Research Area
Year Published

654 Results

January 1, 2020

Designing Safe Spaces for Virtual Reality

Ethics in Design and Communication 2020

Virtual Reality (VR) designers accept the ethical responsibilities of removing a user’s entire world and superseding it with a fabricated reality. These unique immersive design challenges are intensified when virtual experiences become public and socially-driven. As female VR designers in 2018, we see an opportunity to fold the language of consent into the design practice of virtual reality—as a means to design safe, accessible, virtual spaces.

Publication will be made available in 2020.

By: Michelle Cortese, Andrea Zeller

May 25, 2019

UBIS: Utilization-aware cluster scheduling

International Parallel and Distributed Processing Symposium (IPDPS)

Data center costs are among the major enterprise expenses, and any improvement in data center resource utilization corresponds to significant savings in true dollars. We focus on the problem of scheduling jobs in distributed execution environments to improve resource utilization.

By: Karthik Kambatla, Vamsee Yarlagadda, Íñigo Goiri, Ananth Grama

May 12, 2019

Provably Accelerated Randomized Gossip Algorithms

IEEE International Conference on Acoustics, Speech, and Signal Processing

In this work we present novel provably accelerated gossip algorithms for solving the average consensus problem.

By: Nicolas Loizou, Michael Rabbat, Peter Richtárik

May 4, 2019

Quasi-Hyperbolic Momentum and Adam for Deep Learning

International Conference on Learning Representations (ICLR)

Momentum-based acceleration of stochastic gradient descent (SGD) is widely used in deep learning. We propose the quasi-hyperbolic momentum algorithm (QHM) as an extremely simple alteration of momentum SGD, averaging a plain SGD step with a momentum step. We describe numerous connections to and identities with other algorithms, and we characterize the set of two-state optimization algorithms that QHM can recover.

By: Jerry Ma, Denis Yarats

May 1, 2019

Learning graphs from data: A signal representation perspective

IEEE Signal Processing Magazine

In this tutorial overview, we survey solutions to the problem of graph learning, including classical viewpoints from statistics and physics, and more recent approaches that adopt a graph signal processing (GSP) perspective.

By: Xiaowen Dong, Dorina Thanou, Michael Rabbat, Pascal Frossard

March 24, 2019

Skyway: Connecting Managed Heaps in Distributed Big Data Systems

International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)

This paper presents Skyway, a JVM-based technique that can directly connect managed heaps of different (local or remote) JVM processes.

By: Khan Nguyen, Lu Fang, Christian Navasca, Guoqing Xu, Brian Demsky, Shan Lu

February 21, 2019

Improving Treatment Effect Estimators Through Experiment Splitting

The Web Conference (WWW)

We present a method for implementing shrinkage of treatment effect estimators, and hence improving their precision, via experiment splitting.

By: Dominic Coey, Tom Cunningham

February 16, 2019

Machine Learning at Facebook: Understanding Inference at the Edge

IEEE International Symposium on High-Performance Computer Architecture (HPCA)

This paper takes a data-driven approach to present the opportunities and design challenges faced by Facebook in order to enable machine learning inference locally on smartphones and other edge platforms.

By: Carole-Jean Wu, David Brooks, Kevin Chen, Douglas Chen, Sy Choudhury, Marat Dukhan, Kim Hazelwood, Eldad Isaac, Yangqing Jia, Bill Jia, Tommer Leyvand, Hao Lu, Yang Lu, Lin Qiao, Brandon Reagen, Joe Spisak, Fei Sun, Andrew Tulloch, Peter Vajda, Xiaodong Wang, Yanghan Wang, Bram Wasti, Yiming Wu, Ran Xian, Sungjoo Yoo, Peizhao Zhang

February 13, 2019

SapFix: Automated End-to-End Repair at Scale

International Conference on Software Engineering (ICSE)

We report our experience with SAPFIX: the first deployment of automated end-to-end fault fixing, from test case design through to deployed repairs in production code.

By: Alexandru Marginean, Johannes Bader, Satish Chandra, Mark Harman, Yue Jia, Ke Mao, Alexander Mols, Andrew Scott

February 1, 2019

Separation Logic

Communications of the ACM (CACM)

In joint work with John Reynolds and others we developed Separation Logic as a formalism for reasoning about programs that mutate data structures. From a special logic for heaps it gradually evolved into a general theory for modular reasoning about concurrent as well as sequential programs.

By: Peter O'Hearn