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ORCIDJohn Dickerson 0001
John P. Dickerson – John Paul Dickerson
Person information
- affiliation: University of Maryland, MD, USA
Other persons with the same name
- John Dickerson 0002 (aka: John E. Dickerson) — Iowa State University, Ames, IA, USA
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2020 – today
- 2024
[j21]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): 6 (2024)- [c110]Juan Luque, Sharmila Duppala, John P. Dickerson, Aravind Srinivasan:
Barter Exchange with Shared Item Valuations. WWW 2024: 199-210 - [i93]Angelina Wang, Jamie Morgenstern, John P. Dickerson:
Large language models cannot replace human participants because they cannot portray identity groups. CoRR abs/2402.01908 (2024) - [i92]Angelina Wang, Teresa Datta, John P. Dickerson:
Strategies for Increasing Corporate Responsible AI Prioritization. CoRR abs/2405.03855 (2024) - [i91]Sharmila Duppala, Juan Luque, John Dickerson, Seyed A. Esmaeili:
Robust Fair Clustering with Group Membership Uncertainty Sets. CoRR abs/2406.00599 (2024) - [i90]Juan Luque, Sharmila Duppala, John Dickerson, Aravind Srinivasan:
Barter Exchange with Shared Item Valuations. CoRR abs/2406.13983 (2024) - [i89]John Dickerson, Seyed A. Esmaeili, Jamie Morgenstern, Claire Jie Zhang:
Fair Clustering: Critique, Caveats, and Future Directions. CoRR abs/2406.15960 (2024) - [i88]Benjamin Feuer, Micah Goldblum, Teresa Datta, Sanjana Nambiar, Raz Besaleli, Samuel Dooley, Max Cembalest, John P. Dickerson:
Style Outweighs Substance: Failure Modes of LLM Judges in Alignment Benchmarking. CoRR abs/2409.15268 (2024) - 2023
- [j20]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): 4-9 (2023) - [j19]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): 1108-1118 (2023) - [c109]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: 5624-5632 - [c108]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: 9277-9285 - [c107]Christine Herlihy, John P. Dickerson:
Networked Restless Bandits with Positive Externalities. AAAI 2023: 11997-12004 - [c106]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: 229-247 - [c105]Avi Schwarzschild, Max Cembalest, Karthik Rao, Keegan Hines, John P. Dickerson:
Reckoning with the Disagreement Problem: Explanation Consensus as a Training Objective. AIES 2023: 662-678 - [c104]Sahil Verma, Ashudeep Singh, Varich Boonsanong, John P. Dickerson, Chirag Shah:
RecRec: Algorithmic Recourse for Recommender Systems. CIKM 2023: 4325-4329 - [c103]Marina Knittel, Max Springer, John P. Dickerson, MohammadTaghi Hajiaghayi:
Generalized Reductions: Making any Hierarchical Clustering Fair and Balanced with Low Cost. ICML 2023: 17218-17242 - [c102]Sharmila Duppala, Juan Luque, John P. Dickerson, Aravind Srinivasan:
Group Fairness in Set Packing Problems. IJCAI 2023: 391-399 - [c101]Michael J. Curry, Tuomas Sandholm, John P. Dickerson:
Differentiable Economics for Randomized Affine Maximizer Auctions. IJCAI 2023: 2633-2641 - [c100]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: 958-972 - [c99]Christine Herlihy, Aviva Prins, Aravind Srinivasan, John P. Dickerson:
Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting. KDD 2023: 732-740 - [c98]John P. Dickerson, Seyed A. Esmaeili, Jamie H. Morgenstern, Claire Jie Zhang:
Doubly Constrained Fair Clustering. NeurIPS 2023 - [c97]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 - [c96]Marina Knittel, Max Springer, John P. Dickerson, MohammadTaghi Hajiaghayi:
Fair, Polylog-Approximate Low-Cost Hierarchical Clustering. NeurIPS 2023 - [c95]Vedant Nanda, Till Speicher, John P. Dickerson, Krishna P. Gummadi, Soheil Feizi, Adrian Weller:
Diffused Redundancy in Pre-trained Representations. NeurIPS 2023 - [c94]Ryan Sullivan, Akarsh Kumar, Shengyi Huang, John P. Dickerson, Joseph Suarez:
Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks. NeurIPS 2023 - [c93]Teresa Datta, Daniel Nissani, Max Cembalest, Akash Khanna, Haley Massa, John Dickerson:
Tensions Between the Proxies of Human Values in AI. SaTML 2023: 678-689 - [i87]Alex Stein, Avi Schwarzschild, Michael J. Curry, Tom Goldstein, John P. Dickerson:
Neural Auctions Compromise Bidder Information. CoRR abs/2303.00116 (2023) - [i86]Teresa Datta, John P. Dickerson:
