• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 17 matches

• 2024
• 
  Debaditya Roy:
  Towards Trustworthy Machine Learning For Human Activity Recognition. Royal Institute of Technology, Stockholm, Sweden, 2024
• 
  Alexandru Tifrea:
  Towards Trustworthy Machine Learning Using Unlabeled Data. ETH Zurich, Zürich, Switzerland, 2024
• 
  Raphael Fischer, Thomas Liebig, Katharina Morik:
  Towards more sustainable and trustworthy reporting in machine learning. Data Min. Knowl. Discov. 38(4): 1909-1928 (2024)
• 
  Huaiguang Cai:
  CHG Shapley: Efficient Data Valuation and Selection towards Trustworthy Machine Learning. CoRR abs/2406.11730 (2024)
• 
  Firas Bayram, Bestoun S. Ahmed:
  Towards Trustworthy Machine Learning in Production: An Overview of the Robustness in MLOps Approach. CoRR abs/2410.21346 (2024)
• 2023
• 
  Manli Shu:
  Towards Trustworthy Machine Learning Systems. University of Maryland, College Park, MD, USA, 2023
• 
  Muhammad Atif Butt, Adnan Qayyum, Hassan Ali, Ala I. Al-Fuqaha, Junaid Qadir:
  Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study. Comput. Secur. 125: 103058 (2023)
• 
  Haoyang Liu, Maheep Chaudhary, Haohan Wang:
  Towards Trustworthy and Aligned Machine Learning: A Data-centric Survey with Causality Perspectives. CoRR abs/2307.16851 (2023)
• 2022
• 
  Adam Gleave:
  Towards Trustworthy Machine Learning. University of California, Berkeley, USA, 2022
• 
  Pulei Xiong, Scott Buffett, Shahrear Iqbal, Philippe Lamontagne, Mohammad Saiful Islam Mamun, Heather Molyneaux:
  Towards a robust and trustworthy machine learning system development: An engineering perspective. J. Inf. Secur. Appl. 65: 103121 (2022)
• 
  Taotao Zhou, Te Han, Enrique López Droguett:
  Towards trustworthy machine fault diagnosis: A probabilistic Bayesian deep learning framework. Reliab. Eng. Syst. Saf. 224: 108525 (2022)
• 
  Hendrik F. R. Schmidt, Jörg Schlötterer, Marcel Bargull, Enrico Nasca, Ryan Aydelott, Christin Seifert, Folker Meyer:
  Towards a trustworthy, secure and reliable enclave for machine learning in a hospital setting: The Essen Medical Computing Platform (EMCP). CoRR abs/2201.04816 (2022)
• 2021
• 
  Hendrik F. R. Schmidt, Jörg Schlötterer, Marcel Bargull, Enrico Nasca, Ryan Aydelott, Christin Seifert, Folker Meyer:
  Towards a trustworthy, secure and reliable enclave for machine learning in a hospital setting: The Essen Medical Computing Platform (EMCP). CogMI 2021: 116-123
• 
  Pulei Xiong, Scott Buffett, Shahrear Iqbal, Philippe Lamontagne, Mohammad Saiful Islam Mamun, Heather Molyneaux:
  Towards a Robust and Trustworthy Machine Learning System Development. CoRR abs/2101.03042 (2021)
• 2020
• 
  Roland H. C. Yap:
  Towards Certifying Trustworthy Machine Learning Systems. TAILOR 2020: 77-82
• 
  Hendrik Heuer, Andreas Breiter:
  More Than Accuracy: Towards Trustworthy Machine Learning Interfaces for Object Recognition. UMAP 2020: 298-302
• 
  Hendrik Heuer, Andreas Breiter:
  More Than Accuracy: Towards Trustworthy Machine Learning Interfaces for Object Recognition. CoRR abs/2008.01980 (2020)