activity
20172022
most citedAccelerating Generalized Linear Models with MLWeaving: A One-Size-Fits-All System for Any-precision Learning (Technical Report)

23 citations · 53 across the 7 of their papers we have counts for

collaborators

12 papers

cs.LG2022

iFlipper: Label Flipping for Individual Fairness

Hantian Zhang, Ki Hyun Tae, Jaeyoung Park +2

As machine learning becomes prevalent, mitigating any unfairness present in the training data becomes critical. Among the various notions of fairness, this paper focuses on the wel…

cs.CY20211 cited

OmniFair: A Declarative System for Model-Agnostic Group Fairness in Machine Learning

Hantian Zhang, Xu Chu, Abolfazl Asudeh +1

Machine learning (ML) is increasingly being used to make decisions in our society. ML models, however, can be unfair to certain demographic groups (e.g., African Americans or femal…

hep-ph2020

Two-Loop Rational Terms in Yang-Mills Theories

Jean-Nicolas Lang, Stefano Pozzorini, Hantian Zhang +1

Scattering amplitudes in dimensions involve particular terms that originate from the interplay of UV poles with the dimensional parts of loop numerators. Such contributio…

hep-ph2020

Rational terms in two-loop calculations

Stefano Pozzorini, Hantian Zhang, Max F. Zoller

We present an extension of the renormalisation procedure based on the R-operation in dimensions at two-loop level, in which the numerators of all Feynman diagrams can be constr…

hep-ph2020

Rational Terms of UV Origin at Two Loops

Stefano Pozzorini, Hantian Zhang, Max F. Zoller

The advent of efficient numerical algorithms for the construction of one-loop amplitudes has played a crucial role in the automation of NLO calculations, and the development of sim…

hep-ph2019

OpenLoops 2

Federico Buccioni, Jean-Nicolas Lang, Jonas M. Lindert +4

We present the new version of OpenLoops, an automated generator of tree and one-loop scattering amplitudes based on the open-loop recursion. One main novelty of OpenLoops 2 is the…