Flower: A Friendly Federated Learning Framework – Link [https://federated.withgoogle.com/] – Federated Learning – Learning better products with on-device data and privacy by default. An online comic from Google AI “The main difference between federated learning and distributed learning lies in the assumptions made on the properties of the local datasets, as distributed learning originally aims …
Interpretable Machine Learning – A Guide for Making Black Box Models Explainable – Christoph Molnar – Link Interpretable AI – Building explainable machine learning systems, Ajay Thampi – Link Papers Multi-Objective Counterfactual Explanations by Susanne Dandl, Christoph Molnar, Martin Binder, Bernd Bischl – Link Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers by …
Papers Towards Evaluating the Robustness of Neural Networks – Nicholas Carlini, David Wagner, University of California, Berkeley – Link Defense against Universal Adversarial Perturbations – Naveed Akhtar, Jian Liu, Ajmal Mian – Link Local Gradients Smoothing: Defense against localized adversarial attacks – Muzammal Naseer, Salman H. Khan – Link Sparse and Imperceivable Adversarial Attacks – …
State of AI Report – 2020 by AI investors Nathan Benaich and Ian Hogarth:
