Bo Waggoner

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 72

Top Topics

Differential Privacy

Prediction Markets

Top Venues

Publications

Mary Monroe, Bo Waggoner
Public Projects with Preferences and Predictions. CoRR (2024)
Rafael M. Frongillo, Maneesha Papireddygari, Bo Waggoner
An Axiomatic Characterization of CFMMs and Equivalence to Prediction Markets. ITCS (2024)
Robin Bowers, Bo Waggoner
Matching with Nested and Bundled Pandora Boxes. CoRR (2024)
Enrique B. Nueve, Bo Waggoner, Dhamma Kimpara, Jessie Finocchiaro
Trading off Consistency and Dimensionality of Convex Surrogates for the Mode. CoRR (2024)
Rafael M. Frongillo, Manuel E. Lladser, Anish Thilagar, Bo Waggoner
Forecasting Competitions with Correlated Events. CoRR (2023)
Rafael M. Frongillo, Eric Neyman, Bo Waggoner
Agreement Implies Accuracy for Substitutable Signals. EC (2023)
Dhamma Kimpara, Rafael M. Frongillo, Bo Waggoner
Proper Losses for Discrete Generative Models. ICML (2023)
Rafael M. Frongillo, Maneesha Papireddygari, Bo Waggoner
An Axiomatic Characterization of CFMMs and Equivalence to Prediction Markets. CoRR (2023)
Robin Bowers, Bo Waggoner
High-Welfare Matching Markets via Descending Price. WINE (2023)
Robin Bowers, Bo Waggoner
High Welfare Matching Markets via Descending Price. CoRR (2022)
Maneesha Papireddygari, Bo Waggoner
Contracts with Information Acquisition, via Scoring Rules. CoRR (2022)
Jessie Finocchiaro, Rafael M. Frongillo, Bo Waggoner
An Embedding Framework for the Design and Analysis of Consistent Polyhedral Surrogates. CoRR (2022)
Rafael M. Frongillo, Dhamma Kimpara, Bo Waggoner
Proper losses for discrete generative models. CoRR (2022)
Maneesha Papireddygari, Bo Waggoner
Contracts with Information Acquisition, via Scoring Rules. EC (2022)
Rafael M. Frongillo, Robert Gomez, Anish Thilagar, Bo Waggoner
Efficient Competitions and Online Learning with Strategic Forecasters. EC (2021)
Rafael M. Frongillo, Eric Neyman, Bo Waggoner
Agreement Implies Accuracy for Substitutable Signals. CoRR (2021)
Rafael M. Frongillo, Bo Waggoner
Surrogate Regret Bounds for Polyhedral Losses. NeurIPS (2021)
Rafael M. Frongillo, Bo Waggoner
Surrogate Regret Bounds for Polyhedral Losses. CoRR (2021)
Rafael M. Frongillo, Robert Gomez, Anish Thilagar, Bo Waggoner
Efficient Competitions and Online Learning with Strategic Forecasters. CoRR (2021)
Jessie Finocchiaro, Rafael M. Frongillo, Bo Waggoner
Unifying Lower Bounds on Prediction Dimension of Consistent Convex Surrogates. CoRR (2021)
Bo Waggoner
Linear Functions to the Extended Reals. CoRR (2021)
Rupert Freeman, David M. Pennock, Daniel M. Reeves, David M. Rothschild, Bo Waggoner
Towards a Theory of Confidence in Market-Based Predictions. ISIPTA (2021)
Jessica Finocchiaro, Rafael M. Frongillo, Bo Waggoner
Unifying lower bounds on prediction dimension of convex surrogates. NeurIPS (2021)
Jerry Anunrojwong, Yiling Chen, Bo Waggoner, Haifeng Xu
Computing Equilibria of Prediction Markets via Persuasion. CoRR (2020)
Matthew Joseph, Aaron Roth, Jonathan R. Ullman, Bo Waggoner
