Search Results for author: Emily Denton

Found 19 papers, 6 papers with code

Ethics and Creativity in Computer Vision

no code implementations6 Dec 2021 Negar Rostamzadeh, Emily Denton, Linda Petrini

This paper offers a retrospective of what we learnt from organizing the workshop *Ethical Considerations in Creative applications of Computer Vision* at CVPR 2021 conference and, prior to that, a series of workshops on *Computer Vision for Fashion, Art and Design* at ECCV 2018, ICCV 2019, and CVPR 2020.

Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Research

no code implementations3 Dec 2021 Bernard Koch, Emily Denton, Alex Hanna, Jacob G. Foster

Despite the foundational role of benchmarking practices in this field, relatively little attention has been paid to the dynamics of benchmark dataset use and reuse, within or across machine learning subcommunities.

AI and the Everything in the Whole Wide World Benchmark

no code implementations26 Nov 2021 Inioluwa Deborah Raji, Emily M. Bender, Amandalynne Paullada, Emily Denton, Alex Hanna

There is a tendency across different subfields in AI to valorize a small collection of influential benchmarks.

Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Development

no code implementations9 Aug 2021 Morgan Klaus Scheuerman, Emily Denton, Alex Hanna

Specifically, we examine what dataset documentation communicates about the underlying values of vision data and the larger practices and goals of computer vision as a field.

Autonomous Vehicles Object Detection

Characterising Bias in Compressed Models

no code implementations6 Oct 2020 Sara Hooker, Nyalleng Moorosi, Gregory Clark, Samy Bengio, Emily Denton

However, overall accuracy hides disproportionately high errors on a small subset of examples; we call this subset Compression Identified Exemplars (CIE).

Fairness Quantization

Social Biases in NLP Models as Barriers for Persons with Disabilities

no code implementations ACL 2020 Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, Stephen Denuyl

Building equitable and inclusive NLP technologies demands consideration of whether and how social attitudes are represented in ML models.

Sentiment Analysis

Diversity and Inclusion Metrics in Subset Selection

no code implementations9 Feb 2020 Margaret Mitchell, Dylan Baker, Nyalleng Moorosi, Emily Denton, Ben Hutchinson, Alex Hanna, Timnit Gebru, Jamie Morgenstern

The ethical concept of fairness has recently been applied in machine learning (ML) settings to describe a wide range of constraints and objectives.

Fairness

Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing

no code implementations3 Jan 2020 Inioluwa Deborah Raji, Timnit Gebru, Margaret Mitchell, Joy Buolamwini, Joonseok Lee, Emily Denton

Although essential to revealing biased performance, well intentioned attempts at algorithmic auditing can have effects that may harm the very populations these measures are meant to protect.

Computers and Society

Image Counterfactual Sensitivity Analysis for Detecting Unintended Bias

no code implementations14 Jun 2019 Emily Denton, Ben Hutchinson, Margaret Mitchell, Timnit Gebru, Andrew Zaldivar

Facial analysis models are increasingly used in applications that have serious impacts on people's lives, ranging from authentication to surveillance tracking.

Fairness

Modeling Others using Oneself in Multi-Agent Reinforcement Learning

1 code implementation ICML 2018 Roberta Raileanu, Emily Denton, Arthur Szlam, Rob Fergus

We consider the multi-agent reinforcement learning setting with imperfect information in which each agent is trying to maximize its own utility.

Multi-agent Reinforcement Learning reinforcement-learning

Stochastic Video Generation with a Learned Prior

4 code implementations ICML 2018 Emily Denton, Rob Fergus

Sample generations are both varied and sharp, even many frames into the future, and compare favorably to those from existing approaches.

Frame Video Generation +1

Unsupervised Learning of Disentangled Representations from Video

1 code implementation NeurIPS 2017 Emily Denton, Vighnesh Birodkar

We present a new model DrNET that learns disentangled image representations from video.

Frame

Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks

1 code implementation18 Jun 2015 Emily Denton, Soumith Chintala, Arthur Szlam, Rob Fergus

In this paper we introduce a generative parametric model capable of producing high quality samples of natural images.

Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation

no code implementations NeurIPS 2014 Emily Denton, Wojciech Zaremba, Joan Bruna, Yann Lecun, Rob Fergus

We present techniques for speeding up the test-time evaluation of large convolutional networks, designed for object recognition tasks.

Object Recognition

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