34 citations · 129 across the 45 of their papers we have counts for
53 papers
Joint-task truthfulness of the DMI mechanism
Rafael Frongillo
The Determinant Mutual Information (DMI) mechanism of Kong (2020, 2024) is dominantly truthful within the class of *consistent* reporting strategies, those that apply the same sing…
Toward Simultaneously Optimal Regret in U-Calibration
Rafael Frongillo, Haipeng Luo, Nishant A. Mehta +1
U-calibration studies online forecasting algorithms whose predictions can be consumed by any unknown downstream agent, guaranteeing sublinear regret simultaneously for all proper l…
Adaptive Liquidity in Prediction Markets via Online Learning
Enrique Nueve, Bao Nguyen, Rafael Frongillo +1
Prediction markets rely on liquidity to convert trades into informative prices, yet existing mechanisms fix liquidity ex ante. This restriction enforces a static trade-off between…
Equilibria in Large Position-Optimization Games
Rafael Frongillo, Melody Hsu, Mary Monroe +1
We propose a general class of symmetric games called position-optimization games. Given a probability distribution over a set of targets , the players each cho…
Minimax Duality in Game-Theoretic Probability
Rafael Frongillo
Game-theoretic probability uses the structure of gambles to define a concept like probability, but which is more flexible and robust. We show that results in game-theoretic probabi…
Robust forecast aggregation via additional queries
Rafael Frongillo, Mary Monroe, Eric Neyman +1
We study the problem of robust forecast aggregation: combining expert forecasts with provable accuracy guarantees compared to the best possible aggregation of the underlying inform…
Consistency Conditions for Differentiable Surrogate Losses
Drona Khurana, Anish Thilagar, Dhamma Kimpara +1
The statistical consistency of surrogate losses for discrete prediction tasks is often checked via the condition of calibration. However, directly verifying calibration can be ardu…
Structured Prediction with Abstention via the Lovász Hinge
Jessie Finocchiaro, Rafael Frongillo, Enrique Nueve
The Lovász hinge is a convex loss function proposed for binary structured classification, in which k related binary predictions jointly evaluated by a submodular function. Despite…
Peer Prediction with More Signals than Reports
Rafael Frongillo, Ian Kash, Mary Monroe
Peer prediction mechanisms are typically proposed and analyzed under the assumption that the report and signal spaces are identical. In practice, however, agents often observe rich…
Hedging and Approximate Truthfulness in Traditional Forecasting Competitions
Mary Monroe, Anish Thilagar, Melody Hsu +1
In forecasting competitions, the traditional mechanism scores the predictions of each contestant against the outcome of each event, and the contestant with the highest total score…
A General Theory of Liquidity Provisioning for Prediction Markets
Adithya Bhaskara, Rafael Frongillo, Elias Lindgren +1
Liquidity provisioning in automated market makers is the practice of recruiting third-party liquidity providers (LPs) to contribute assets to the market in exchange for fees skimme…
Forecasting Competitions with Correlated Events
Rafael Frongillo, Manuel Lladser, Anish Thilagar +1
Beginning with Witkowski et al. [2022], recent work on forecasting competitions has addressed incentive problems with the common winner-take-all mechanism. Frongillo et al. [2021]…
An Axiomatic Characterization of CFMMs and Equivalence to Prediction Markets
Rafael Frongillo, Maneesha Papireddygari, Bo Waggoner
Constant-function market makers (CFMMs), such as Uniswap, are automated exchanges offering trades among a set of assets. We study their technical relationship to another class of a…
Proper losses for discrete generative models
Rafael Frongillo, Dhamma Kimpara, Bo Waggoner
We initiate the study of proper losses for evaluating generative models in the discrete setting. Unlike traditional proper losses, we treat both the generative model and the target…
Consistent Polyhedral Surrogates for Top- Classification and Variants
Jessie Finocchiaro, Rafael Frongillo, Emma Goodwill +1
Top- classification is a generalization of multiclass classification used widely in information retrieval, image classification, and other extreme classification settings. Sever…
An Embedding Framework for the Design and Analysis of Consistent Polyhedral Surrogates
Jessie Finocchiaro, Rafael M. Frongillo, Bo Waggoner
We formalize and study the natural approach of designing convex surrogate loss functions via embeddings, for problems such as classification, ranking, or structured prediction. In…
The Structured Abstain Problem and the Lovász Hinge
Jessie Finocchiaro, Rafael Frongillo, Enrique Nueve
The Lovász hinge is a convex surrogate recently proposed for structured binary classification, in which binary predictions are made simultaneously and the error is judged by a…
Quantum Information Elicitation
Rafael Frongillo
In the classic scoring rule setting, a principal incentivizes an agent to truthfully report their probabilistic belief about some future outcome. This paper addresses the situation…
No-Regret Learning in Games is Turing Complete
Gabriel P. Andrade, Rafael Frongillo, Georgios Piliouras
Games are natural models for multi-agent machine learning settings, such as generative adversarial networks (GANs). The desirable outcomes from algorithmic interactions in these ga…
Computational complexity of problems for deterministic presentations of sofic shifts
Justin Cai, Rafael Frongillo
Sofic shifts are symbolic dynamical systems defined by the set of bi-infinite sequences on an edge-labeled directed graph, called a presentation. We study the computational complex…
Agreement Implies Accuracy for Substitutable Signals
Rafael Frongillo, Eric Neyman, Bo Waggoner
Inspired by Aumann's agreement theorem, Scott Aaronson studied the amount of communication necessary for two Bayesian experts to approximately agree on the expectation of a random…
Surrogate Regret Bounds for Polyhedral Losses
Rafael Frongillo, Bo Waggoner
Surrogate risk minimization is an ubiquitous paradigm in supervised machine learning, wherein a target problem is solved by minimizing a surrogate loss on a dataset. Surrogate regr…
Graphical Economies with Resale
Gabriel P. Andrade, Rafael Frongillo, Elliot Gorokhovsky +1
Kakade, Kearns, and Ortiz (KKO) introduce a graph-theoretic generalization of the classic Arrow--Debreu (AD) exchange economy. Despite its appeal as a networked version of AD, we a…
Truncated Metric Dimension for Finite Graphs
Richard C. Tillquist, Rafael M. Frongillo, Manuel E. Lladser
A graph with geodesic distance is said to be resolved by a non-empty subset of its vertices when, for all vertices and , if fo…