From the 1 of 8 linked papers with an AI index.
8 papers
Bandit PCA with Minimax Optimal Regret
Moïse Blanchard, Dmitrii Ostrovskii, Aadirupa Saha
The paper investigates the bandit-feedback version of online principal component analysis, presenting a new algorithm that achieves near‑optimal regret of order r√(dT) and proving…
Non-Monetary Mechanism Design without Priors: Achieving Efficiency via Adaptive Costly Audits
Yan Dai, Moise Blanchard, Patrick Jaillet
We study repeated resource allocation with strategic agents, where monetary transfers are disallowed and the planner has no prior information on agents' utility distributions. Insp…
Distribution-Free Sequential Prediction with Abstentions
Jialin Yu, Moïse Blanchard
We study a sequential prediction problem in which an adversary is allowed to inject arbitrarily many adversarial instances in a stream of i.i.d. instances, but at each round, the l…
Characterizing Online and Private Learnability under Distributional Constraints via Generalized Smoothness
Moïse Blanchard, Abhishek Shetty, Alexander Rakhlin
Understanding minimal assumptions that enable learning and generalization is perhaps the central question of learning theory. Several celebrated results in statistical learning the…
Consistency and inconsistency in -means clustering
Moïse Blanchard, Moïse Blanchard, Adam Quinn Jaffe +1
A celebrated result of Pollard proves asymptotic consistency for -means clustering when the population distribution has finite variance. In this work, we point out that the popu…
Fréchet Mean Set Estimation in the Hausdorff Metric, via Relaxation
Moise Blanchard, Adam Quinn Jaffe
This work resolves the following question in non-Euclidean statistics: Is it possible to consistently estimate the Fréchet mean set of an unknown population distribution, with res…