7 citations · 20 across the 8 of their papers we have counts for
9 papers
Defensive Boosting for Online Probabilistic Forecasting
Georgy Noarov, Aaron Roth
We study online probabilistic forecasting of binary outcomes chosen by an adaptive adversary. Given an online learning algorithm for a weak hypothesis class , we would like to e…
High-Dimensional Prediction for Sequential Decision Making
Georgy Noarov, Ramya Ramalingam, Aaron Roth +1
We study the problem of making predictions of an adversarially chosen high-dimensional state that are unbiased subject to an arbitrary collection of conditioning events, with the g…
The Scope of Multicalibration: Characterizing Multicalibration via Property Elicitation
Georgy Noarov, Aaron Roth
We make a connection between multicalibration and property elicitation and show that (under mild technical conditions) it is possible to produce a multicalibrated predictor for a c…
Batch Multivalid Conformal Prediction
Christopher Jung, Georgy Noarov, Ramya Ramalingam +1
We develop fast distribution-free conformal prediction algorithms for obtaining multivalid coverage on exchangeable data in the batch setting. Multivalid coverage guarantees are st…
Practical Adversarial Multivalid Conformal Prediction
Osbert Bastani, Varun Gupta, Christopher Jung +3
We give a simple, generic conformal prediction method for sequential prediction that achieves target empirical coverage guarantees against adversarially chosen data. It is computat…
Online Minimax Multiobjective Optimization: Multicalibeating and Other Applications
Daniel Lee, Georgy Noarov, Mallesh Pai +1
We introduce a simple but general online learning framework in which a learner plays against an adversary in a vector-valued game that changes every round. Even though the learner'…
Online Multivalid Learning: Means, Moments, and Prediction Intervals
Varun Gupta, Christopher Jung, Georgy Noarov +2
We present a general, efficient technique for providing contextual predictions that are "multivalid" in various senses, against an online sequence of adversarially chosen examples…
Binary Scoring Rules that Incentivize Precision
Eric Neyman, Georgy Noarov, S. Matthew Weinberg
All proper scoring rules incentivize an expert to predict \emph{accurately} (report their true estimate), but not all proper scoring rules equally incentivize \emph{precision}. Rat…
Computing Approximate Equilibria in Weighted Congestion Games via Best-Responses
Yiannis Giannakopoulos, Georgy Noarov, Andreas S. Schulz
We present a deterministic polynomial-time algorithm for computing -approximate (pure) Nash equilibria in (proportional sharing) weighted congestion games with polynomi…