certifying Strategyproof Auction Networks. - Michael J. Curry; Ping-Yeh Chiang; Tom Goldstein; John Dickerson 001 (NeurIPS, 2020)

Probabilistic Fair Clustering. - Seyed A. Esmaeili; Brian Brubach; Leonidas Tsepenekas; John Dickerson 001 (NeurIPS, 2020)

Improving Policy-Constrained Kidney Exchange via Pre-Screening. - Duncan C. McElfresh; Michael J. Curry; Tuomas Sandholm; John Dickerson 001 (NeurIPS, 2020)

Kidney Exchange with Inhomogeneous Edge Existence Uncertainty. - Hoda Bidkhori; John Dickerson 001; Duncan C. McElfresh; Ke Ren (UAI, 2020)

Adapting a kidney exchange algorithm to align with human values. - Rachel Freedman; Jana Schaich Borg; Walter Sinnott-Armstrong; John P. Dickerson; Vincent Conitzer (Artif. Intell., 2020)

AAAI/ACM SIGAI job fair 2020: a retrospective. - Michael Albert 002; John P. Dickerson (AI Matters, 2020)

SIGAI annual report: July 1 2019 - June 30 2020. - Sanmay Das; Nicholas Mattei; John P. Dickerson; Sven Koenig; Louise A. Dennis; Larry R. Medsker; Todd W. Neller; Iolanda Leite; Anuj Karpatne (AI Matters, 2020)

Can an Algorithm be My Healthcare Proxy? - Duncan C. McElfresh; Samuel Dooley; Yuan Cui; Kendra Griesman; Weiqin Wang; Tyler Will; Neil Sehgal; John P. Dickerson (CoRR, 2020)

Forming Diverse Teams from Sequentially Arriving People. - Faez Ahmed; John Dickerson 001; Mark D. Fuge (CoRR, 2020)

Active Preference Elicitation via Adjustable Robust Optimization. - Phebe Vayanos; Duncan C. McElfresh; Yingxiao Ye; John Paul Dickerson; Eric Rice (CoRR, 2020)

Unifying Model Explainability and Robustness via Machine-Checkable Concepts. - Vedant Nanda; Till Speicher; John P. Dickerson; Krishna P. Gummadi; Muhammad Bilal Zafar (CoRR, 2020)

Detection as Regression: Certified Object Detection by Median Smoothing. - Ping-yeh Chiang; Michael J. Curry; Ahmed Abdelkader; Aounon Kumar; John P. Dickerson; Tom Goldstein (CoRR, 2020)

The Affiliate Matching Problem: On Labor Markets where Firms are Also Interested in the Placement of Previous Workers. - Samuel Dooley; John P. Dickerson (CoRR, 2020)

ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning. - Kevin Kuo; Anthony Ostuni; Elizabeth Horishny; Michael J. Curry; Samuel Dooley; Ping-yeh Chiang; Tom Goldstein; John P. Dickerson (CoRR, 2020)

Counterfactual Explanations for Machine Learning: A Review. - Sahil Verma; John P. Dickerson; Keegan Hines (CoRR, 2020)

Noisy Labels Can Induce Good Representations. - Jingling Li; Mozhi Zhang; Keyulu Xu; John P. Dickerson; Jimmy Ba (CoRR, 2020)

Ignorance Is Almost Bliss: Near-Optimal Stochastic Matching with Few Queries. - Avrim Blum; John P. Dickerson; Nika Haghtalab; Ariel D. Procaccia; Tuomas Sandholm; Ankit Sharma 001 (Oper. Res., 2020)

Optimal Kidney Exchange with Immunosuppressants. - Haris Aziz 001; Ágnes Cseh; John P. Dickerson; Duncan C. McElfresh (AAAI, 2021)

Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints. - Brian Brubach; Darshan Chakrabarti; John P. Dickerson; Aravind Srinivasan; Leonidas Tsepenekas (AAAI, 2021)

Scalable Equilibrium Computation in Multi-agent Influence Games on Networks. - Fotini Christia; Michael J. Curry; Constantinos Daskalakis; Erik D. Demaine; John P. Dickerson; MohammadTaghi Hajiaghayi; Adam Hesterberg; Marina Knittel; Aidan Milliff (AAAI, 2021)

