6 citations · 39 across the 21 of their papers we have counts for
6 papers · 1 filter
Robust Voting Rules from Algorithmic Robust Statistics
Allen Liu, Ankur Moitra
Maximum likelihood estimation furnishes powerful insights into voting theory, and the design of voting rules. However the MLE can usually be badly corrupted by a single outlying sa…
BERT_SE: A Pre-trained Language Representation Model for Software Engineering
Eliane Maria De Bortoli Fávero, Dalcimar Casanova
The application of Natural Language Processing (NLP) has achieved a high level of relevance in several areas. In the field of software engineering (SE), NLP applications are based…
Margin-Independent Online Multiclass Learning via Convex Geometry
Guru Guruganesh, Allen Liu, Jon Schneider +1
We consider the problem of multi-class classification, where a stream of adversarially chosen queries arrive and must be assigned a label online. Unlike traditional bounds which se…
Robust Model Selection and Nearly-Proper Learning for GMMs
Jerry Li, Allen Liu, Ankur Moitra
In learning theory, a standard assumption is that the data is generated from a finite mixture model. But what happens when the number of components is not known in advance? The pro…
Algorithms from Invariants: Smoothed Analysis of Orbit Recovery over
Allen Liu, Ankur Moitra
In this work we study orbit recovery over , where the goal is to recover a function on the sphere from noisy, randomly rotated copies of it. We assume that the function is a…
Learning GMMs with Nearly Optimal Robustness Guarantees
Allen Liu, Ankur Moitra
In this work we solve the problem of robustly learning a high-dimensional Gaussian mixture model with components from -corrupted samples up to accuracy in…