activity
20192026
most citedAn Improved Algorithm for Learning Drifting Discrete Distributions

1 citations · 2 across the 6 of their papers we have counts for

collaborators
Showing cs.LGShow all

6 papers · 1 filter

cs.LG2026

tensorFM: Low-Rank Approximations of Cross-Order Feature Interactions

Alessio Mazzetto, Mohammad Mahdi Khalili, Laura Fee Nern +3

We address prediction problems on tabular categorical data, where each instance is defined by multiple categorical attributes, each taking values from a finite set. These attribute…

cs.LG2024★ 1 cited

An Improved Algorithm for Learning Drifting Discrete Distributions

Alessio Mazzetto

We present a new adaptive algorithm for learning discrete distributions under distribution drift. In this setting, we observe a sequence of independent samples from a discrete dist…

cs.LG2023

An Adaptive Method for Weak Supervision with Drifting Data

Alessio Mazzetto, Reza Esfandiarpoor, Akash Singirikonda +2

We introduce an adaptive method with formal quality guarantees for weak supervision in a non-stationary setting. Our goal is to infer the unknown labels of a sequence of data by us…

cs.LG2023

An Adaptive Algorithm for Learning with Unknown Distribution Drift

Alessio Mazzetto, Eli Upfal

We develop and analyze a general technique for learning with an unknown distribution drift. Given a sequence of independent observations from the last steps of a drifting distr…

cs.LG2023

Nonparametric Density Estimation under Distribution Drift

Alessio Mazzetto, Eli Upfal

We study nonparametric density estimation in non-stationary drift settings. Given a sequence of independent samples taken from a distribution that gradually changes in time, the go…

cs.LG2022★ 1 cited

Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with Attributes

Alessio Mazzetto, Cristina Menghini, Andrew Yuan +2

We develop a rigorous mathematical analysis of zero-shot learning with attributes. In this setting, the goal is to label novel classes with no training data, only detectors for att…