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nnU-Net for Brain Tumor Segmentation


Authors:  FabianIsensee, PaulF.Jaeger, PeterM.Full....
Published date-11/02/2020
Tasks:  BrainTumorSegmentation, DataAugmentation, TumorSegmentation

Abstract: We apply nnU-Net to the segmentation task of the BraTS 2020 challenge. The unmodified nnU-Net baseline configuration already achieves a respectable result. By incorporating BraTS-specific modifications regarding postprocessing, region-based training, …

Multi-Agent Reinforcement Learning for Persistent Monitoring


Authors:  JingxiChen, AmrishBaskaran, ZhongshunZhang....
Published date-11/02/2020
Tasks:  Multi-agentReinforcementLearning

Abstract: The Persistent Monitoring (PM) problem seeks to find a set of trajectories (or controllers) for robots to persistently monitor a changing environment. Each robot has a limited field-of-view and may …

ABNIRML: Analyzing the Behavior of Neural IR Models


Authors:  SeanMacAvaney, SergeyFeldman, NazliGoharian....
Published date-11/02/2020
Tasks:  LanguageModelling

Abstract: Numerous studies have demonstrated the effectiveness of pretrained contextualized language models such as BERT and T5 for ad-hoc search. However, it is not well-understood why these methods are so effective, …

Collection and Validation of Psycophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset


Authors:  AntonSmerdov, BoZhou, PaulLukowicz....
Published date-11/02/2020
Tasks:  LeagueofLegends

Abstract: Proper training and analytics in eSports require accurately collected and annotated data. Most eSports research focuses exclusively on in-game data analysis, and there is a lack of prior work involving …

Instance based Generalization in Reinforcement Learning


Authors:  MartinBertran, NataliaMartinez, MarianoPhielipp....
Published date-11/02/2020

Abstract: Agents trained via deep reinforcement learning (RL) routinely fail to generalize to unseen environments, even when these share the same underlying dynamics as the training levels. Understanding the generalization properties …

Adapting Pretrained Transformer to Lattices for Spoken Language Understanding


Authors:  Chao-WeiHuang, Yun-NungChen....
Published date-11/02/2020
Tasks:  NaturalLanguageUnderstanding, SpeechRecognition, SpokenLanguageUnderstanding

Abstract: Lattices are compact representations that encode multiple hypotheses, such as speech recognition results or different word segmentations. It is shown that encoding lattices as opposed to 1-best results generated by …

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