Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges

10 May 2019

Papers citing "Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges"

20 / 20 papers shown

Title
Towards a Non-Ideal Methodological Framework for Responsible ML Ramaravind Kommiya Mothilal Shion Guha Syed Ishtiaque Ahmed 44 7 0 20 Jan 2024
Machine Learning practices and infrastructures G. Berman 20 3 0 13 Jul 2023
Optimization's Neglected Normative Commitments Benjamin Laufer T. Gilbert Helen Nissenbaum OffRL 21 4 0 27 May 2023
Machine Learning with Requirements: a Manifesto Eleonora Giunchiglia F. Imrie M. Schaar Thomas Lukasiewicz AI4TS OffRL VLM 32 5 0 07 Apr 2023
MLTEing Models: Negotiating, Evaluating, and Documenting Model and System Qualities Katherine R. Maffey Kyle Dotterrer Jennifer Niemann Iain J. Cruickshank Grace A. Lewis Christian Kastner 27 4 0 03 Mar 2023
Iterative Assessment and Improvement of DNN Operational Accuracy Antonio Guerriero R. Pietrantuono S. Russo AI4CE 12 4 0 02 Mar 2023
Fiduciary Responsibility: Facilitating Public Trust in Automated Decision Making Shannon B. Harper Eric S. Weber 16 0 0 06 Jan 2023
When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development Nghia Duong-Trung Stefan Born Jong Woo Kim M. Schermeyer Katharina Paulick ... Thorben Werner Randolf Scholz Lars Schmidt-Thieme Peter Neubauer Ernesto Martinez 34 20 0 02 Sep 2022
Ergo, SMIRK is Safe: A Safety Case for a Machine Learning Component in a Pedestrian Automatic Emergency Brake System Markus Borg Jens Henriksson Kasper Socha Olof Lennartsson Elias Sonnsjo Lonegren T. Bui Piotr Tomaszewski S. Sathyamoorthy Sebastian Brink M. H. Moghadam 32 23 0 16 Apr 2022
Data Justice in Practice: A Guide for Developers David Leslie Michael Katell Mhairi Aitken Jatinder Singh Morgan Briggs Rosamund Powell Cami Rincón A. Perini Smera Jayadeva Christopher Burr SyDa 20 2 0 12 Apr 2022
Trustworthy AI: From Principles to Practices Bo-wen Li Peng Qi Bo Liu Shuai Di Jingen Liu Jiquan Pei Jinfeng Yi Bowen Zhou 119 355 0 04 Oct 2021
The missing link: Developing a safety case for perception components in automated driving Rick Salay Krzysztof Czarnecki Hiroshi Kuwajima Hirotoshi Yasuoka Toshihiro Nakae Vahdat Abdelzad Chengjie Huang Maximilian Kahn Van Duong Nguyen 24 11 0 30 Aug 2021
Certification of embedded systems based on Machine Learning: A survey Guillaume Vidot Christophe Gabreau I. Ober Iulian Ober 11 12 0 14 Jun 2021
Towards Risk Modeling for Collaborative AI Matteo Camilli Michael Felderer Andrea Giusti D. Matt A. Perini B. Russo A. Susi 17 4 0 12 Mar 2021
DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers Colin Paterson Haoze Wu John M. Grese R. Calinescu C. Păsăreanu Clark W. Barrett AAML 22 21 0 02 Mar 2021
A Safety Framework for Critical Systems Utilising Deep Neural Networks Xingyu Zhao Alec Banks James Sharp Valentin Robu David Flynn Michael Fisher Xiaowei Huang AAML 50 48 0 07 Mar 2020
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 231 1,837 0 03 Feb 2017
Safety Verification of Deep Neural Networks Xiaowei Huang M. Kwiatkowska Sen Wang Min Wu AAML 180 932 0 21 Oct 2016
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,746 0 26 Sep 2016
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,636 0 03 Jul 2012