"Traffic Classification in an Increasingly Encrypted Web," by Iman Akbari et al., does a great job in reviewing related work in the network traffic classification...Athina Markopoulou From Communications of the ACM | October 2022
In this paper, we design a novel feature engineering approach used for encrypted Web protocols, and develop a neural network architecture based on stacked long...Iman Akbari, Mohammad A. Salahuddin, Leni Ven, Noura Limam, Raouf Boutaba, Bertrand Mathieu, Stephanie Moteau, Stephane Tuffin From Communications of the ACM | October 2022
"Polymorphic Wireless Receivers," by Francesco Restuccia and Tommaso Melodia, tackles the problem of physical layer resilience in wireless systems from a completely...Falko Dressler From Communications of the ACM | September 2022
We introduce PolymoRF, a deep learning-based polymorphic receiver able to reconfigure itself in real time based on the inferred waveform parameters.
Francesco Restuccia, Tommaso Melodia From Communications of the ACM | September 2022
In "hXDP: Efficient Software Packet Processing on FPGA NICs," the authors offer an interesting solution to bridging the performance gap between the CPU and the...Noa Zilberman From Communications of the ACM | August 2022
We present hXDP, a solution to run on FPGAs software packet processing tasks described with the eBPF technology and targeting the Linux's eXpress Data Path.
Marco Spaziani Brunella, Giacomo Belocchi, Marco Bonola, Salvatore Pontarelli, Giuseppe Siracusano, Giuseppe Bianchi, Aniello Cammarano, Alessandro Palumbo, Luca Petrucci, Roberto Bifulco From Communications of the ACM | August 2022
"On Sampled Metrics for Item Recommendation," by Walid Krichene and Steffen Rendle, exposes a crucial aspect for the evaluation of algorithms and tools: the impact...Fabio Vandin From Communications of the ACM | July 2022
This paper investigates sampled metrics and shows that it is possible to improve the quality of sampled metrics by applying a correction, obtained by minimizing...Walid Krichene, Steffen Rendle From Communications of the ACM | July 2022
In "FANG," the authors focus on a strategy of automatically detecting disinformation campaigns on online media with a new graph-based, contextual technique for...Philippe Cudré-Mauroux From Communications of the ACM | April 2022
We propose Factual News Graph (FANG), a novel graphical social context representation and learning framework for fake news detection.
Van-Hoang Nguyen, Kazunari Sugiyama, Preslav Nakov, Min-Yen Kan From Communications of the ACM | April 2022
"Worst-Case Topological Entropy and Minimal Data Rate for State Estimation of Switched Linear Systems" gives a method for computing the topological entropy of a...Sayan Mitra From Communications of the ACM | February 2022
In this paper, we study the problem of estimating the state of a switched linear system when the observation of the system is subject to communication constraints...Guillaume O. Berger, Raphael M. Jungers From Communications of the ACM | February 2022
Neural volume rendering exploded onto the scene in 2020, triggered by "NeRF," the impressive paper by Ben Mildenhall et al., on Neural Radiance Fields.
Frank Dellaert From Communications of the ACM | January 2022
We present a method that achieves state-of-the-art results for synthesizing novel views of complex scenes by optimizing an underlying continuous volumetric scene...Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, Ren Ng From Communications of the ACM | January 2022
"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
"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
"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