SPLASH 2020
Sun 15 - Sat 21 November 2020 Online Conference
Thu 19 Nov 2020 15:20 - 15:40 at SPLASH-I - R-5 Chair(s): Alex Potanin, Anitha Gollamudi
Fri 20 Nov 2020 03:20 - 03:40 at SPLASH-I - R-5 Chair(s): Jan Vitek

Recently, there is growing concern that machine-learned software, which currently assists or even automates decision making, reproduces, and in the worst case reinforces, bias present in the training data. The development of tools and techniques for certifying fairness of this software or describing its biases is, therefore, critical. In this paper, we propose a perfectly parallel static analysis for certifying fairness of feed-forward neural networks used for classification of tabular data. When certification succeeds, our approach provides definite guarantees, otherwise, it describes and quantifies the biased input space regions. We design the analysis to be sound, in practice also exact, and configurable in terms of scalability and precision, thereby enabling pay-as-you-go certification. We implement our approach in an open-source tool called Libra and demonstrate its effectiveness on neural networks trained on popular datasets.

Conference Day
Thu 19 Nov

Displayed time zone: Central Time (US & Canada) change

15:00 - 16:20
R-5OOPSLA at SPLASH-I +12h
Chair(s): Alex PotaninVictoria University of Wellington, Anitha GollamudiHarvard University
15:00
20m
Talk
Precise Static Modeling of Ethereum “Memory”
OOPSLA
Sifis LagouvardosUniversity of Athens, Neville GrechUniversity of Malta, Ilias TsatirisUniversity of Athens, Yannis SmaragdakisUniversity of Athens
Link to publication DOI Media Attached
15:20
20m
Talk
Perfectly Parallel Fairness Certification of Neural Networks
OOPSLA
Caterina UrbanINRIA & École Normale Supérieure | Université PSL, Maria ChristakisMPI-SWS, Valentin WüstholzConsenSys, Fuyuan ZhangMPI-SWS
Link to publication DOI Media Attached
15:40
20m
Talk
Taming Callbacks for Smart Contract Modularity
OOPSLA
Elvira AlbertComplutense University of Madrid, Shelly GrossmanTel Aviv University, Noam RinetzkyTel Aviv University, Clara Rodríguez-NúñezComplutense University of Madrid, Albert RubioComplutense University of Madrid, Mooly SagivTel Aviv University
Link to publication DOI Media Attached
16:00
20m
Talk
Exposing Cache Timing Side-Channel Leaks through Out-of-Order Symbolic Execution
OOPSLA
Shengjian GuoBaidu Security, Yueqi ChenPennsylvania State University, Jiyong YuUniversity of Illinois at Urbana-Champaign, Meng WuAnt Group, Zhiqiang ZuoNanjing University, Peng LiBaidu Security, Yueqiang ChengBaidu Security, Huibo WangBaidu Security
Link to publication DOI Media Attached

Conference Day
Fri 20 Nov

Displayed time zone: Central Time (US & Canada) change

03:00 - 04:20
R-5OOPSLA at SPLASH-I
Chair(s): Jan VitekNortheastern University / Czech Technical University
03:00
20m
Talk
Precise Static Modeling of Ethereum “Memory”
OOPSLA
Sifis LagouvardosUniversity of Athens, Neville GrechUniversity of Malta, Ilias TsatirisUniversity of Athens, Yannis SmaragdakisUniversity of Athens
Link to publication DOI Media Attached
03:20
20m
Talk
Perfectly Parallel Fairness Certification of Neural Networks
OOPSLA
Caterina UrbanINRIA & École Normale Supérieure | Université PSL, Maria ChristakisMPI-SWS, Valentin WüstholzConsenSys, Fuyuan ZhangMPI-SWS
Link to publication DOI Media Attached
03:40
20m
Talk
Taming Callbacks for Smart Contract Modularity
OOPSLA
Elvira AlbertComplutense University of Madrid, Shelly GrossmanTel Aviv University, Noam RinetzkyTel Aviv University, Clara Rodríguez-NúñezComplutense University of Madrid, Albert RubioComplutense University of Madrid, Mooly SagivTel Aviv University
Link to publication DOI Media Attached
04:00
20m
Talk
Exposing Cache Timing Side-Channel Leaks through Out-of-Order Symbolic Execution
OOPSLA
Shengjian GuoBaidu Security, Yueqi ChenPennsylvania State University, Jiyong YuUniversity of Illinois at Urbana-Champaign, Meng WuAnt Group, Zhiqiang ZuoNanjing University, Peng LiBaidu Security, Yueqiang ChengBaidu Security, Huibo WangBaidu Security
Link to publication DOI Media Attached