Indecision Modeling. - Duncan C. McElfresh; Lok Chan; Kenzie Doyle; Walter Sinnott-Armstrong; Vincent Conitzer; Jana Schaich Borg; John P. Dickerson (AAAI, 2021)

Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning. - Vedant Nanda; Samuel Dooley; Sahil Singla 002; Soheil Feizi; John P. Dickerson (FAccT, 2021)

LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition. - Valeriia Cherepanova; Micah Goldblum; Harrison Foley; Shiyuan Duan; John P. Dickerson; Gavin Taylor; Tom Goldstein (ICLR, 2021)

Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks. - Avi Schwarzschild; Micah Goldblum; Arjun Gupta; John P. Dickerson; Tom Goldstein (ICML, 2021)

Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling. - Naveen Raman 001; Sanket Shah; John P. Dickerson (IJCAI, 2021)

VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization. - Mucong Ding; Kezhi Kong; Jingling Li; Chen Zhu 001; John Dickerson 001; Furong Huang; Tom Goldstein (NeurIPS, 2021)

Fair Clustering Under a Bounded Cost. - Seyed A. Esmaeili; Brian Brubach; Aravind Srinivasan; John Dickerson 001 (NeurIPS, 2021)

How does a Neural Network's Architecture Impact its Robustness to Noisy Labels? - Jingling Li; Mozhi Zhang; Keyulu Xu; John Dickerson 001; Jimmy Ba (NeurIPS, 2021)

PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning. - Neehar Peri; Michael J. Curry; Samuel Dooley; John Dickerson 001 (NeurIPS, 2021)

Distributionally Robust Cycle and Chain Packing With Application To Organ Exchange. - Duncan C. McElfresh; John P. Dickerson; Ke Ren; Hoda Bidkhori (WSC, 2021)

SIGAI annual report: July 1 2020 - June 30 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 (AI Matters, 2021)

Technical Challenges for Training Fair Neural Networks. - Valeriia Cherepanova; Vedant Nanda; Micah Goldblum; John P. Dickerson; Tom Goldstein (CoRR, 2021)

Amortized Generation of Sequential Counterfactual Explanations for Black-box Models. - Sahil Verma; Keegan Hines; John P. Dickerson (CoRR, 2021)

Counterfactual Explanations for Machine Learning: Challenges Revisited. - Sahil Verma; John P. Dickerson; Keegan Hines (CoRR, 2021)

Pitfalls of Explainable ML: An Industry Perspective. - Sahil Verma; Aditya Lahiri; John P. Dickerson; Su-In Lee (CoRR, 2021)

Robustness Disparities in Commercial Face Detection. - Samuel Dooley; Tom Goldstein; John P. Dickerson (CoRR, 2021)

Comparing Human and Machine Bias in Face Recognition. - 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; et al. (CoRR, 2021)

Exploring Alignment of Representations with Human Perception. - Vedant Nanda; Ayan Majumdar; Camila Kolling; John P. Dickerson; Krishna P. Gummadi; Bradley C. Love; Adrian Weller (CoRR, 2021)

User-Driven Programming Support for Rapid Visualization Authoring in D3. - Hannah K. Bako; Alisha Varma; Anuoluwapo Faboro; Mahreen Haider; Favour Nerrise; John P. Dickerson; Leilani Battle (CoRR, 2021)

Allocation Problems in Ride-sharing Platforms: Online Matching with Offline Reusable Resources. - John P. Dickerson; Karthik Abinav Sankararaman; Aravind Srinivasan; Pan Xu 001 (ACM Trans. Economics and Comput., 2021)

Amortized Generation of Sequential Algorithmic Recourses for Black-Box Models. - Sahil Verma; Keegan Hines; John P. Dickerson (AAAI, 2022)

Equalizing Credit Opportunity in Algorithms: Aligning Algorithmic Fairness Research with U.S. Fair Lending Regulation. - I. Elizabeth Kumar; Keegan E. Hines; John P. Dickerson (AIES, 2022)