Local Differential Privacy for Evolving Data. J. Priv. Confidentiality 10 (1) (2020)
Zhiyuan Liu, Huazheng Wang, Bo Waggoner, Youjian Liu, Lijun Chen
A Smoothed Analysis of Online Lasso for the Sparse Linear Contextual Bandit Problem. CoRR (2020)
Jessie Finocchiaro, Rafael M. Frongillo, Bo Waggoner
Embedding Dimension of Polyhedral Losses. COLT (2020)
Ariel Avital, Klim Efremenko, Aryeh Kontorovich, David Toplin, Bo Waggoner
Non-parametric Binary regression in metric spaces with KL loss. CoRR (2020)
Eduardo M. Azevedo, David M. Pennock, Bo Waggoner, E. Glen Weyl
Channel Auctions. Manag. Sci. 66 (5) (2020)
Nicole Immorlica, Sahil Singla, Bo Waggoner
Prophet Inequalities with Linear Correlations and Augmentations. EC (2020)
Nicole Immorlica, Sahil Singla, Bo Waggoner
Prophet Inequalities with Linear Correlations and Augmentations. CoRR (2020)
Rupert Freeman, David M. Pennock, Dominik Peters, Bo Waggoner
Preventing Arbitrage from Collusion When Eliciting Probabilities. AAAI (2020)
Jerry Anunrojwong, Yiling Chen, Bo Waggoner, Haifeng Xu
Computing Equilibria of Prediction Markets via Persuasion. WINE (2019)
Yahav Bechavod, Katrina Ligett, Aaron Roth, Bo Waggoner, Zhiwei Steven Wu
Equal Opportunity in Online Classification with Partial Feedback. NeurIPS (2019)
Justin D. Harris, Bo Waggoner
Decentralized & Collaborative AI on Blockchain. CoRR (2019)
Jessie Finocchiaro, Rafael M. Frongillo, Bo Waggoner
An Embedding Framework for Consistent Polyhedral Surrogates. CoRR (2019)
Nika Haghtalab, Cameron Musco, Bo Waggoner
Toward a Characterization of Loss Functions for Distribution Learning. CoRR (2019)
Rafael M. Frongillo, Nishant A. Mehta, Tom Morgan, Bo Waggoner
Multi-Observation Regression. AISTATS (2019)
Zhiwei Steven Wu, Aaron Roth, Katrina Ligett, Bo Waggoner, Seth Neel
Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM. J. Priv. Confidentiality 9 (2) (2019)
Justin D. Harris, Bo Waggoner
Decentralized and Collaborative AI on Blockchain. Blockchain (2019)
Yahav Bechavod, Katrina Ligett, Aaron Roth, Bo Waggoner, Zhiwei Steven Wu
Equal Opportunity in Online Classification with Partial Feedback. CoRR (2019)
Jessica Finocchiaro, Rafael M. Frongillo, Bo Waggoner
An Embedding Framework for Consistent Polyhedral Surrogates. NeurIPS (2019)
Nika Haghtalab, Cameron Musco, Bo Waggoner
Toward a Characterization of Loss Functions for Distribution Learning. NeurIPS (2019)
Matthew Joseph, Aaron Roth, Jonathan R. Ullman, Bo Waggoner
Local Differential Privacy for Evolving Data. NeurIPS (2018)
Shuran Zheng, Bo Waggoner, Yang Liu, Yiling Chen
Active Information Acquisition for Linear Optimization. UAI (2018)
Matthew Joseph, Aaron Roth, Jonathan R. Ullman, Bo Waggoner
Local Differential Privacy for Evolving Data. CoRR (2018)
Rafael M. Frongillo, Nishant A. Mehta, Tom Morgan, Bo Waggoner
Multi-Observation Regression. CoRR (2018)
Rafael M. Frongillo, Bo Waggoner
An Axiomatic Study of Scoring Rule Markets. ITCS (2018)
Rafael M. Frongillo, Bo Waggoner
Bounded-Loss Private Prediction Markets. NeurIPS (2018)
