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March 1, 2021 Guilherme Ottoni, Bin Liu
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HHVM Jump-Start: Boosting Both Warmup and Steady-State Performance at Scale

This paper presents the Jump-Start mechanism implemented inside the HipHop Virtual Machine (HHVM). Jump-Start is a practical approach to share VM profile data at a large scale, being used to power one of the largest websites in the world.
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February 23, 2021 Satadru Pan, Theano Stavrinos, Yunqiao Zhang, Atul Sikaria, Pavel Zakharov, Abhinav Sharma, Shiva Shankar, Mike Shuey, Richard Wareing, Monika Gangapuram, Guanglei Cao, Christian Preseau, Pratap Singh, Kestutis Patiejunas, JR Tipton, Ethan Katz-Bassett, Wyatt Lloyd
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Facebook’s Tectonic Filesystem: Efficiency from Exascale

This paper describes Tectonic’s design, explaining how it achieves scalability, supports multitenancy, and allows tenants to specialize operations to optimize for diverse workloads. The paper also presents insights from designing, deploying, and operating Tectonic.
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February 22, 2021 Jeremiah Onaolapo, Nektarios Leontiadis, Despoina Magka, Gianluca Stringhini
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SocialHEISTing: Understanding Stolen Facebook Accounts

To understand the effects of demographic attributes on attacker behavior in stolen social accounts, we devised a method to instrument and monitor such accounts. We then created, instrumented, and deployed more than 1000 Facebook accounts, and exposed them to criminals.
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January 25, 2021 Julius Kusuma, Erik Boch
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Improving Rural Connectivity Coverage using Diffractive Non-Line of Sight (NLOS) Wireless Backhaul

We present a feasible condition for the use of diffractive NLOS, for a single obstacle with shallow diffraction angle, modest foliage loss, and moderate foliage, which we call NLOSv1.
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January 15, 2021 Sarah Bechtle, Artem Molchanov, Yevgen Chebotar, Edward Grefenstette, Ludovic Righetti, Gaurav S. Sukhatme, Franziska Meier
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Meta Learning via Learned Loss

In this paper, we take the first step towards automating this process, with the view of producing models which train faster and more robustly. Concretely, we present a meta-learning method for learning parametric loss functions that can generalize across different tasks and model architectures.
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January 5, 2021 Nirbhay Modhe, Prithvijit Chattopadhyay, Mohit Sharma, Abhishek Das, Devi Parikh, Dhruv Batra, Ramakrishna Vedantam
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IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL

We propose a novel framework to identify subgoals useful for exploration in sequential decision making tasks under partial observability.
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January 1, 2021 Mahmoud Assran, Michael Rabbat
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Asynchronous Gradient-Push

We consider a multi-agent framework for distributed optimization where each agent has access to a local smooth strongly convex function, and the collective goal is to achieve consensus on the parameters that minimize the sum of the agents’ local functions. We propose an algorithm wherein each agent operates asynchronously and independently of the other agents.
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December 23, 2020 Duncan C. McElfresh, Christian Kroer, Sergey Pupyrev, Eric Sodomka, Karthik Abinav Sankararaman, Zack Chauvin, Neil Dexter, John P. Dickerson
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Matching Algorithms for Blood Donation

Using the recently deployed Facebook Blood Donation tool, we conduct the first large-scale algorithmic matching of blood donors with donation opportunities. In both simulations and real experiments we match potential donors with opportunities, guided by a machine learning model trained on prior observations of donor behavior.
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December 21, 2020 May Yen, Francesco Colella, Harri Kytomaa, Boyd Allin, Alex Ockfen
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Contact Burn Injuries Part I: The influence of object thermal mass

This paper is the first of a two-part series that discusses a numerical methodology that relies on the concept of cumulative equivalent exposure to evaluate contact burn injury thresholds.
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December 21, 2020 May Yen, Francesco Colella, Harri Kytomaa, Boyd Allin, Alex Ockfen
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Contact Burn Injuries Part II: The influence of object shape, size, contact resistance, and applied heat flux

This paper is the second of a two-part series that discusses a numerical methodology that relies on the concept of cumulative equivalent exposure to evaluate contact burn injury thresholds. In Part I, the effect of a finite thermal mass is analyzed for an infinite plate of several finite thicknesses. In Part II, the sensitivities to object shape, size, thickness, contact resistance and applied heat flux are considered.
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