A New Notion of Individually Fair Clustering: α-Equitable k-Center. - Darshan Chakrabarti; John P. Dickerson; Seyed A. Esmaeili; Aravind Srinivasan; Leonidas Tsepenekas (AISTATS, 2022)

Learning Revenue-Maximizing Auctions With Differentiable Matching. - Michael J. Curry; Uro Lyi; Tom Goldstein; John P. Dickerson (AISTATS, 2022)

Rawlsian Fairness in Online Bipartite Matching: Two-sided, Group, and Individual. - Seyed A. Esmaeili; Sharmila Duppala; Vedant Nanda; Aravind Srinivasan; John P. Dickerson (AAMAS, 2022)

Group Fairness in Bandits with Biased Feedback. - Candice Schumann; Zhi Lang; Nicholas Mattei; John P. Dickerson (AAMAS, 2022)

Field Evidence of the Effects of Privacy, Data Transparency, and Pro-social Appeals on COVID-19 App Attractiveness. - Samuel Dooley; Dana Turjeman; John P. Dickerson; Elissa M. Redmiles (CHI, 2022)

Certified Neural Network Watermarks with Randomized Smoothing. - Arpit Bansal; Ping-Yeh Chiang; Michael J. Curry; Rajiv Jain; Curtis Wigington; Varun Manjunatha; John P. Dickerson; Tom Goldstein (ICML, 2022)

Measuring Representational Robustness of Neural Networks Through Shared Invariances. - Vedant Nanda; Till Speicher; Camila Kolling; John P. Dickerson; Krishna P. Gummadi; Adrian Weller (ICML, 2022)

Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments. - Ryan Sullivan; Jordan K. Terry; Benjamin Black; John P. Dickerson (ICML, 2022)

Forecasting Patient Outcomes in Kidney Exchange. - Naveen Durvasula; Aravind Srinivasan; John P. Dickerson (IJCAI, 2022)

The Dichotomous Affiliate Stable Matching Problem: Approval-Based Matching with Applicant-Employer Relations. - Marina Knittel; Samuel Dooley; John P. Dickerson (IJCAI, 2022)

Fair Labeled Clustering. - Seyed A. Esmaeili; Sharmila Duppala; John P. Dickerson; Brian Brubach (KDD, 2022)

Robustness Disparities in Face Detection. - Samuel Dooley; George Z. Wei; Tom Goldstein; John Dickerson 001 (NeurIPS, 2022)

On the Generalizability and Predictability of Recommender Systems. - Duncan C. McElfresh; Sujay Khandagale; Jonathan Valverde; John Dickerson 001; Colin White (NeurIPS, 2022)

Using inverse optimization to learn cost functions in generalized Nash games. - Stephanie Allen; Steven A. Gabriel; John P. Dickerson (Comput. Oper. Res., 2022)

Achieving Downstream Fairness with Geometric Repair. - Kweku Kwegyir-Aggrey; Jessica Dai; John P. Dickerson; Keegan Hines (CoRR, 2022)

Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments. - Ryan Sullivan; Justin K. Terry; Benjamin Black; John P. Dickerson (CoRR, 2022)

Generalized Reductions: Making any Hierarchical Clustering Fair and Balanced with Low Cost. - Marina Knittel; John P. Dickerson; MohammadTaghi Hajiaghayi (CoRR, 2022)

On the Importance of Architectures and Hyperparameters for Fairness in Face Recognition. - Rhea Sukthanker; Samuel Dooley; John P. Dickerson; Colin White; Frank Hutter; Micah Goldblum (CoRR, 2022)

Interpretable Deep Reinforcement Learning for Green Security Games with Real-Time Information. - Vishnu Dutt Sharma; John P. Dickerson; Pratap Tokekar (CoRR, 2022)

Targets in Reinforcement Learning to solve Stackelberg Security Games. - Saptarashmi Bandyopadhyay; Chenqi Zhu; Philip Daniel; Joshua Morrison; Ethan Shay; John Dickerson 001 (CoRR, 2022)

SIGAI Annual Report: July 1 2021 - June 30 2022. - Sanmay Das; Nicholas Mattei; John P. Dickerson; Sven Koenig; Louise A. Dennis; Larry R. Medsker; Ziyu Yao 002; Anuj Karpatne; Alan Tsang; Matt Luckcuck (AI Matters, 2022)