Sampath Kannan, Jamie Morgenstern, Aaron Roth, Bo Waggoner, Zhiwei Steven Wu
A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem. NeurIPS (2018)
Sampath Kannan, Jamie Morgenstern, Aaron Roth, Bo Waggoner, Zhiwei Steven Wu
A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem. CoRR (2018)
Jinshuo Dong, Aaron Roth, Zachary Schutzman, Bo Waggoner, Zhiwei Steven Wu
Strategic Classification from Revealed Preferences. EC (2018)
Yiling Chen, Bo Waggoner
Intro to informational substitutes. SIGecom Exch. 16 (1) (2017)
Sebastian Casalaina-Martin, Rafael M. Frongillo, Tom Morgan, Bo Waggoner
Multi-Observation Elicitation. CoRR (2017)
Rafael M. Frongillo, Bo Waggoner
An Axiomatic Study of Scoring Rule Markets. CoRR (2017)
Jinshuo Dong, Aaron Roth, Zachary Schutzman, Bo Waggoner, Zhiwei Steven Wu
Strategic Classification from Revealed Preferences. CoRR (2017)
Yiling Chen, Bo Waggoner
Informational Substitutes. CoRR (2017)
Yuan Deng, Debmalya Panigrahi, Bo Waggoner
The Complexity of Stable Matchings under Substitutable Preferences. AAAI (2017)
Sebastian Casalaina-Martin, Rafael M. Frongillo, Tom Morgan, Bo Waggoner
Multi-Observation Elicitation. COLT (2017)
Shuran Zheng, Bo Waggoner, Yang Liu, Yiling Chen
Active Information Acquisition for Linear Optimization. CoRR (2017)
Bo Waggoner, Rafael M. Frongillo, Jacob D. Abernethy
Addendum to "A Market Framework for Eliciting Private Data". CoRR (2017)
Katrina Ligett, Seth Neel, Aaron Roth, Bo Waggoner, Zhiwei Steven Wu
Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM. NIPS (2017)
Katrina Ligett, Seth Neel, Aaron Roth, Bo Waggoner, Zhiwei Steven Wu
Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM. CoRR (2017)
Yiling Chen, Bo Waggoner
Informational Substitutes. FOCS (2016)
Robert Kleinberg, Bo Waggoner, E. Glen Weyl
Descending Price Coordinates Approximately Efficient Search. CoRR (2016)
Robert D. Kleinberg, Bo Waggoner, E. Glen Weyl
Descending Price Optimally Coordinates Search. EC (2016)
Aranyak Mehta, Bo Waggoner, Morteza Zadimoghaddam
Online Stochastic Matching with Unequal Probabilities. SODA (2015)
Bo Waggoner
Testing and Learning of Discrete Distributions. ITCS (2015)
Yiling Chen, Kobbi Nissim, Bo Waggoner
Fair Information Sharing for Treasure Hunting. AAAI (2015)
Bo Waggoner, Rafael M. Frongillo, Jacob D. Abernethy
A Market Framework for Eliciting Private Data. NIPS (2015)
Jacob D. Abernethy, Yiling Chen, Chien-Ju Ho, Bo Waggoner
Low-Cost Learning via Active Data Procurement. EC (2015)
Jacob D. Abernethy, Yiling Chen, Chien-Ju Ho, Bo Waggoner
Actively Purchasing Data for Learning. CoRR (2015)
Bo Waggoner, Yiling Chen
Output Agreement Mechanisms and Common Knowledge. HCOMP (2014)
Bo Waggoner
Testing and Learning of Discrete Distributions. CoRR (2014)
Yang Cai, Mohammad Mahdian, Aranyak Mehta, Bo Waggoner
Designing Markets for Daily Deals. WINE (2013)
Yang Cai, Mohammad Mahdian, Aranyak Mehta, Bo Waggoner
Designing Markets for Daily Deals. CoRR (2013)
Bo Waggoner, Lirong Xia, Vincent Conitzer
Evaluating Resistance to False-Name Manipulations in Elections. AAAI (2012)