Waggoner, Bo

24 publications

AAAI 2025 Forecasting Competitions with Correlated Events Rafael M. Frongillo, Manuel E. Lladser, Anish Thilagar, Bo Waggoner

NeurIPS 2025 Smooth Quadratic Prediction Markets Enrique Nueve, Bo Waggoner

JMLR 2024 An Embedding Framework for the Design and Analysis of Consistent Polyhedral Surrogates Jessie Finocchiaro, Rafael M. Frongillo, Bo Waggoner

NeurIPS 2024 Trading Off Consistency and Dimensionality of Convex Surrogates for Multiclass Classification Enrique Nueve, Bo Waggoner, Dhamma Kimpara, Jessie Finocchiaro

ICML 2023 Proper Losses for Discrete Generative Models Dhamma Kimpara, Rafael Frongillo, Bo Waggoner

NeurIPS 2021 Surrogate Regret Bounds for Polyhedral Losses Rafael M. Frongillo, Bo Waggoner

ISIPTA 2021 Towards a Theory of Confidence in Market-Based Predictions Rupert Freeman, David Pennock, Daniel Reeves, David Rothschild, Bo Waggoner

NeurIPS 2021 Unifying Lower Bounds on Prediction Dimension of Convex Surrogates Jessica Finocchiaro, Rafael M. Frongillo, Bo Waggoner

COLT 2020 Embedding Dimension of Polyhedral Losses Jessie Finocchiaro, Rafael Frongillo, Bo Waggoner

AAAI 2020 Preventing Arbitrage from Collusion When Eliciting Probabilities Rupert Freeman, David M. Pennock, Dominik Peters, Bo Waggoner

NeurIPS 2019 An Embedding Framework for Consistent Polyhedral Surrogates Jessica Finocchiaro, Rafael Frongillo, Bo Waggoner

NeurIPS 2019 Equal Opportunity in Online Classification with Partial Feedback Yahav Bechavod, Katrina Ligett, Aaron Roth, Bo Waggoner, Steven Z. Wu

AISTATS 2019 Multi-Observation Regression Rafael Frongillo, Nishant A. Mehta, Tom Morgan, Bo Waggoner

NeurIPS 2019 Toward a Characterization of Loss Functions for Distribution Learning Nika Haghtalab, Cameron Musco, Bo Waggoner

NeurIPS 2018 A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem Sampath Kannan, Jamie H Morgenstern, Aaron Roth, Bo Waggoner, Zhiwei Steven Wu

UAI 2018 Active Information Acquisition for Linear Optimization Shuran Zheng, Bo Waggoner, Yang Liu, Yiling Chen

NeurIPS 2018 Bounded-Loss Private Prediction Markets Rafael Frongillo, Bo Waggoner

NeurIPS 2018 Local Differential Privacy for Evolving Data Matthew Joseph, Aaron Roth, Jonathan Ullman, Bo Waggoner

NeurIPS 2017 Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM Katrina Ligett, Seth Neel, Aaron Roth, Bo Waggoner, Steven Z. Wu

COLT 2017 Multi-Observation Elicitation Sebastian Casalaina-Martin, Rafael Frongillo, Tom Morgan, Bo Waggoner

AAAI 2017 The Complexity of Stable Matchings Under Substitutable Preferences Yuan Deng, Debmalya Panigrahi, Bo Waggoner

NeurIPS 2015 A Market Framework for Eliciting Private Data Bo Waggoner, Rafael Frongillo, Jacob D. Abernethy

AAAI 2015 Fair Information Sharing for Treasure Hunting Yiling Chen, Kobbi Nissim, Bo Waggoner

AAAI 2012 Evaluating Resistance to False-Name Manipulations in Elections Bo Waggoner, Lirong Xia, Vincent Conitzer