239 citations · 532 across the 9 of their papers we have counts for
10 papers
With Great Freedom Comes Great Opportunity: Rethinking Resource Allocation for Serverless Functions
Muhammad Bilal, Marco Canini, Rodrigo Fonseca +1
Current serverless offerings give users a limited degree of flexibility for configuring the resources allocated to their function invocations by either coupling memory and CPU reso…
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search
Linnan Wang, Rodrigo Fonseca, Yuandong Tian
High dimensional black-box optimization has broad applications but remains a challenging problem to solve. Given a set of samples $\{\vx_i, y_i\}$, building a global model (like Ba…
Few-shot Neural Architecture Search
Yiyang Zhao, Linnan Wang, Yuandong Tian +2
Efficient evaluation of a network architecture drawn from a large search space remains a key challenge in Neural Architecture Search (NAS). Vanilla NAS evaluates each architecture…
Serverless in the Wild: Characterizing and Optimizing the Serverless Workload at a Large Cloud Provider
Mohammad Shahrad, Rodrigo Fonseca, Íñigo Goiri +7
Function as a Service (FaaS) has been gaining popularity as a way to deploy computations to serverless backends in the cloud. This paradigm shifts the complexity of allocating and…
Sample-Efficient Neural Architecture Search by Learning Action Space
Linnan Wang, Saining Xie, Teng Li +2
Neural Architecture Search (NAS) has emerged as a promising technique for automatic neural network design. However, existing MCTS based NAS approaches often utilize manually design…
SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks
Linnan Wang, Wei Wu, Junyu Zhang +4
The performance and efficiency of distributed training of Deep Neural Networks highly depend on the performance of gradient averaging among all participating nodes, which is bounde…
Scanning the Internet for ROS: A View of Security in Robotics Research
Nicholas DeMarinis, Stefanie Tellex, Vasileios Kemerlis +2
Because robots can directly perceive and affect the physical world, security issues take on particular importance. In this paper, we describe the results of our work on scanning th…
Neural Architecture Search using Deep Neural Networks and Monte Carlo Tree Search
Linnan Wang, Yiyang Zhao, Yuu Jinnai +2
Neural Architecture Search (NAS) has shown great success in automating the design of neural networks, but the prohibitive amount of computations behind current NAS methods requires…
FITing-Tree: A Data-aware Index Structure
Alex Galakatos, Michael Markovitch, Carsten Binnig +2
Index structures are one of the most important tools that DBAs leverage to improve the performance of analytics and transactional workloads. However, building several indexes over…
Compiling Stateful Network Properties for Runtime Verification
Tim Nelson, Nicholas DeMarinis, Timothy Adam Hoff +2
Networks are difficult to configure correctly, and tricky to debug. These problems are accentuated by temporal and stateful behavior. Static verification, while useful, is ineffect…