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- affiliation: Harvard University, School of Engineering and Applied Science
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2020 – today
- 2023
[c189]Jamelle Watson-Daniels, David C. Parkes, Berk Ustun
:
Predictive Multiplicity in Probabilistic Classification. AAAI 2023: 10306-10314- [c188]Zhun Deng, He Sun, Steven Wu, Linjun Zhang, David C. Parkes:
Reinforcement Learning with Stepwise Fairness Constraints. AISTATS 2023: 10594-10618 - [c187]Matthias Gerstgrasser, David C. Parkes:
Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning. ICML 2023: 11213-11236 - [c186]Yaniv Yacoby, John Girash, David C. Parkes:
Empowering First-Year Computer Science Ph.D. Students to Create a Culture that Values Community and Mental Health. SIGCSE (1) 2023: 694-700 - [c185]Matheus Venturyne Xavier Ferreira, David C. Parkes:
Credible Decentralized Exchange Design via Verifiable Sequencing Rules. STOC 2023: 723-736 - [c184]Xintong Wang, Gary Qiurui Ma, Alon Eden, Clara Li, Alexander Trott, Stephan Zheng, David C. Parkes:
Platform Behavior under Market Shocks: A Simulation Framework and Reinforcement-Learning Based Study. WWW 2023: 3592-3602 - [i79]Denizalp Goktas, David C. Parkes, Ian Gemp, Luke Marris, Georgios Piliouras, Romuald Elie, Guy Lever, Andrea Tacchetti:
Generative Adversarial Equilibrium Solvers. CoRR abs/2302.06607 (2023) - [i78]Manuel Wuthrich, Mark York, David C. Parkes:
Eliciting Information from participants with Competing Incentives and Dependent Beliefs. CoRR abs/2302.14122 (2023) - [i77]Omer Nahum, Gali Noti, David C. Parkes, Nir Rosenfeld:
Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces. CoRR abs/2306.10606 (2023) - [i76]Tonghan Wang, Paul Dütting, Dmitry Ivanov, Inbal Talgam-Cohen, David C. Parkes:
Deep Contract Design via Discontinuous Piecewise Affine Neural Networks. CoRR abs/2307.02318 (2023) - [i75]Sara Fish, Paul Gölz, David C. Parkes, Ariel D. Procaccia, Gili Rusak, Itai Shapira, Manuel Wüthrich:
Generative Social Choice. CoRR abs/2309.01291 (2023) - [i74]Hugh Zhang, David C. Parkes:
Chain-of-Thought Reasoning is a Policy Improvement Operator. CoRR abs/2309.08589 (2023) - [i73]Alon Eden, Gary Qiurui Ma, David C. Parkes:
Platform Equilibrium: Analayzing Social Welfare in Online Market Places. CoRR abs/2309.08781 (2023) - 2022
- [j53]Hongyao Ma, Fei Fang, David C. Parkes:
Spatio-Temporal Pricing for Ridesharing Platforms. Oper. Res. 70(2): 1025-1041 (2022) - [j52]Rediet Abebe, T.-H. Hubert Chan, Jon M. Kleinberg, Zhibin Liang, David C. Parkes, Mauro Sozio, Charalampos E. Tsourakakis:
Opinion Dynamics Optimization by Varying Susceptibility to Persuasion via Non-Convex Local Search. ACM Trans. Knowl. Discov. Data 16(2): 33:1-33:34 (2022) - [c183]Mira Finkelstein, Lucy Liu, Yoav Kolumbus, David C. Parkes, Jeffrey S. Rosenshein, Sarah Keren:
Reinforcement Learning Explainability via Model Transforms (Student Abstract). AAAI 2022: 12943-12944 - [c182]Zhou Fan, Francisco J. Marmolejo Cossío, Ben Altschuler, He Sun, Xintong Wang, David C. Parkes:
Differential Liquidity Provision in Uniswap v3 and Implications for Contract Design✱. ICAIF 2022: 9-17 - [c181]Matthias Gerstgrasser, Rakshit Trivedi, David C. Parkes:
CrowdPlay: Crowdsourcing Human Demonstrations for Offline Learning. ICLR 2022 - [c180]Gianluca Brero, Eric Mibuari, Nicolas Lepore, David C. Parkes:
Learning to Mitigate AI Collusion on Economic Platforms. NeurIPS 2022 - [c179]Mira Finkelstein, Nitsan Levy Schlot, Lucy Liu, Yoav Kolumbus, David C. Parkes, Jeffrey S. Rosenschein, Sarah Keren:
Explainable Reinforcement Learning via Model Transforms. NeurIPS 2022 - [p1]Rose E. Wang, Sarah A. Wu, James A. Evans, David C. Parkes, Joshua B. Tenenbaum, Max Kleiman-Weiner:
Too Many cooks: Bayesian inference for coordinating Multi-agent Collaboration. Human-Like Machine Intelligence 2022: 152-170 - [i72]Gianluca Brero, Nicolas Lepore, Eric Mibuari, David C. Parkes:
Learning to Mitigate AI Collusion on Economic Platforms. CoRR abs/2202.07106 (2022) - [i71]Xintong Wang, Gary Qiurui Ma, Alon Eden, Clara Li, Alexander Trott, Stephan Zheng, David C. Parkes:
Using Reinforcement Learning to Study Platform Economies under Market Shocks. CoRR abs/2203.13395 (2022) - [i70]Zhou Fan, Francisco J. Marmolejo Cossío, Ben Altschuler, He Sun, Xintong Wang, David C. Parkes:
Differential Liquidity Provision in Uniswap v3 and Implications for Contract Design. CoRR abs/2204.00464 (2022) - [i69]Jamelle Watson-Daniels, David C. Parkes, Berk Ustun:
Predictive Multiplicity in Probabilistic Classification. CoRR abs/2206.01131 (2022) - [i68]Yaniv Yacoby, John Girash, David C. Parkes:
Empowering First-Year Computer Science Ph.D. Students to Create a Culture that Values Community and Mental Health. CoRR abs/2208.12650 (2022) - [i67]Mira Finkelstein, Lucy Liu, Nitsan Levy Schlot, Yoav Kolumbus, David C. Parkes, Jeffrey S. Rosenshein, Sarah Keren:
Explainable Reinforcement Learning via Model Transforms. CoRR abs/2209.12006 (2022) - [i66]Matheus V. X. Ferreira, David C. Parkes:
Credible Decentralized Exchange Design via Verifiable Sequencing Rules. CoRR abs/2209.15569 (2022) - [i65]Gianluca Brero, Alon Eden, Darshan Chakrabarti, Matthias Gerstgrasser, Vincent Li, David C. Parkes:
Learning Stackelberg Equilibria and Applications to Economic Design Games. CoRR abs/2210.03852 (2022) - [i64]Matthias Gerstgrasser, David C. Parkes:
Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning. CoRR abs/2210.11942 (2022) - [i63]Zhun Deng, He Sun, Zhiwei Steven Wu, Linjun Zhang, David C. Parkes:
Reinforcement Learning with Stepwise Fairness Constraints. CoRR abs/2211.03994 (2022) - [i62]Peter Stone, Rodney Brooks, Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram Kalyanakrishnan, Ece Kamar, Sarit Kraus, Kevin Leyton-Brown, David C. Parkes, William H. Press, AnnaLee Saxenian, Julie Shah, Milind Tambe, Astro Teller:
Artificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence. CoRR abs/2211.06318 (2022) - 2021
- [j51]Paul Dütting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes, Sai Srivatsa Ravindranath:
Optimal auctions through deep learning. Commun. ACM 64(8): 109-116 (2021) - [j50]David C. Parkes:
Playing with symmetry with neural networks. Nat. Mach. Intell. 3(8): 658 (2021) - [j49]Sarah A. Wu, Rose E. Wang, James A. Evans, Joshua B. Tenenbaum, David C. Parkes, Max Kleiman-Weiner:
Too Many Cooks: Bayesian Inference for Coordinating Multi-Agent Collaboration. Top. Cogn. Sci. 13(2): 414-432 (2021) - [c178]Gianluca Brero, Alon Eden, Matthias Gerstgrasser, David C. Parkes, Duncan Rheingans-Yoo:
Reinforcement Learning of Sequential Price Mechanisms. AAAI 2021: 5219-5227 - [c177]Matheus V. X. Ferreira, Daniel J. Moroz, David C. Parkes, Mitchell Stern:
Dynamic posted-price mechanisms for the blockchain transaction-fee market. AFT 2021: 86-99 - [c176]Paul Tylkin, Goran Radanovic, David C. Parkes:
Learning Robust Helpful Behaviors in Two-Player Cooperative Atari Environments. AAMAS 2021: 1686-1688 - [c175]Sophie Hilgard, Nir Rosenfeld, Mahzarin R. Banaji, Jack Cao, David C. Parkes:
Learning Representations by Humans, for Humans. ICML 2021: 4227-4238 - [c174]Matheus V. X. Ferreira, Daniel J. Moroz, David C. Parkes, Mitchell Stern:
Dynamic Posted-Price Mechanisms for the Blockchain Transaction Fee Market (Invited Talk). Tokenomics 2021: 6:1-6:1 - [c173]Vincent Conitzer, Zhe Feng, David C. Parkes, Eric Sodomka:
Welfare-Preserving ε-BIC to BIC Transformation with Negligible Revenue Loss. WINE 2021: 76-94 - [c172]Mark York, Munther A. Dahleh, David C. Parkes:
Eliciting Social Knowledge for Creditworthiness Assessment. WINE 2021: 428-445 - [i61]Michael Neuder, Daniel J. Moroz, Rithvik Rao, David C. Parkes:
Low-cost attacks on Ethereum 2.0 by sub-1/3 stakeholders. CoRR abs/2102.02247 (2021) - [i60]Matheus V. X. Ferreira, Daniel J. Moroz, David C. Parkes, Mitchell Stern:
Dynamic Posted-Price Mechanisms for the Blockchain Transaction-Fee Market. CoRR abs/2103.14144 (2021) - [i59]Michael Neuder, Rithvik Rao, Daniel J. Moroz, David C. Parkes:
Strategic Liquidity Provision in Uniswap v3. CoRR abs/2106.12033 (2021) - [i58]Sai Srivatsa Ravindranath, Zhe Feng, Shira Li, Jonathan Ma, Scott Duke Kominers, David C. Parkes:
Deep Learning for Two-Sided Matching. CoRR abs/2107.03427 (2021) - [i57]Stephan Zheng, Alexander Trott, Sunil Srinivasa, David C. Parkes, Richard Socher:
The AI Economist: Optimal Economic Policy Design via Two-level Deep Reinforcement Learning. CoRR abs/2108.02755 (2021) - [i56]Mark York, Munther A. Dahleh, David C. Parkes:
Eliciting Social Knowledge for Creditworthiness Assessment. CoRR abs/2108.09289 (2021) - 2020
- [j48]Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu:
How do fairness definitions fare? Testing public attitudes towards three algorithmic definitions of fairness in loan allocations. Artif. Intell. 283: 103238 (2020) - [j47]Haris Aziz, Hau Chan, Barton E. Lee, David C. Parkes:
The capacity constrained facility location problem. Games Econ. Behav. 124: 478-490 (2020) - [j46]Hongyao Ma, Fei Fang, David C. Parkes:
Spatio-temporal pricing for ridesharing platforms. SIGecom Exch. 18(2): 53-57 (2020) - [j45]Arpit Agarwal, Debmalya Mandal, David C. Parkes, Nisarg Shah:
Peer Prediction with Heterogeneous Users. ACM Trans. Economics and Comput. 8(1): 2:1-2:34 (2020) - [j44]Malvika Rao, David F. Bacon, David C. Parkes, Margo I. Seltzer:
Incentivizing Deep Fixes in Software Economies. IEEE Trans. Software Eng. 46(1): 51-70 (2020) - [c171]Debmalya Mandal, Goran Radanovic, David C. Parkes:
The Effectiveness of Peer Prediction in Long-Term Forecasting. AAAI 2020: 2160-2167 - [c170]Sarah Keren, Haifeng Xu, Kofi Kwapong, David C. Parkes, Barbara J. Grosz:
Information Shaping for Enhanced Goal Recognition of Partially-Informed Agents. AAAI 2020: 9908-9915 - [c169]Michael Neuder, Daniel J. Moroz, Rithvik Rao, David C. Parkes:
Defending Against Malicious Reorgs in Tezos Proof-of-Stake. AFT 2020: 46-58 - [c168]Hongyao Ma, Reshef Meir, David C. Parkes, Elena Wu-Yan:
Penalty Bidding Mechanisms for Allocating Resources and Overcoming Present-Bias. AAMAS 2020: 807-815 - [c167]Hau Chan, David C. Parkes, Karim R. Lakhani:
The Price of Anarchy of Self-Selection in Tullock Contests. AAMAS 2020: 1795-1797 - [c166]Rose E. Wang, Sarah A. Wu, James A. Evans, Joshua B. Tenenbaum, David C. Parkes, Max Kleiman-Weiner:
Too Many Cooks: Coordinating Multi-agent Collaboration Through Inverse Planning. AAMAS 2020: 2032-2034 - [c165]Sarah A. Wu, Rose E. Wang, James A. Evans, Josh Tenenbaum, David C. Parkes, Max Kleiman-Weiner:
Too many cooks: Coordinating multi-agent collaboration through inverse planning. CogSci 2020 - [c164]Zhe Feng, David C. Parkes, Haifeng Xu:
The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation. ICML 2020: 3092-3101 - [c163]Sarah Keren, Sara Bernardini, Kofi Kwapong, David C. Parkes:
Reasoning About Plan Robustness Versus Plan Cost for Partially Informed Agents. KR 2020: 550-559 - [c162]Nir Rosenfeld, Sophie Hilgard, Sai Srivatsa Ravindranath, David C. Parkes:
From Predictions to Decisions: Using Lookahead Regularization. NeurIPS 2020 - [c161]Nir Rosenfeld, Aron Szanto, David C. Parkes:
A Kernel of Truth: Determining Rumor Veracity on Twitter by Diffusion Pattern Alone. WWW 2020: 1018-1028 - [i55]Nir Rosenfeld, Aron Szanto, David C. Parkes:
A Kernel of Truth: Determining Rumor Veracity on Twitter by Diffusion Pattern Alone. CoRR abs/2002.00850 (2020) - [i54]Daniel J. Moroz, Daniel J. Aronoff, Neha Narula, David C. Parkes:
Double-Spend Counterattacks: Threat of Retaliation in Proof-of-Work Systems. CoRR abs/2002.10736 (2020) - [i53]Rose E. Wang, Sarah A. Wu, James A. Evans, Joshua B. Tenenbaum, David C. Parkes, Max Kleiman-Weiner:
Too many cooks: Coordinating multi-agent collaboration through inverse planning. CoRR abs/2003.11778 (2020) - [i52]Stephan Zheng, Alexander Trott, Sunil Srinivasa, Nikhil Naik, Melvin Gruesbeck, David C. Parkes, Richard Socher:
The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies. CoRR abs/2004.13332 (2020) - [i51]Nir Rosenfeld, Sophie Hilgard, Sai Srivatsa Ravindranath, David C. Parkes:
From Predictions to Decisions: Using Lookahead Regularization. CoRR abs/2006.11638 (2020) - [i50]Vincent Conitzer, Zhe Feng, David C. Parkes, Eric Sodomka:
Welfare-Preserving ε-BIC to BIC Transformation with Negligible Revenue Loss. CoRR abs/2007.09579 (2020) - [i49]Michael Neuder, Daniel J. Moroz, Rithvik Rao, David C. Parkes:
Defending Against Malicious Reorgs in Tezos Proof-of-Stake. CoRR abs/2009.05413 (2020) - [i48]He Sun, Zhun Deng, Hui Chen, David C. Parkes:
Decision-Aware Conditional GANs for Time Series Data. CoRR abs/2009.12682 (2020) - [i47]Gianluca Brero, Alon Eden, Matthias Gerstgrasser, David C. Parkes, Duncan Rheingans-Yoo:
Reinforcement Learning of Simple Indirect Mechanisms. CoRR abs/2010.01180 (2020) - [i46]Rediet Abebe, T.-H. Hubert Chan, Jon M. Kleinberg, Zhibin Liang, David C. Parkes, Mauro Sozio, Charalampos E. Tsourakakis:
Opinion Dynamics with Varying Susceptibility to Persuasion via Non-Convex Local Search. CoRR abs/2011.02583 (2020) - [i45]Ian T. Foster, David C. Parkes, Stephan Zheng:
The Rise of AI-Driven Simulators: Building a New Crystal Ball. CoRR abs/2012.06049 (2020)
2010 – 2019
- 2019
- [j43]Paul Dütting, Felix A. Fischer, David C. Parkes:
Expressiveness and Robustness of First-Price Position Auctions. Math. Oper. Res. 44(1): 196-211 (2019) - [j42]Iyad Rahwan, Manuel Cebrián, Nick Obradovich, Josh C. Bongard, Jean-François Bonnefon, Cynthia Breazeal, Jacob W. Crandall, Nicholas A. Christakis, Iain D. Couzin, Matthew O. Jackson, Nicholas R. Jennings, Ece Kamar, Isabel M. Kloumann, Hugo Larochelle, David Lazer, Richard McElreath, Alan Mislove, David C. Parkes, Alex 'Sandy' Pentland, Margaret E. Roberts, Azim Shariff, Joshua B. Tenenbaum, Michael P. Wellman:
Machine behaviour. Nat. 568(7753): 477-486 (2019) - [c160]Christos Dimitrakakis, Yang Liu, David C. Parkes, Goran Radanovic:
Bayesian Fairness. AAAI 2019: 509-516 - [c159]Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu:
How Do Fairness Definitions Fare?: Examining Public Attitudes Towards Algorithmic Definitions of Fairness. AIES 2019: 99-106 - [c158]Hongyao Ma, Reshef Meir, David C. Parkes, James Y. Zou:
Contingent Payment Mechanisms for Resource Utilization. AAMAS 2019: 422-430 - [c157]Hongyao Ma, Fei Fang, David C. Parkes:
Spatio-Temporal Pricing for Ridesharing Platforms. EC 2019: 583 - [c156]Paul Duetting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes, Sai Srivatsa Ravindranath:
Optimal Auctions through Deep Learning. ICML 2019: 1706-1715 - [c155]Goran Radanovic, Rati Devidze, David C. Parkes, Adish Singla:
Learning to Collaborate in Markov Decision Processes. ICML 2019: 5261-5270 - [c154]Berk Ustun, Yang Liu, David C. Parkes:
Fairness without Harm: Decoupled Classifiers with Preference Guarantees. ICML 2019: 6373-6382 - [c153]Duncan Rheingans-Yoo, Scott Duke Kominers, Hongyao Ma, David C. Parkes:
Ridesharing with Driver Location Preferences. IJCAI 2019: 557-564 - [c152]Jack Serrino, Max Kleiman-Weiner, David C. Parkes, Josh Tenenbaum:
Finding Friend and Foe in Multi-Agent Games. NeurIPS 2019: 1249-1259 - [c151]Haris Aziz, Hau Chan, Barton E. Lee, David C. Parkes:
The Capacity Constrained Facility Location Problem. WINE 2019: 336 - [i44]Gregory D. Hager, Ann W. Drobnis, Fei Fang, Rayid Ghani, Amy Greenwald, Terah Lyons, David C. Parkes, Jason Schultz, Suchi Saria, Stephen F. Smith, Milind Tambe:
Artificial Intelligence for Social Good. CoRR abs/1901.05406 (2019) - [i43]Goran Radanovic, Rati Devidze, David C. Parkes, Adish Singla:
Learning to Collaborate in Markov Decision Processes. CoRR abs/1901.08029 (2019) - [i42]Debmalya Mandal, David C. Parkes:
Weighted Tensor Completion for Time-Series Causal Inference. CoRR abs/1902.04646 (2019) - [i41]Sophie Hilgard, Nir Rosenfeld, Mahzarin R. Banaji, Jack Cao, David C. Parkes:
Learning Representations by Humans, for Humans. CoRR abs/1905.12686 (2019) - [i40]Duncan Rheingans-Yoo, Scott Duke Kominers, Hongyao Ma, David C. Parkes:
Ridesharing with Driver Location Preferences. CoRR abs/1905.13191 (2019) - [i39]Zhe Feng, David C. Parkes, Haifeng Xu:
The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation. CoRR abs/1906.01528 (2019) - [i38]Jack Serrino, Max Kleiman-Weiner, David C. Parkes, Joshua B. Tenenbaum:
Finding Friend and Foe in Multi-Agent Games. CoRR abs/1906.02330 (2019) - [i37]Hongyao Ma, Reshef Meir, David C. Parkes, Elena Wu-Yan:
Penalty Bidding Mechanisms for Allocating Resources and Overcoming Present Bias. CoRR abs/1906.09713 (2019) - [i36]David C. Parkes, Rakesh V. Vohra, et al.:
Algorithmic and Economic Perspectives on Fairness. CoRR abs/1909.05282 (2019) - [i35]Michael Neuder, Daniel J. Moroz, Rithvik Rao, David C. Parkes:
Selfish Behavior in the Tezos Proof-of-Stake Protocol. CoRR abs/1912.02954 (2019) - 2018
- [j41]David C. Parkes:
Technical perspective: Moving spectrum. Commun. ACM 61(1): 96 (2018) - [c150]Reshef Meir, David C. Parkes:
Playing the Wrong Game: Bounding Externalities in Diverse Populations of Agents. AAMAS 2018: 86-94 - [c149]Zhe Feng, Harikrishna Narasimhan, David C. Parkes:
Deep Learning for Revenue-Optimal Auctions with Budgets. AAMAS 2018: 354-362 - [c148]Noah Golowich, Harikrishna Narasimhan, David C. Parkes:
Deep Learning for Multi-Facility Location Mechanism Design. IJCAI 2018: 261-267 - [c147]Rediet Abebe, Jon M. Kleinberg, David C. Parkes, Charalampos E. Tsourakakis:
Opinion Dynamics with Varying Susceptibility to Persuasion. KDD 2018: 1089-1098 - [c146]Jean Pouget-Abadie, Vahab S. Mirrokni, David C. Parkes, Edoardo M. Airoldi:
Optimizing Cluster-based Randomized Experiments under Monotonicity. KDD 2018: 2090-2099 - [c145]Hongyao Ma, Reshef Meir, David C. Parkes:
Social Choice with Non Quasi-linear Utilities. EC 2018: 49 - [i34]Hongyao Ma, Fei Fang, David C. Parkes:
Spatio-Temporal Pricing for Ridesharing Platforms. CoRR abs/1801.04015 (2018) - [i33]Rediet Abebe, Jon M. Kleinberg, David C. Parkes, Charalampos E. Tsourakakis:
Opinion Dynamics with Varying Susceptibility to Persuasion. CoRR abs/1801.07863 (2018) - [i32]Hongyao Ma, Reshef Meir, David C. Parkes:
Social Choice with Non Quasi-linear Utilities. CoRR abs/1804.02268 (2018) - [i31]Haris Aziz, Hau Chan, Barton E. Lee, David C. Parkes:
Mechanism Design without Money for Common Goods. CoRR abs/1806.00960 (2018) - [i30]Nripsuta Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu:
How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness. CoRR abs/1811.03654 (2018) - 2017
- [j40]Ehud Kalai, Marco Battaglini, Gary Charness, Vincent P. Crawford, Françoise Forges, David C. Parkes, Jennifer Byrd:
Introduction to the John Forbes Nash Jr. Memorial Special Issue. Games Econ. Behav. 103: 1-18 (2017) - [c144]David C. Parkes:
On AI, Markets and Machine Learning. AAMAS 2017: 2 - [c143]David C. Parkes, Paul Tylkin, Lirong Xia:
Thwarting Vote Buying Through Decoy Ballots - Extended Version. AAMAS Workshops (Visionary Papers) 2017: 45-66 - [c142]Hongyao Ma, David C. Parkes, Valentin Robu:
Generalizing Demand Response Through Reward Bidding. AAMAS 2017: 60-68 - [c141]Rediet Abebe, Jon M. Kleinberg, David C. Parkes:
Fair Division via Social Comparison. AAMAS 2017: 281-289 - [c140]David C. Parkes, Paul Tylkin, Lirong Xia:
Thwarting Vote Buying Through Decoy Ballots. AAMAS 2017: 1679-1681 - [c139]David C. Parkes, Paul Tylkin, Lirong Xia:
Thwarting Vote Buying Through Decoy Ballots. IJCAI 2017: 3784-3790 - [c138]Christos Dimitrakakis, David C. Parkes, Goran Radanovic, Paul Tylkin:
Multi-View Decision Processes: The Helper-AI Problem. NIPS 2017: 5443-5452 - [c137]Arpit Agarwal, Debmalya Mandal, David C. Parkes, Nisarg Shah:
Peer Prediction with Heterogeneous Users. EC 2017: 81-98 - [i29]Christos Dimitrakakis, Yang Liu, David C. Parkes, Goran Radanovic:
Subjective fairness: Fairness is in the eye of the beholder. CoRR abs/1706.00119 (2017) - [i28]Paul Dütting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes:
Optimal Auctions through Deep Learning. CoRR abs/1706.03459 (2017) - [i27]