We present the first approach for checking the internal validity of online experiments statically, that is, from code alone.
Emma Tosch, Eytan Bakshy, Emery D. Berger, David D. Jensen, J. Eliot B. Moss From Communications of the ACM | September 2021
"WINOGRANDE" explores new methods of dataset development and adversarial filtering, expressly designed to prevent AI systems from making claims of smashing through...Leora Morgenstern From Communications of the ACM | September 2021
We introduce WinoGrande, a large-scale dataset of 44k problems, inspired by the original Winograd Schema Challenge, but adjusted to improve both the scale and the...Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi From Communications of the ACM | September 2021
The automated blood pressure wearable system described in "eBP," by Nam Bui et al., is a sterling example of the third wave of mobile health tech to fill the preventative...Josiah D. Hester From Communications of the ACM | August 2021
We developed eBP to measure blood pressure from inside a user's ear aiming to minimize the measurement's impact on normal activities while maximizing its comfort...Nam Bui, Nhat Pham, Jessica Jacqueline Barnitz, Zhanan Zou, Phuc Nguyen, Hoang Truong, Taeho Kim, Nicholas Farrow, Anh Nguyen, Jianliang Xiao, Robin Deterding, Thang Dinh, Tam Vu From Communications of the ACM | August 2021
"Optimal Auctions Through Deep Learning," by Paul Dütting et al., contributes a very interesting and forward-looking new take on the optimal multi-item mechanism...Constantinos Daskalakis From Communications of the ACM | August 2021
We overview recent research results that show how tools from deep learning are shaping up to become a powerful tool for the automated design of near-optimal auctions...Paul Dütting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes, Sai S. Ravindranath From Communications of the ACM | August 2021
We review the impact of the first year of the COVID-19 pandemic on Internet traffic in order to analyze its performance.
Anja Feldmann, Oliver Gasser, Franziska Lichtblau, Enric Pujol, Ingmar Poese, Christoph Dietzel, Daniel Wagner, Matthias Wichtlhuber, Juan Tapiador, Narseo Vallina-Rodriguez, Oliver Hohlfeld, Georgios Smaragdakis From Communications of the ACM | July 2021
"Deriving Equations from Sensor Data Using Dimensional Function Synthesis," by Vasileios Tsoutsouras, et al., addresses the key problem of discovering relationships...Sriram Sankaranarayanan From Communications of the ACM | July 2021
We present a new method, which we call dimensional function synthesis, for deriving functions that model the relationship between multiple signals in a physical...Vasileios Tsoutsouras, Sam Willis, Phillip Stanley-Marbell From Communications of the ACM | July 2021
"In-Sensor Classification With Boosted Race Trees," by Georgios Tzimpragos, et al., proposes a surprising, novel, and creative approach to post-Moore's Law computing...Abhishek Bhattacharjee From Communications of the ACM | June 2021
We demonstrate the potential of a novel form of encoding, race logic, in which information is represented as the delay in the arrival of a signal.
Georgios Tzimpragos, Advait Madhavan, Dilip Vasudevan, Dmitri Strukov, Timothy Sherwood From Communications of the ACM | June 2021
"Simba," by Yakun Sophia Shao, et al., presents a scalable deep learning accelerator architecture that tackles issues ranging from chip integration technology to...Natalie Enright Jerger From Communications of the ACM | June 2021
This work investigates and quantifies the costs and benefits of using multi-chip-modules with fine-grained chiplets for deep learning inference, an application...Yakun Sophia Shao, Jason Cemons, Rangharajan Venkatesan, Brian Zimmer, Matthew Fojtik, Nan Jiang, Ben Keller, Alicia Klinefelter, Nathaniel Pinckney, Priyanka Raina, Stephen G. Tell, Yanqing Zhang, William J. Dally, Joel Emer, C. Thomas Gray, Brucek Khailany, Stephen W. Keckler From Communications of the ACM | June 2021
"Robustness Meets Algorithms," by Ilias Diakonikolas, et al., represents the beginning of a long and productive line of work on robust statistics in high dimensions...Jacob S. Steinhardt From Communications of the ACM | May 2021
We give the first efficient algorithm for estimating the parameters of a high-dimensional Gaussian that is able to tolerate a constant fraction of corruptions that...Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart From Communications of the ACM | May 2021
In "Isomorphism, Canonization, and Definability for Graphs of Bounded Rank Width," Grohe and Neuen show that the Weisfeiler-Leman algorithm in its plain form solves...Pascal Schweitzer From Communications of the ACM | May 2021
In this paper we study the graph isomorphism problem and the closely related graph canonization problem as well as logical definability and descriptive complexity...Martin Grohe, Daniel Neuen From Communications of the ACM | May 2021