Who's Thinking? A Push for Human-Centered Evaluation of LLMs using the XAI Playbook. CoRR abs/2303.06223 (2023) - [i85]Avi Schwarzschild, Max Cembalest, Karthik Rao, Keegan Hines, John P. Dickerson:
Reckoning with the Disagreement Problem: Explanation Consensus as a Training Objective. CoRR abs/2303.13299 (2023) - [i84]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 abs/2304.04677 (2023) - [i83]John P. Dickerson, Seyed A. Esmaeili, Jamie Morgenstern, Claire Jie Zhang:
Doubly Constrained Fair Clustering. CoRR abs/2305.19475 (2023) - [i82]Vedant Nanda, Till Speicher, John P. Dickerson, Soheil Feizi, Krishna P. Gummadi, Adrian Weller:
Diffused Redundancy in Pre-trained Representations. CoRR abs/2306.00183 (2023) - [i81]Sahil Verma, Ashudeep Singh, Varich Boonsanong, John P. Dickerson, Chirag Shah:
RecRec: Algorithmic Recourse for Recommender Systems. CoRR abs/2308.14916 (2023) - [i80]Ryan Sullivan, Akarsh Kumar, Shengyi Huang, John P. Dickerson, Joseph Suarez:
Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks. CoRR abs/2310.17805 (2023) - [i79]Marina Knittel, Max Springer, John P. Dickerson, MohammadTaghi Hajiaghayi:
Fair Polylog-Approximate Low-Cost Hierarchical Clustering. CoRR abs/2311.12501 (2023) - [i78]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 abs/2311.14948 (2023) - 2022
- [j18]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): 4-7 (2022) - [j17]Stephanie Allen, Steven A. Gabriel, John P. Dickerson:
Using inverse optimization to learn cost functions in generalized Nash games. Comput. Oper. Res. 142: 105721 (2022) - [c92]Sahil Verma, Keegan Hines, John P. Dickerson:
Amortized Generation of Sequential Algorithmic Recourses for Black-Box Models. AAAI 2022: 8512-8519 - [c91]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: 357-368 - [c90]Michael J. Curry, Uro Lyi, Tom Goldstein, John P. Dickerson:
Learning Revenue-Maximizing Auctions With Differentiable Matching. AISTATS 2022: 6062-6073 - [c89]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: 6387-6408 - [c88]Candice Schumann, Zhi Lang, Nicholas Mattei, John P. Dickerson:
Group Fairness in Bandits with Biased Feedback. AAMAS 2022: 1155-1163 - [c87]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: 1583-1585 - [c86]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: 622:1-622:21 - [c85]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: 1450-1465 - [c84]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: 16368-16382 - [c83]Ryan Sullivan, Jordan K. Terry, Benjamin Black, John P. Dickerson:
Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments. ICML 2022: 20744-20776 - [c82]Marina Knittel, Samuel Dooley, John P. Dickerson:
The Dichotomous Affiliate Stable Matching Problem: Approval-Based Matching with Applicant-Employer Relations. IJCAI 2022: 356-362 - [c81]Naveen Durvasula, Aravind Srinivasan, John P. Dickerson:
Forecasting Patient Outcomes in Kidney Exchange. IJCAI 2022: 5052-5058 - [c80]Seyed A. Esmaeili, Sharmila Duppala, John P. Dickerson, Brian Brubach:
Fair Labeled Clustering. KDD 2022: 327-335 - [c79]Samuel Dooley, George Z. Wei, Tom Goldstein, John Dickerson:
Robustness Disparities in Face Detection. NeurIPS 2022 - [c78]Duncan C. McElfresh, Sujay Khandagale, Jonathan Valverde, John Dickerson, Colin White:
On the Generalizability and Predictability of Recommender Systems. NeurIPS 2022 - [i77]Seyed A. Esmaeili, Sharmila Duppala, Vedant Nanda, Aravind Srinivasan, John P. Dickerson:
Rawlsian Fairness in Online Bipartite Matching: Two-sided, Group, and Individual. CoRR abs/2201.06021 (2022) - [i76]Michael J. Curry, Tuomas Sandholm, John P. Dickerson:
Differentiable Economics for Randomized Affine Maximizer Auctions. CoRR abs/2202.02872 (2022) - [i75]Marina Knittel, Samuel Dooley, John P. Dickerson:
The Dichotomous Affiliate Stable Matching Problem: Approval-Based Matching with Applicant-Employer Relations. CoRR abs/2202.11095 (2022) - [i74]Kweku Kwegyir-Aggrey, Jessica Dai, John P. Dickerson, Keegan Hines:
Achieving Downstream Fairness with Geometric Repair. CoRR abs/2203.07490 (2022) - [i73]Ryan Sullivan, Justin K. Terry, Benjamin Black, John P. Dickerson:
Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments. CoRR abs/2205.07015 (2022) - [i72]Marina Knittel, John P. Dickerson, MohammadTaghi Hajiaghayi:
Generalized Reductions: Making any Hierarchical Clustering Fair and Balanced with Low Cost. CoRR abs/2205.14198 (2022) - [i71]Seyed A. Esmaeili, Sharmila Duppala, John P. Dickerson, Brian Brubach:
Fair Labeled Clustering. CoRR abs/2205.14358 (2022) - [i70]Duncan C. McElfresh, Sujay Khandagale, Jonathan Valverde, John P. Dickerson, Colin White:
On the Generalizability and Predictability of Recommender Systems. CoRR abs/2206.11886 (2022) - [i69]Vedant Nanda, Till Speicher, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Adrian Weller:
Measuring Representational Robustness of Neural Networks Through Shared Invariances. CoRR abs/2206.11939 (2022) - [i68]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 abs/2207.07972 (2022) - [i67]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 abs/2210.02516 (2022) - [i66]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 abs/2210.09943 (2022) - [i65]Vishnu Dutt Sharma, John P. Dickerson, Pratap Tokekar:
Interpretable Deep Reinforcement Learning for Green Security Games with Real-Time Information. CoRR abs/2211.04987 (2022) - [i64]Samuel Dooley, George Z. Wei, Tom Goldstein, John P. Dickerson:
Robustness Disparities in Face Detection. CoRR abs/2211.15937 (2022) - [i63]Saptarashmi Bandyopadhyay, Chenqi Zhu, Philip Daniel, Joshua Morrison, Ethan Shay, John Dickerson:
Targets in Reinforcement Learning to solve Stackelberg Security Games. CoRR abs/2211.17132 (2022) - [i62]Christine Herlihy, John P. Dickerson:
Networked Restless Bandits with Positive Externalities. CoRR abs/2212.05144 (2022) - [i61]Teresa Datta, Daniel Nissani, Max Cembalest, Akash Khanna, Haley Massa, John P. Dickerson:
Tensions Between the Proxies of Human Values in AI. CoRR abs/2212.07508 (2022) - 2021
- [j16]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): 5-11 (2021) - [j15]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): 13:1-13:17 (2021) - [c77]Haris Aziz, Ágnes Cseh, John P. Dickerson, Duncan C. McElfresh:
Optimal Kidney Exchange with Immunosuppressants. AAAI 2021: 21-29 - [c76]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: 5277-5285 - [c75]Duncan C. McElfresh, Lok Chan, Kenzie Doyle, Walter Sinnott-Armstrong, Vincent Conitzer, Jana Schaich Borg, John P. Dickerson:
Indecision Modeling. AAAI 2021: 5975-5983 - [c74]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: 6822-6830 - [c73]Vedant Nanda, Samuel Dooley, Sahil Singla, Soheil Feizi, John P. Dickerson:
Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning. FAccT 2021: 466-477 - [c72]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 - [c71]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: 9389-9398 - [c70]Naveen Raman, Sanket Shah, John P. Dickerson:
Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling. IJCAI 2021: 363-369 - [c69]Mucong Ding, Kezhi Kong, Jingling Li, Chen Zhu, John Dickerson, Furong Huang, Tom Goldstein:
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization. NeurIPS 2021: 6733-6746 - [c68]Jingling Li, Mozhi Zhang, Keyulu Xu, John Dickerson, Jimmy Ba:
How does a Neural Network's Architecture Impact its Robustness to Noisy Labels? NeurIPS 2021: 9788-9803 - [c67]Seyed A. Esmaeili, Brian Brubach, Aravind Srinivasan, John Dickerson:
Fair Clustering Under a Bounded Cost. NeurIPS 2021: 14345-14357 - [c66]Neehar Peri, Michael J. Curry, Samuel Dooley, John Dickerson:
PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning. NeurIPS 2021: 17532-17542 - [c65]Duncan C. McElfresh, John P. Dickerson, Ke Ren, Hoda Bidkhori:
Distributionally Robust Cycle and Chain Packing With Application To Organ Exchange. WSC 2021: 1-12 - [i60]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 abs/2101.07922 (2021) - [i59]Valeriia Cherepanova, Vedant Nanda, Micah Goldblum, John P. Dickerson, Tom Goldstein:
Technical Challenges for Training Fair Neural Networks. CoRR abs/2102.06764 (2021) - [i58]Stephanie Allen, John P. Dickerson, Steven A. Gabriel:
Using Inverse Optimization to Learn Cost Functions in Generalized Nash Games. CoRR abs/2102.12415 (2021) - [i57]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 abs/2103.02013 (2021) - [i56]Haris Aziz, Ágnes Cseh, John P. Dickerson, Duncan C. McElfresh:
Optimal Kidney Exchange with Immunosuppressants. CoRR abs/2103.02253 (2021) - [i55]Neehar Peri, Michael J. Curry, Samuel Dooley, John P. Dickerson:
PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning. CoRR abs/2106.03215 (2021) - [i54]Sahil Verma, Keegan Hines, John P. Dickerson:
Amortized Generation of Sequential Counterfactual Explanations for Black-box Models. CoRR abs/2106.03962 (2021) - [i53]Darshan Chakrabarti, John P. Dickerson, Seyed A. Esmaeili, Aravind Srinivasan, Leonidas Tsepenekas:
A New Notion of Individually Fair Clustering: α-Equitable k-Center. CoRR abs/2106.05423 (2021) - [i52]Seyed A. Esmaeili, Brian Brubach, Aravind Srinivasan, John P. Dickerson:
Fair Clustering Under a Bounded Cost. CoRR abs/2106.07239 (2021) - [i51]Christine Herlihy, Aviva Prins, Aravind Srinivasan, John Dickerson:
Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting. CoRR abs/2106.07677 (2021) - [i50]Sahil Verma, John P. Dickerson, Keegan Hines:
Counterfactual Explanations for Machine Learning: Challenges Revisited. CoRR abs/2106.07756 (2021) - [i49]Sahil Verma, Aditya Lahiri, John P. Dickerson, Su-In Lee:
Pitfalls of Explainable ML: An Industry Perspective. CoRR abs/2106.07758 (2021) - [i48]Michael J. Curry, Uro Lyi, Tom Goldstein, John Dickerson:
Learning Revenue-Maximizing Auctions With Differentiable Matching. CoRR abs/2106.07877 (2021) - [i47]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 abs/2108.04862 (2021) - [i46]Samuel Dooley, Tom Goldstein, John P. Dickerson:
Robustness Disparities in Commercial Face Detection. CoRR abs/2108.12508 (2021) - [i45]Naveen Raman, Sanket Shah, John Dickerson:
Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling. CoRR abs/2110.03524 (2021) - [i44]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 abs/2110.08396 (2021) - [i43]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 abs/2110.14363 (2021) - [i42]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 abs/2111.14726 (2021) - [i41]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 abs/2112.03179 (2021) - 2020
- [j14]Rachel Freedman, Jana Schaich Borg, Walter Sinnott-Armstrong, John P. Dickerson, Vincent Conitzer:
Adapting a kidney exchange algorithm to align with human values. Artif. Intell. 283: 103261 (2020) - [j13]Michael Albert, John P. Dickerson:
AAAI/ACM SIGAI job fair 2020: a retrospective. AI Matters 6(1): 7-8 (2020) - [j12]Sanmay Das, Nicholas Mattei, John P. Dickerson, Sven Koenig, Louise A. Dennis, Larry R. Medsker, Todd W. Neller, Iolanda Leite, Anuj Karpatne:
SIGAI annual report: July 1 2019 - June 30 2020. AI Matters 6(2): 5-9 (2020) - [j11]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): 16-34 (2020) - [c64]Vedant Nanda, Pan Xu, Karthik Abinav Sankararaman, John P. Dickerson, Aravind Srinivasan:
Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms during High-Demand Hours. AAAI 2020: 2210-2217 - [c63]Ali Shafahi, Mahyar Najibi, Zheng Xu, John P. Dickerson, Larry S. Davis, Tom Goldstein:
Universal Adversarial Training. AAAI 2020: 5636-5643 - [c62]Zeyu Zhao, John P. Dickerson:
Clearing Kidney Exchanges via Graph Neural Network Guided Tree Search (Student Abstract). AAAI 2020: 13989-13990 - [c61]Vedant Nanda, Pan Xu, Karthik Abinav Sankararaman, John P. Dickerson, Aravind Srinivasan:
Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms during High-Demand Hours. AIES 2020: 131 - [c60]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: 152 - [c59]Lok Chan, Kenzie Doyle, Duncan C. McElfresh, Vincent Conitzer, John P. Dickerson, Jana Schaich Borg, Walter Sinnott-Armstrong:
Artificial Artificial Intelligence: Measuring Influence of AI 'Assessments' on Moral Decision-Making. AIES 2020: 214-220 - [c58]Candice Schumann, Jeffrey S. Foster, Nicholas Mattei, John P. Dickerson:
We Need Fairness and Explainability in Algorithmic Hiring. AAMAS 2020: 1716-1720 - [c57]Neehar Peri, Neal Gupta, W. Ronny Huang, Liam Fowl, Chen Zhu, Soheil Feizi, Tom Goldstein, John P. Dickerson:
Deep k-NN Defense Against Clean-Label Data Poisoning Attacks. ECCV Workshops (1) 2020: 55-70 - [c56]Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas:
A Pairwise Fair and Community-preserving Approach to k-Center Clustering. ICML 2020: 1178-1189 - [c55]Debjani Saha, Candice Schumann, Duncan C. McElfresh, John P. Dickerson, Michelle L. Mazurek, Michael Carl Tschantz:
Measuring Non-Expert Comprehension of Machine Learning Fairness Metrics. ICML 2020: 8377-8387 - [c54]Saba Ahmadi, Faez Ahmed, John P. Dickerson, Mark D. Fuge, Samir Khuller:
An Algorithm for Multi-Attribute Diverse Matching. IJCAI 2020: 3-9 - [c53]Ping-yeh Chiang, Michael J. Curry, Ahmed Abdelkader, Aounon Kumar, John Dickerson, Tom Goldstein:
Detection as Regression: Certified Object Detection with Median Smoothing. NeurIPS 2020 - [c52]Michael J. Curry, Ping-Yeh Chiang, Tom Goldstein, John Dickerson:
Certifying Strategyproof Auction Networks. NeurIPS 2020 - [c51]Seyed A. Esmaeili, Brian Brubach, Leonidas Tsepenekas, John Dickerson:
Probabilistic Fair Clustering. NeurIPS 2020 - [c50]Duncan C. McElfresh, Michael J. Curry, Tuomas Sandholm, John Dickerson:
Improving Policy-Constrained Kidney Exchange via Pre-Screening. NeurIPS 2020 - [c49]Duncan C. McElfresh, Christian Kroer, Sergey Pupyrev, Eric Sodomka, Karthik Abinav Sankararaman, Zack Chauvin, Neil Dexter, John P. Dickerson:
Matching Algorithms for Blood Donation. EC 2020: 463-464 - [c48]Hoda Bidkhori, John Dickerson, Duncan C. McElfresh, Ke Ren:
Kidney Exchange with Inhomogeneous Edge Existence Uncertainty. UAI 2020: 161-170 - [i40]Debjani Saha, Candice Schumann, Duncan C. McElfresh, John P. Dickerson, Michelle L. Mazurek, Michael Carl Tschantz:
Human Comprehension of Fairness in Machine Learning. CoRR abs/2001.00089 (2020) - [i39]Duncan C. McElfresh, Samuel Dooley, Yuan Cui, Kendra Griesman, Weiqin Wang, Tyler Will, Neil Sehgal, John P. Dickerson:
Can an Algorithm be My Healthcare Proxy? CoRR abs/2001.09742 (2020) - [i38]Lok Chan, Kenzie Doyle, Duncan C. McElfresh, Vincent Conitzer, John P. Dickerson, Jana Schaich Borg, Walter Sinnott-Armstrong:
Artificial Artificial Intelligence: Measuring Influence of AI 'Assessments' on Moral Decision-Making. CoRR abs/2001.09766 (2020) - [i37]Faez Ahmed, John Dickerson, Mark D. Fuge:
Forming Diverse Teams from Sequentially Arriving People. CoRR abs/2002.10697 (2020) - [i36]Phebe Vayanos, Duncan C. McElfresh, Yingxiao Ye, John Paul Dickerson, Eric Rice:
Active Preference Elicitation via Adjustable Robust Optimization. CoRR abs/2003.01899 (2020) - [i35]Rachel Freedman, Jana Schaich Borg, Walter Sinnott-Armstrong, John P. Dickerson, Vincent Conitzer:
Adapting a Kidney Exchange Algorithm to Align with Human Values. CoRR abs/2005.09755 (2020) - [i34]Michael J. Curry, Ping-Yeh Chiang, Tom Goldstein, John P. Dickerson:
Certifying Strategyproof Auction Networks. CoRR abs/2006.08742 (2020) - [i33]Seyed A. Esmaeili, Brian Brubach, Leonidas Tsepenekas, John P. Dickerson:
Probabilistic Fair Clustering. CoRR abs/2006.10916 (2020) - [i32]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. CoRR abs/2006.12557 (2020) - [i31]Vedant Nanda, Samuel Dooley, Sahil Singla, Soheil Feizi, John P. Dickerson:
Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning. CoRR abs/2006.12621 (2020) - [i30]Vedant Nanda, Till Speicher, John P. Dickerson, Krishna P. Gummadi, Muhammad Bilal Zafar:
Unifying Model Explainability and Robustness via Machine-Checkable Concepts. CoRR abs/2007.00251 (2020) - [i29]Hoda Bidkhori, John P. Dickerson, Duncan C. McElfresh, Ke Ren:
Kidney Exchange with Inhomogeneous Edge Existence Uncertainty. CoRR abs/2007.03191 (2020) - [i28]Ping-yeh Chiang, Michael J. Curry, Ahmed Abdelkader, Aounon Kumar, John P. Dickerson, Tom Goldstein:
Detection as Regression: Certified Object Detection by Median Smoothing. CoRR abs/2007.03730 (2020) - [i27]Brian Brubach, Darshan Chakrabarti, John P. Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas:
A Pairwise Fair and Community-preserving Approach to k-Center Clustering. CoRR abs/2007.07384 (2020) - [i26]Samuel Dooley, John P. Dickerson:
The Affiliate Matching Problem: On Labor Markets where Firms are Also Interested in the Placement of Previous Workers. CoRR abs/2009.11867 (2020) - [i25]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 abs/2010.06398 (2020) - [i24]Sahil Verma, John P. Dickerson, Keegan Hines:
Counterfactual Explanations for Machine Learning: A Review. CoRR abs/2010.10596 (2020) - [i23]Duncan C. McElfresh, Michael J. Curry, Tuomas Sandholm, John P. Dickerson:
Improving Policy-Constrained Kidney Exchange via Pre-Screening. CoRR abs/2010.12069 (2020) - [i22]Duncan C. McElfresh, Lok Chan, Kenzie Doyle, Walter Sinnott-Armstrong, Vincent Conitzer, Jana Schaich Borg, John P. Dickerson:
Indecision Modeling. CoRR abs/2012.08485 (2020) - [i21]Jingling Li, Mozhi Zhang, Keyulu Xu, John P. Dickerson, Jimmy Ba:
Noisy Labels Can Induce Good Representations. CoRR abs/2012.12896 (2020)