Rawlsian Fairness in Online Bipartite Matching: Two-Sided, Group, and Individual. - Seyed A. Esmaeili; Sharmila Duppala; Davidson Cheng; Vedant Nanda; Aravind Srinivasan; John P. Dickerson (AAAI, 2023)

Networked Restless Bandits with Positive Externalities. - Christine Herlihy; John P. Dickerson (AAAI, 2023)

Do Invariances in Deep Neural Networks Align with Human Perception? - Vedant Nanda; Ayan Majumdar; Camila Kolling; John P. Dickerson; Krishna P. Gummadi; Bradley C. Love; Adrian Weller (AAAI, 2023)

A Deep Dive into Dataset Imbalance and Bias in Face Identification. - Valeriia Cherepanova; Steven Reich; Samuel Dooley; Hossein Souri; John P. Dickerson; Micah Goldblum; Tom Goldstein (AIES, 2023)

Reckoning with the Disagreement Problem: Explanation Consensus as a Training Objective. - Avi Schwarzschild; Max Cembalest; Karthik Rao; Keegan Hines; John P. Dickerson (AIES, 2023)

RecRec: Algorithmic Recourse for Recommender Systems. - Sahil Verma; Ashudeep Singh; Varich Boonsanong; John P. Dickerson; Chirag Shah 001 (CIKM, 2023)

Generalized Reductions: Making any Hierarchical Clustering Fair and Balanced with Low Cost. - Marina Knittel; Max Springer; John P. Dickerson; MohammadTaghi Hajiaghayi (ICML, 2023)

Differentiable Economics for Randomized Affine Maximizer Auctions. - Michael J. Curry; Tuomas Sandholm; John P. Dickerson (IJCAI, 2023)

Group Fairness in Set Packing Problems. - Sharmila Duppala; Juan Luque; John P. Dickerson; Aravind Srinivasan (IJCAI, 2023)

User-Driven Support for Visualization Prototyping in D3. - Hannah K. Bako; Alisha Varma; Anuoluwapo Faboro; Mahreen Haider; Favour Nerrise; Bissaka Kenah; John P. Dickerson; Leilani Battle (IUI, 2023)

Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting. - Christine Herlihy; Aviva Prins; Aravind Srinivasan; John P. Dickerson (KDD, 2023)

Doubly Constrained Fair Clustering. - John P. Dickerson; Seyed A. Esmaeili; Jamie H. Morgenstern; Claire Jie Zhang (NeurIPS, 2023)

Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition. - Samuel Dooley; Rhea Sukthanker; John P. Dickerson; Colin White; Frank Hutter; Micah Goldblum (NeurIPS, 2023)

Fair, Polylog-Approximate Low-Cost Hierarchical Clustering. - Marina Knittel; Max Springer; John P. Dickerson; MohammadTaghi Hajiaghayi (NeurIPS, 2023)

Diffused Redundancy in Pre-trained Representations. - Vedant Nanda; Till Speicher; John P. Dickerson; Krishna P. Gummadi; Soheil Feizi; Adrian Weller (NeurIPS, 2023)

Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks. - Ryan Sullivan; Akarsh Kumar; Shengyi Huang; John P. Dickerson; Joseph Suarez (NeurIPS, 2023)

Tensions Between the Proxies of Human Values in AI. - Teresa Datta; Daniel Nissani; Max Cembalest; Akash Khanna; Haley Massa; John Dickerson 001 (SaTML, 2023)

Neural Auctions Compromise Bidder Information. - Alex Stein; Avi Schwarzschild; Michael J. Curry; Tom Goldstein; John P. Dickerson (CoRR, 2023)

Who's Thinking? A Push for Human-Centered Evaluation of LLMs using the XAI Playbook. - Teresa Datta; John P. Dickerson (CoRR, 2023)

Artificial Intelligence/Operations Research Workshop 2 Report Out. - 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 (CoRR, 2023)

Effective Backdoor Mitigation Depends on the Pre-training Objective. - Sahil Verma; Gantavya Bhatt; Avi Schwarzschild; Soumye Singhal; Arnav Mohanty Das; Chirag Shah 001; John P. Dickerson; Jeff A. Bilmes (CoRR, 2023)

SIGAI Annual Report: July 1 2022 - August 30 2023. - Sanmay Das; Nicholas Mattei; John P. Dickerson; Sven Koenig; Louise A. Dennis; Larry R. Medsker; Ziyu Yao 002; Anuj Karpatne; Alan Tsang; Matt Luckcuck (AI Matters, 2023)

Matching algorithms for blood donation. - Duncan C. McElfresh; Christian Kroer; Sergey Pupyrev; Eric Sodomka; Karthik Abinav Sankararaman; Zack Chauvin; Neil Dexter; John P. Dickerson (Nat. Mac. Intell., 2023)

Strategies for Increasing Corporate Responsible AI Prioritization. - Angelina Wang; Teresa Datta; John P. Dickerson (AIES (1), 2024)

Barter Exchange with Shared Item Valuations. - Juan Luque; Sharmila Duppala; John P. Dickerson; Aravind Srinivasan (WWW, 2024)

Large language models cannot replace human participants because they cannot portray identity groups. - Angelina Wang; Jamie Morgenstern; John P. Dickerson (CoRR, 2024)

Fair Clustering: Critique, Caveats, and Future Directions. - John Dickerson 001; Seyed A. Esmaeili; Jamie Morgenstern; Claire Jie Zhang (CoRR, 2024)

A Simple Baseline for Predicting Events with Auto-Regressive Tabular Transformers. - Alex Stein; Samuel Sharpe; Doron Bergman; Senthil Kumar; C. Bayan Bruss; John Dickerson 001; Tom Goldstein; Micah Goldblum (CoRR, 2024)

Syllabus: Portable Curricula for Reinforcement Learning Agents. - Ryan Sullivan; Ryan Pégoud; Ameen Ur Rahmen; Xinchen Yang; Junyun Huang; Aayush Verma; Nistha Mitra; John P. Dickerson (CoRR, 2024)

Matching Tasks and Workers under Known Arrival Distributions: Online Task Assignment with Two-sided Arrivals. - John P. Dickerson; Karthik Abinav Sankararaman; Aravind Srinivasan; Pan Xu 001; Yifan Xu 002 (ACM Trans. Economics and Comput., 2024)

Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review. - Sahil Verma; Varich Boonsanong; Minh Hoang; Keegan Hines; John Dickerson 001; Chirag Shah 001 (ACM Comput. Surv., 2024)

Robust Fair Clustering with Group Membership Uncertainty Sets. - Sharmila Duppala; Juan Luque; John P. Dickerson; Seyed A. Esmaeili (AISTATS, 2025)

Style Outweighs Substance: Failure Modes of LLM Judges in Alignment Benchmarking. - Benjamin Feuer; Micah Goldblum; Teresa Datta; Sanjana Nambiar; Raz Besaleli; Samuel Dooley; Max Cembalest; John P. Dickerson (ICLR, 2025)

SoK: Fair Clustering: Critique, Caveats, and Future Directions. - John Dickerson 001; Seyed A. Esmaeili; Jamie Morgenstern; Claire Jie Zhang (SaTML, 2025)

Advancing African American and hispanic health literacy with a bilingual, personalized, prevention smartphone application. - Neil Sehgal; Devlon Nicole Jackson; Christine Herlihy; John Dickerson 001; Cynthia Baur (Health Informatics J., 2025)

Large language models that replace human participants can harmfully misportray and flatten identity groups. - Angelina Wang; Jamie Morgenstern; John P. Dickerson (Nat. Mac. Intell., 2025)

Effective Backdoor Mitigation in Vision-Language Models Depends on the Pre-training Objective. - Sahil Verma; Gantavya Bhatt; Avi Schwarzschild; Soumye Singhal; Arnav Mohanty Das; Chirag Shah 001; John P. Dickerson; Pin-Yu Chen; Jeff Bilmes (Trans. Mach. Learn. Res., 2025)

Who Gets the Kidney? Human-AI Alignment, Indecision, and Moral Values. - John P. Dickerson; Hadi Hosseini; Samarth Khanna; Leona Pierce (CoRR, 2025)