Biased Embeddings from Wild Data: Measuring, Understanding and Removing

16 June 2018

Papers citing "Biased Embeddings from Wild Data: Measuring, Understanding and Removing"

9 / 9 papers shown

Title
Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks Ruth C. Fong Andrea Vedaldi FAtt 64 264 0 10 Jan 2018
SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation Daniel Cer Mona T. Diab Eneko Agirre I. Lopez-Gazpio Lucia Specia 369 1,880 0 31 Jul 2017
ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models Minsuk Kahng Pierre Yves Andrews Aditya Kalro Duen Horng Chau HAI 66 324 0 06 Apr 2017
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks Jun-Yan Zhu Taesung Park Phillip Isola Alexei A. Efros GAN 111 5,554 0 30 Mar 2017
Learning from Simulated and Unsupervised Images through Adversarial Training A. Shrivastava Tomas Pfister Oncel Tuzel J. Susskind Wenda Wang Russ Webb GAN 94 1,800 0 22 Dec 2016
Semantics derived automatically from language corpora contain human-like biases Aylin Caliskan J. Bryson Arvind Narayanan 193 2,661 0 25 Aug 2016
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings Tolga Bolukbasi Kai-Wei Chang James Zou Venkatesh Saligrama Adam Kalai CVBM FaML 95 3,127 0 21 Jul 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 995 16,931 0 16 Feb 2016
Evaluating the visualization of what a Deep Neural Network has learned Wojciech Samek Alexander Binder G. Montavon Sebastian Lapuschkin K. Müller XAI 132 1,191 0 21 Sep 2015