2010 – 2019
- 2019
- [j10]Christopher Amato, John P. Dickerson:
AAAI/ACM SIGAI job fair 2019: a retrospective. AI Matters 5(1): 5-6 (2019) - [j9]Sven Koenig, Sanmay Das, Rosemary D. Paradis, John P. Dickerson, Yolanda Gil, Katherine Guo, Benjamin Kuipers, Iolanda Leite, Hang Ma, Nicholas Mattei, Amy McGovern, Larry R. Medsker, Todd W. Neller, Marion Neumann, Plamen Petrov, Michael Rovatsos, David G. Stork:
ACM SIGAI activity report. AI Matters 5(3): 6-11 (2019) - [j8]John P. Dickerson, Ariel D. Procaccia, Tuomas Sandholm:
Failure-Aware Kidney Exchange. Manag. Sci. 65(4): 1768-1791 (2019) - [c47]Duncan C. McElfresh, Hoda Bidkhori, John P. Dickerson:
Scalable Robust Kidney Exchange. AAAI 2019: 1077-1084 - [c46]John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu:
Balancing Relevance and Diversity in Online Bipartite Matching via Submodularity. AAAI 2019: 1877-1884 - [c45]Pan Xu, Yexuan Shi, Hao Cheng, John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Yongxin Tong, Leonidas Tsepenekas:
A Unified Approach to Online Matching with Conflict-Aware Constraints. AAAI 2019: 2221-2228 - [c44]Candice Schumann, Samsara N. Counts, Jeffrey S. Foster, John P. Dickerson:
The Diverse Cohort Selection Problem. AAMAS 2019: 601-609 - [c43]John P. Dickerson, Karthik Abinav Sankararaman, Kanthi Kiran Sarpatwar, Aravind Srinivasan, Kun-Lung Wu, Pan Xu:
Online Resource Allocation with Matching Constraints. AAMAS 2019: 1681-1689 - [c42]Ali Shafahi, Amin Ghiasi, Mahyar Najibi, Furong Huang, John P. Dickerson, Tom Goldstein:
Batch-wise Logit-Similarity: Generalizing Logit-Squeezing and Label-Smoothing. BMVC 2019: 72 - [c41]Ali Shafahi, Mahyar Najibi, Amin Ghiasi, Zheng Xu, John P. Dickerson, Christoph Studer, Larry S. Davis, Gavin Taylor, Tom Goldstein:
Adversarial training for free! NeurIPS 2019: 3353-3364 - [c40]Candice Schumann, Zhi Lang, Jeffrey S. Foster, John P. Dickerson:
Making the Cut: A Bandit-based Approach to Tiered Interviewing. NeurIPS 2019: 4641-4651 - [c39]Michael J. Curry, John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Yuhao Wan, Pan Xu:
Mix and Match: Markov Chains and Mixing Times for Matching in Rideshare. WINE 2019: 129-141 - [i20]Ali Shafahi, Mahyar Najibi, Amin Ghiasi, Zheng Xu, John P. Dickerson, Christoph Studer, Larry S. Davis, Gavin Taylor, Tom Goldstein:
Adversarial Training for Free! CoRR abs/1904.12843 (2019) - [i19]Candice Schumann, Zhi Lang, Jeffrey S. Foster, John P. Dickerson:
Making the Cut: A Bandit-based Approach to Tiered Interviewing. CoRR abs/1906.09621 (2019) - [i18]Saba Ahmadi, Faez Ahmed, John P. Dickerson, Mark D. Fuge, Samir Khuller:
Algorithms for Optimal Diverse Matching. CoRR abs/1909.03350 (2019) - [i17]Neal Gupta, W. Ronny Huang, Liam Fowl, Chen Zhu, Soheil Feizi, Tom Goldstein, John P. Dickerson:
Strong Baseline Defenses Against Clean-Label Poisoning Attacks. CoRR abs/1909.13374 (2019) - [i16]Michael J. Curry, John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Yuhao Wan, Pan Xu:
Mix and Match: Markov Chains & Mixing Times for Matching in Rideshare. CoRR abs/1912.00225 (2019) - [i15]Candice Schumann, Zhi Lang, Nicholas Mattei, John P. Dickerson:
Group Fairness in Bandit Arm Selection. CoRR abs/1912.03802 (2019) - [i14]Vedant Nanda, Pan Xu, Karthik Abinav Sankararaman, John P. Dickerson, Aravind Srinivasan:
Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms During High-Demand Hours. CoRR abs/1912.08388 (2019) - 2018
- [j7]John P. Dickerson, Nicholas Mattei:
AAAI/ACM SIGAI job fair 2018: a retrospective. AI Matters 4(1): 5-6 (2018) - [j6]Sven Koenig, Sanmay Das, Rosemary D. Paradis, John P. Dickerson, Yolanda Gil, Katherine Guo, Benjamin Kuipers, Hang Ma, Nicholas Mattei, Amy McGovern, Larry R. Medsker, Todd W. Neller, Plamen Petrov, Michael Rovatsos, David G. Stork:
ACM SIGAI activity report. AI Matters 4(3): 7-11 (2018) - [c38]Duncan C. McElfresh, John P. Dickerson:
Balancing Lexicographic Fairness and a Utilitarian Objective with Application to Kidney Exchange. AAAI Workshops 2018: 487-494 - [c37]John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu:
Allocation Problems in Ride-Sharing Platforms: Online Matching With Offline Reusable Resources. AAAI 2018: 1007-1014 - [c36]Duncan C. McElfresh, John P. Dickerson:
