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Fransisca Susan

dblp:286/0963 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2024
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 2 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Theory of computation · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
2 papers
Approximation and online algorithms · 58% Mathematical optimization · 25% Algorithmic game theory and mechanism design · 17%
Artificial intelligence
1 paper
Trustworthy machine learning · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Approximation and online algorithms › online algorithms
online combinatorial optimization		 1.322024
Online Combinatorial Optimization with Group Fairness Constraints · IJCAI 2024
Online Learning via Offline Greedy Algorithms: Applications in Market Design and Optimization · EC 2021
Mathematical optimization › constrained optimization
fairness constraints		 0.812024
Online Combinatorial Optimization with Group Fairness Constraints · IJCAI 2024
Approximation and online algorithms
online algorithms		 0.512021
Online Learning via Offline Greedy Algorithms: Applications in Market Design and Optimization · EC 2021
Algorithmic game theory and mechanism design › mechanism design › algorithmic mechanism design
online mechanism design		 0.512021
Online Learning via Offline Greedy Algorithms: Applications in Market Design and Optimization · EC 2021
Machine learning › Trustworthy machine learning › fairness
group fairness		 0.212024
Online Combinatorial Optimization with Group Fairness Constraints · IJCAI 2024

Methods — techniques the papers use, named apart from their topics

online optimization · 1.5offline greedy algorithms · 0.5blackwell approachability · 0.5
YearPublicationVenuePosition
2024 Online Combinatorial Optimization with Group Fairness Constraints
Negin Golrezaei, Rad Niazadeh, Kumar Kshitij Patel, Fransisca Susan
 IJCAI4
2021 Online Learning via Offline Greedy Algorithms: Applications in Market Design and Optimization
abstract
Motivated by online decision-making in time-varying combinatorial environments, we study the problem of transforming offline algorithms to their online counterparts. We focus on offline combinatorial problems that are amenable to a constant factor approximation using a greedy algorithm that is robust to local errors. For such problems, we provide a general framework that efficiently transforms offline robust greedy algorithms to online ones using Blackwell approachability.
Rad Niazadeh, Negin Golrezaei, Joshua R. Wang, Fransisca Susan, Ashwinkumar Badanidiyuru
 EC4