output
20062020
most citedResource Management in Wireless Networks via Multi-Agent Deep Reinforcement Learning

187 citations

21 papers

cs.LG2020★ 15 cited

Scaling Polyhedral Neural Network Verification on GPUs

Christoph Müller, François Serre, Gagandeep Singh +2

Certifying the robustness of neural networks against adversarial attacks is essential to their reliable adoption in safety-critical systems such as autonomous driving and medical d…

cs.DC2020★ 2 cited

Constant-Time Snapshots with Applications to Concurrent Data Structures

Yuanhao Wei, Naama Ben-David, Guy E. Blelloch +3

We present an approach for efficiently taking snapshots of the state of a collection of CAS objects. Taking a snapshot allows later operations to read the value that each CAS objec…

cs.CR2020★ 36 cited

Hermes Attack: Steal DNN Models with Lossless Inference Accuracy

Yuankun Zhu, Yueqiang Cheng, Husheng Zhou +1

Deep Neural Networks (DNNs) models become one of the most valuable enterprise assets due to their critical roles in all aspects of applications. With the trend of privatization dep…

cs.LG2020★ 187 cited

Resource Management in Wireless Networks via Multi-Agent Deep Reinforcement Learning

Navid Naderializadeh, Jaroslaw Sydir, Meryem Simsek +1

We propose a mechanism for distributed resource management and interference mitigation in wireless networks using multi-agent deep reinforcement learning (RL). We equip each transm…

cs.DB2019★ 7 cited

Optimal Algorithms for Ranked Enumeration of Answers to Full Conjunctive Queries

Nikolaos Tziavelis, Deepak Ajwani, Wolfgang Gatterbauer +2

We study ranked enumeration of join-query results according to very general orders defined by selective dioids. Our main contribution is a framework for ranked enumeration over a c…

cs.DB2019★ 46 cited

Understanding and Benchmarking the Impact of GDPR on Database Systems

Supreeth Shastri, Vinay Banakar, Melissa Wasserman +2

The General Data Protection Regulation (GDPR) provides new rights and protections to European people concerning their personal data. We analyze GDPR from a systems perspective, tra…