no code implementations • 23 Nov 2020 • Jayant Gupchup, Ashkan Aazami, Yaran Fan, Senja Filipi, Tom Finley, Scott Inglis, Marcus Asteborg, Luke Caroll, Rajan Chari, Markus Cozowicz, Vishak Gopal, Vinod Prakash, Sasikanth Bendapudi, Jack Gerrits, Eric Lau, Huazhou Liu, Marco Rossi, Dima Slobodianyk, Dmitri Birjukov, Matty Cooper, Nilesh Javar, Dmitriy Perednya, Sriram Srinivasan, John Langford, Ross Cutler, Johannes Gehrke
Large software systems tune hundreds of 'constants' to optimize their runtime performance.
The goal of the synthesizer is to synthesize a "decision function" $f$ which transforms the features to a decision value for the black-box component so as to maximize the expected reward $E[r \circ f (x)]$ for executing decisions $f(x)$ for various values of $x$.
Web-scale applications can ship code on a daily to weekly cadence.
no code implementations • 16 May 2020 • Chandan K. A. Reddy, Vishak Gopal, Ross Cutler, Ebrahim Beyrami, Roger Cheng, Harishchandra Dubey, Sergiy Matusevych, Robert Aichner, Ashkan Aazami, Sebastian Braun, Puneet Rana, Sriram Srinivasan, Johannes Gehrke
In this challenge, we open-sourced a large clean speech and noise corpus for training the noise suppression models and a representative test set to real-world scenarios consisting of both synthetic and real recordings.
For a given workload, however, such techniques are unable to optimize for the important metric of the number of blocks accessed by a query.
no code implementations • 23 Jan 2020 • Chandan K. A. Reddy, Ebrahim Beyrami, Harishchandra Dubey, Vishak Gopal, Roger Cheng, Ross Cutler, Sergiy Matusevych, Robert Aichner, Ashkan Aazami, Sebastian Braun, Puneet Rana, Sriram Srinivasan, Johannes Gehrke
In this challenge, we open-source a large clean speech and noise corpus for training the noise suppression models and a representative test set to real-world scenarios consisting of both synthetic and real recordings.
no code implementations • 4 Dec 2019 • Joyce Fang, Martin Ellis, Bin Li, Siyao Liu, Yasaman Hosseinkashi, Michael Revow, Albert Sadovnikov, Ziyuan Liu, Peng Cheng, Sachin Ashok, David Zhao, Ross Cutler, Yan Lu, Johannes Gehrke
Bandwidth estimation and congestion control for real-time communications (i. e., audio and video conferencing) remains a difficult problem, despite many years of research.
Our subjective MOS evaluation is the first large scale evaluation of Speech Enhancement algorithms that we are aware of.
no code implementations • 21 May 2019 • Jialin Ding, Umar Farooq Minhas, JIA YU, Chi Wang, Jaeyoung Do, Yi-Nan Li, Hantian Zhang, Badrish Chandramouli, Johannes Gehrke, Donald Kossmann, David Lomet, Tim Kraska
The original work by Kraska et al. shows that a learned index beats a B+Tree by a factor of up to three in search time and by an order of magnitude in memory footprint.
Thus, to make a GPLAM a viable approach in situations in which little is known $a~priori$ about the features, one must overcome two primary model selection challenges: deciding which features to include in the model and determining which of these features to treat nonlinearly.
We consider the problem of quantitatively evaluating missing value imputation algorithms.