June 22, 2015

Learning Spatiotemporal Features with 3D Convolutional Networks

ArXiv PrePrint

We propose C3D, a simple and effective approach for spatiotemporal feature using deep 3-dimensional convolutional networks (3D ConvNets) trained on a large scale supervised video dataset.

Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, Manohar Paluri
June 22, 2015

Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks

ArXiv PrePrint

We introduce a generative parametric model capable of producing high quality samples of natural images

Emily Denton, Soumith Chintala, Arthur Szlam, Rob Fergus
June 22, 2015

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

International Conference on Learning Representations, 2015

We examine the performance profile of Convolutional Neural Network training on the current generation of NVIDIA Graphics Processing Units.

Nicolas Vasilache, Jeff Johnson, Soumith Chintala, Serkan Piantino, Yann LeCun
June 22, 2015

Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets

ArXiv PrePrint

We develop a model that overcomes certain basic limitations of popular deep learning models. We demonstrate its capabilities by learning in an unsupervised way concepts such as simple memorization and binary addition.

Armand Joulin, Tomas Mikolov
June 22, 2015

A theoretical argument for complex-valued convolutional networks

ArXiv PrePrint

This article provides foundations for certain convolutional networks.

Joan Bruna, Soumith Chintala, Yann LeCun, Serkan Piantino, Arthur Szlam, Mark Tygert
June 15, 2015

A Large-Scale Study of Flash Memory Failures in the Field

ACM Sigmetrics 2015

This paper presents the first large-scale study of flash-based SSD reliability in the field.

Justin Meza, Qiang Wu, Sanjeev Kumar, Onur Mutlu
June 12, 2015

Web-Scale Training for Face Identification

The IEEE Conference on Computer Vision and Pattern Recognition

We study face recognition and show that three distinct properties have surprising effects on the transferability of deep convolutional networks (CNN)

Yaniv Taigman, Ming Yang, Marc'Aurelio Ranzato, Lior Wolf
June 1, 2015

Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues

International Conference on Computer Vision and Pattern Recognition

We propose a method for person recognition from arbitrary viewpoint and pose.

Ning Zhang, Manohar Paluri, Yaniv Taigman, Rob Fergus, Lubomir Bourdev
May 19, 2015

Challenges to Adopting Stronger Consistency at Scale

Workshop on Hot Topics in Operating Systems

There have been many recent advances in distributed systems that provide stronger semantics for geo-replicated data stores like those underlying Facebook. At Facebook we are excited by these lines of research, but fundamental and operational challenges currently make it infeasible to incorporate these advances into deployed systems. This paper describes some of these challenges with the hope that future advances will address them.

Philippe Ajoux, Nathan Bronson, Sanjeev Kumar, Wyatt Lloyd, Kaushik Veeraraghavan
May 18, 2015

The Lifecycles of Apps in a Social Ecosystem

Proc. WWW'15

Apps are emerging as an important form of on-line content, and they combine aspects of Web usage in interesting ways — they exhibit a rich temporal structure of user adoption and long-term engagement, and they exist in a broader social ecosystem that helps drive these patterns of adoption and engagement. It has been difficult, however, to study apps in their natural setting since this requires a simultaneous analysis of a large set of popular apps and the underlying social network they inhabit.

Isabel Kloumann, Lada Adamic, Jon Kleinberg, Shaomei Wu
May 18, 2015

Design and Analysis of Benchmarking Experiments for Distributed Internet Services

Proc. WWW

We develop statistical models of distributed Internet service performance based on data from Perflab, a production system used at Facebook which vets thousands of changes to the company’s codebase each day.

Eytan Bakshy, Eitan Frachtenberg
May 9, 2015

Exposure to Ideologically Diverse Information on Facebook

Science.

How do these online networks influence exposure to perspectives that cut across ideological lines?

Eytan Bakshy, Solomon Messing, Lada Adamic
May 6, 2015

Wormhole: Reliable Pub-Sub to Support Geo-replicated Internet Services

12th USENIX Symposium on Networked Systems Design and Implementation

Wormhole is a publish-subscribe (pub-sub) system developed for use within Facebook’s geographically replicated datacenters. It is used to reliably replicate changes among several Facebook services including TAO, Graph Search and Memcache. This paper describes the design and implementation of Wormhole as well as the operational challenges of scaling the system to support the multiple data storage systems deployed at Facebook.

Yogeshwer Sharma, Philippe Ajoux, Petchean Ang, David Callies, Abhishek Choudhary, Laurent Demailly, Thomas Fersch, Liat Atsmon, Andrzej Kotulski, Sachin Kulkarni, Sanjeev Kumar, Hu Li, Jun Li, Evgeniy Makeev, Kowshik Prakasam, Robbert van Renesse, Sabyasachi Roy, Pratyush Seth, Yee Jiun Song, Kaushik Veeraraghavan, Benjamin Wester, Peter Xie
March 14, 2015

The Diffusion of Support in an Online Social Movement: Evidence from the Adoption of Equal-Sign Profile Pictures

Proc. CSCW'15

In March of 2013, 3 million Facebook users changed their profile picture to one of an equals sign to express support of same-sex marriage. We demonstrate that this action shows complex diffusion characteristics congruent with threshold models, with most users observing several of their friends changing their profile picture before taking the action themselves.

Bogdan State, Lada Adamic
February 17, 2015

What makes for effective detection proposals?

PAMI

An in depth study of object proposals and their effect on object detection performance.

Jan Hosang, Rodrigo Benenson, Piotr Dollar, Bernt Schiele
February 10, 2015

Moving Fast with Software Verification

NASA Formal Method Symposium

For organisations like Facebook, high quality software is important. However, the pace of change and increasing complexity of modern code makes it difficult to produce error free software. Available tools are often lacking in helping programmers develop more reliable and secure applications.

Cristiano Calcagno, Dino Distefano, Jeremy Dubreil, Dominik Gabi, Pieter Hooimeijer, Martino Luca, Peter O'Hearn, Irene Papakonstantinou, Jim Purbrick, Dulma Churchill
December 19, 2014

Predicting the quality of new contributors to the Facebook crowdsourcing system

Neural Information Processing Systems: Crowdsourcing and Machine Learning Workshop

We are interested in improving the quality and coverage of a knowledge graph through crowdsourcing features built into a social networking service. This work presents an approach to model user trust when prior history is lacking.

Julian Eisenschlos
December 19, 2014

Video (language) modeling: a baseline for generative models of natural videos

ArXiv PrePrint

In this work, we investigate models of natural high-resolution video sequences. We show that very simple models borrowed by language modeling applications are surprisingly effective at recovering shor…

Marc'Aurelio Ranzato, Arthur Szlam, Joan Bruna, Michael Mathieu, Ronan Collobert, Sumit Chopra
December 19, 2014

Ensemble of Generative and Discriminative Techniques for Sentiment Analysis of Movie Reviews

ICLR workshop 2015

In this work we ensemble several models and achieve state of the art accuracy for predicting the sentiment of movie reviews in the IMDB dataset.

Gregoire Mesnil, Tomas Mikolov, Marc'Aurelio Ranzato, Yoshua Bengio
December 4, 2014

Extracting Translation Pairs from Social Network Content

International Workshop on Spoken Language Translation

We describe two methods to collect translation pairs from public Facebook content. We use the extracted translation pairs as additional training data for machine translation systems and we can show significant improvements.

Matthias Eck, Yury Zemlyanskiy, Joy Zhang, Alex Waibel