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September 4, 2022
Daniel Haimovich, Dima Karamshuk, Thomas J. Leeper, Evgeniy Riabenko, Milan Vojnovic

We propose a feature-based approach based on a self-excited Hawkes point process model, which involves prediction of the content’s popularity at one or more reference horizons in tandem with a point predictor of an effective growth parameter that reflects the timescale of popularity growth.

February 14, 2022
Mahesh Balakrishnan, Mahesh Balakrishnan, Mihir Dharamshi, Jason Flinn, David Geraghty, Santosh Ghosh, Filip Gruszczynski, Ahmed Jafri, Jun Li, Jingming Liu, Suyog Mapara, Rajeev Nagar, Ivailo Nedelchev, Francois Richard, Chen Shen, Yee Jiun Song, Rounak Tibrewal, Vidhya Venkat, Ahmed Yossef, Ali Zaveri

We built and deployed two production databases using Delos at Facebook, creating nine dierent log-structured protocols in the process.

January 22, 2022
Wenlei He, Julián Mestre, Sergey Pupyrev, Lei Wang, Hongtao Yu

In this paper we tackle the problem, which is also known as profile inference and profile rectification. We investigate the classical approach for profile inference, based on computing minimum-cost maximum flows in a control-flow graph, and develop an extended model capturing the desired properties of real-world profiles.

January 10, 2022
Casey Brown, Taylor Bunge, Chip Conor, Meiyuzi Gao, Ali Israr, Carine Rognon, Benjamin Stephens-Fripp

Mediated social touch enables physical interactions, despite the distance, by transmitting the haptic cues that constitute social touch through devices. As this technology is fairly new, the users’ needs and their expectations on a device design and its features are unclear, as well as who would use this technology, and in which conditions.

January 9, 2022
Julian Chan, Chunxi Liu, Jun Liu, Fuchun Peng, Pradyot Prakash, Yatharth Saraf, Kjell Schubert, Ching-Feng Yeh, Xiaohui Zhang, Frank Zhang, Geoffrey Zweig

In this work, to measure the accuracy and efficiency for a latency-controlled streaming automatic speech recognition (ASR) application, we perform comprehensive evaluations on three popular training criteria: LF-MMI, CTC and RNN-T.