Balancing Lexicographic Fairness and a Utilitarian Objective With Application to Kidney Exchange. AAAI 2018: 1161-1168 - [c35]Rachel Freedman, Jana Schaich Borg, Walter Sinnott-Armstrong, John P. Dickerson, Vincent Conitzer:
Adapting a Kidney Exchange Algorithm to Align With Human Values. AAAI 2018: 1636-1643 - [c34]Duncan C. McElfresh, John P. Dickerson:
Balancing Lexicographic Fairness and a Utilitarian Objective With Application to Kidney Exchange. AAAI 2018: 8119-8120 - [c33]Rachel Freedman, Jana Schaich Borg, Walter Sinnott-Armstrong, John P. Dickerson, Vincent Conitzer:
Adapting a Kidney Exchange Algorithm to Align with Human Values. AIES 2018: 115 - [c32]John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu:
Assigning Tasks to Workers based on Historical Data: Online Task Assignment with Two-sided Arrivals. AAMAS 2018: 318-326 - [c31]Elissa M. Redmiles, John P. Dickerson, Krishna P. Gummadi, Michelle L. Mazurek:
Equitable Security: Optimizing Distribution of Nudges and Resources. CCS 2018: 2270-2272 - [c30]Guangqi Cui, John P. Dickerson, Naveen Durvasula, William Gasarch, Erik Metz, Jacob Prinz, Naveen Raman, Daniel Smolyak, Sung Hyun Yoo:
A Muffin-Theorem Generator. FUN 2018: 15:1-15:19 - [c29]Zhuoshu Li, Neal Gupta, Sanmay Das, John P. Dickerson:
Equilibrium Behavior in Competing Dynamic Matching Markets. IJCAI 2018: 389-395 - [c28]Elissa M. Redmiles, Michelle L. Mazurek, John P. Dickerson:
Dancing Pigs or Externalities?: Measuring the Rationality of Security Decisions. EC 2018: 215-232 - [i13]Elissa M. Redmiles, Michelle L. Mazurek, John P. Dickerson:
Dancing Pigs or Externalities? Measuring the Rationality of Security Decisions. CoRR abs/1805.06542 (2018) - [i12]Duncan C. McElfresh, Hoda Bidkhori, John P. Dickerson:
Scalable Robust Kidney Exchange. CoRR abs/1811.03532 (2018) - [i11]John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu:
Balancing Relevance and Diversity in Online Bipartite Matching via Submodularity. CoRR abs/1811.05100 (2018) - [i10]Ali Shafahi, Mahyar Najibi, Zheng Xu, John P. Dickerson, Larry S. Davis, Tom Goldstein:
Universal Adversarial Training. CoRR abs/1811.11304 (2018) - 2017
- [j5]John P. Dickerson, Tuomas Sandholm:
Multi-Organ Exchange. J. Artif. Intell. Res. 60: 639-679 (2017) - [c27]John P. Dickerson, Aleksandr M. Kazachkov, Ariel D. Procaccia, Tuomas Sandholm:
Small Representations of Big Kidney Exchange Graphs. AAAI 2017: 487-493 - [c26]John P. Dickerson, Aleksandr M. Kazachkov, Ariel D. Procaccia, Tuomas Sandholm:
Small Representations of Big Kidney Exchange Graphs. AAAI Workshops 2017 - [c25]Gabriele Farina, John P. Dickerson, Tuomas Sandholm:
Inter-Club Kidney Exchange. AAAI Workshops 2017 - [c24]Faez Ahmed, John P. Dickerson, Mark D. Fuge:
Diverse Weighted Bipartite b-Matching. IJCAI 2017: 35-41 - [c23]Gabriele Farina, John P. Dickerson, Tuomas Sandholm:
Operation Frames and Clubs in Kidney Exchange. IJCAI 2017: 199-205 - [i9]Faez Ahmed, John P. Dickerson, Mark D. Fuge:
Diverse Weighted Bipartite b-Matching. CoRR abs/1702.07134 (2017) - [i8]Duncan C. McElfresh, John P. Dickerson:
Balancing Lexicographic Fairness and a Utilitarian Objective with Application to Kidney Exchange. CoRR abs/1702.08286 (2017) - [i7]Gabriele Farina, John P. Dickerson, Tuomas Sandholm:
Operation Frames and Clubs in Kidney Exchange. CoRR abs/1705.09328 (2017) - [i6]Hanan Rosemarin, John P. Dickerson, Sarit Kraus:
Learning to Schedule Deadline- and Operator-Sensitive Tasks. CoRR abs/1706.06051 (2017) - [i5]Candice Schumann, Samsara N. Counts, Jeffrey S. Foster, John P. Dickerson:
The Diverse Cohort Selection Problem: Multi-Armed Bandits with Varied Pulls. CoRR abs/1709.03441 (2017) - [i4]John P. Dickerson, Karthik Abinav Sankararaman, Aravind Srinivasan, Pan Xu:
Allocation Problems in Ride-Sharing Platforms: Online Matching with Offline Reusable Resources. CoRR abs/1711.08345 (2017) - 2016
- [c22]Benjamin Plaut, John P. Dickerson, Tuomas Sandholm:
Fast Optimal Clearing of Capped-Chain Barter Exchanges. AAAI 2016: 601-607 - [c21]John P. Dickerson, David F. Manlove, Benjamin Plaut, Tuomas Sandholm, James Trimble:
Position-Indexed Formulations for Kidney Exchange. EC 2016: 25-42 - [i3]John P. Dickerson, Aleksandr M. Kazachkov, Ariel D. Procaccia, Tuomas Sandholm:
Small Representations of Big Kidney Exchange Graphs. CoRR abs/1605.07728 (2016) - [i2]Benjamin Plaut, John P. Dickerson, Tuomas Sandholm:
