73 citations · 439 across the 61 of their papers we have counts for
7 papers · 1 filter
Empirical Risk Minimization for Losses without Variance
Guanhua Fang, Ping Li, Gennady Samorodnitsky
This paper considers an empirical risk minimization problem under heavy-tailed settings, where data does not have finite variance, but only has -th moment with . In…
Limit theorems for high-dimensional Betti numbers in the multiparameter random simplicial complexes
Takashi Owada, Gennady Samorodnitsky
We consider the multiparameter random simplicial complex on a vertex set , which is parameterized by multiple connectivity probabilities. Our key results concern t…
Epsilon*: Privacy Metric for Machine Learning Models
Diana M. Negoescu, Humberto Gonzalez, Saad Eddin Al Orjany +9
We introduce Epsilon*, a new privacy metric for measuring the privacy risk of a single model instance prior to, during, or after deployment of privacy mitigation strategies. The me…
Adaptive Privacy Composition for Accuracy-first Mechanisms
Ryan Rogers, Gennady Samorodnitsky, Zhiwei Steven Wu +1
In many practical applications of differential privacy, practitioners seek to provide the best privacy guarantees subject to a target level of accuracy. A recent line of work by Li…
A Cover Time Study of a non-Markovian Algorithm
Guanhua Fang, Gennady Samorodnitsky, Zhiqiang Xu
Given a traversal algorithm, cover time is the expected number of steps needed to visit all nodes in a given graph. A smaller cover time means a higher exploration efficiency of tr…
The Asymptotics of the Expected Betti Numbers of Preferential Attachment Clique Complexes
Chunyin Siu, Gennady Samorodnitsky, Christina Lee Yu +1
The preferential attachment model is a natural and popular random graph model for a growing network that contains very well-connected ``hubs''. We study the higher-order connectivi…