Hardness of the Pricing Problem for Chains in Barter Exchanges. CoRR abs/1606.00117 (2016) - [i1]John P. Dickerson, David F. Manlove, Benjamin Plaut, Tuomas Sandholm, James Trimble:
Position-Indexed Formulations for Kidney Exchange. CoRR abs/1606.01623 (2016) - 2015
- [j4]Anshul Sawant, John P. Dickerson, Mohammad Taghi Hajiaghayi, V. S. Subrahmanian:
Automated Generation of Counterterrorism Policies Using Multiexpert Input. ACM Trans. Intell. Syst. Technol. 6(4): 44:1-44:27 (2015) - [c20]John P. Dickerson, Tuomas Sandholm:
FutureMatch: Combining Human Value Judgments and Machine Learning to Match in Dynamic Environments. AAAI 2015: 622-628 - [c19]Chen Hajaj, John P. Dickerson, Avinatan Hassidim, Tuomas Sandholm, David Sarne:
Strategy-Proof and Efficient Kidney Exchange Using a Credit Mechanism. AAAI 2015: 921-928 - [c18]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. EC 2015: 325-342 - 2014
- [c17]John P. Dickerson, Jonathan R. Goldman, Jeremy Karp, Ariel D. Procaccia, Tuomas Sandholm:
The Computational Rise and Fall of Fairness. AAAI 2014: 1405-1411 - [c16]John P. Dickerson, Tuomas Sandholm:
Multi-Organ Exchange: The Whole Is Greater than the Sum of its Parts. AAAI 2014: 1412-1418 - [c15]John Paul Dickerson, Tuomas Sandholm:
Balancing Efficiency and Fairness in Dynamic Kidney Exchange. AAAI Workshop: Modern Artificial Intelligence for Health Analytics 2014 - [c14]John P. Dickerson, Vadim Kagan, V. S. Subrahmanian:
Using sentiment to detect bots on Twitter: Are humans more opinionated than bots? ASONAM 2014: 620-627 - [c13]John P. Dickerson, Ariel D. Procaccia, Tuomas Sandholm:
Price of fairness in kidney exchange. AAMAS 2014: 1013-1020 - [c12]John P. Dickerson:
Robust dynamic optimization with application to kidney exchange. AAMAS 2014: 1701-1702 - [c11]Lucy Erickson, Erik D. Thiessen, Karrie E. Godwin, John P. Dickerson, Anna V. Fisher:
Endogenously- but not Exogenously-driven Selective Sustained Attention is Related to Learning in a Classroom-like Setting in Kindergarten Children. CogSci 2014 - [c10]Steven Banaszak, Elizabeth K. Bowman, John P. Dickerson, V. S. Subrahmanian:
Forecasting Country Stability in North Africa. JISIC 2014: 304-307 - 2013
- [j3]Gerardo I. Simari, John P. Dickerson, Amy Sliva, V. S. Subrahmanian:
Parallel Abductive Query Answering in Probabilistic Logic Programs. ACM Trans. Comput. Log. 14(2): 12:1-12:39 (2013) - [c9]John Paul Dickerson, Tuomas Sandholm:
Throwing Darts: Random Sampling Helps Tree Search when the Number of Short Certificates is Moderate. AAAI (Late-Breaking Developments) 2013 - [c8]John P. Dickerson, Anshul Sawant, Mohammad Taghi Hajiaghayi, V. S. Subrahmanian:
PREVE: a policy recommendation engine based on vector equilibria applied to reducing LeT's attacks. ASONAM 2013: 1084-1091 - [c7]John P. Dickerson, Ariel D. Procaccia, Tuomas Sandholm:
Failure-aware kidney exchange. EC 2013: 323-340 - [c6]John Paul Dickerson, Tuomas Sandholm:
Throwing Darts: Random Sampling Helps Tree Search when the Number of Short Certificates Is Moderate. SOCS 2013: 55-62 - 2012
- [j2]Robert Patro, John P. Dickerson, Sujal Bista, Satyandra K. Gupta, Amitabh Varshney:
Speeding Up Particle Trajectory Simulations Under Moving Force Fields using Graphic Processing Units. J. Comput. Inf. Sci. Eng. 12(2) (2012) - [j1]Paulo Shakarian, John P. Dickerson, V. S. Subrahmanian:
Adversarial Geospatial Abduction Problems. ACM Trans. Intell. Syst. Technol. 3(2): 34:1-34:35 (2012) - [c5]John P. Dickerson, Ariel D. Procaccia, Tuomas Sandholm:
Dynamic Matching via Weighted Myopia with Application to Kidney Exchange. AAAI 2012: 1340-1346 - [c4]John P. Dickerson, Ariel D. Procaccia, Tuomas Sandholm:
Optimizing kidney exchange with transplant chains: theory and reality. AAMAS 2012: 711-718 - 2011
- [c3]John P. Dickerson, Aaron Mannes, V. S. Subrahmanian:
Dealing with Lashkar-e-Taiba: A Multi-player Game-Theoretic Perspective. EISIC 2011: 354-359 - 2010
- [c2]John P. Dickerson, Gerardo I. Simari, V. S. Subrahmanian, Sarit Kraus:
A graph-theoretic approach to protect static and moving targets from adversaries. AAMAS 2010: 299-306 - [c1]Gerardo I. Simari, John P. Dickerson, V. S. Subrahmanian:
Cost-Based Query Answering in Action Probabilistic Logic Programs. SUM 2010: 319-332
Coauthor Index
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