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Stochastic Hard Thresholding Algorithms for AUC Maximization
ZhenhuanYang, BaojianZhou, YunwenLei....
Published date-11/04/2020
In this paper, we aim to develop stochastic hard thresholding algorithms for the important problem of AUC maximization in imbalanced classification. The main challenge is the pairwise loss involved in …
Diversity-Enriched Option-Critic
AnandKamat, DoinaPrecup....
Published date-11/04/2020
ContinuousControl
Temporal abstraction allows reinforcement learning agents to represent knowledge and develop strategies over different temporal scales. The option-critic framework has been demonstrated to learn temporally extended actions, represented as options, …
MTLB-STRUCT @PARSEME 2020: Capturing Unseen Multiword Expressions Using Multi-task Learning and Pre-trained Masked Language Models
ShivaTaslimipoor, SaraBahaadini, EkaterinaKochmar....
Published date-11/04/2020
Multi-TaskLearning
This paper describes a semi-supervised system that jointly learns verbal multiword expressions (VMWEs) and dependency parse trees as an auxiliary task. The model benefits from pre-trained multilingual BERT. BERT hidden …
Deep Multimodality Learning for UAV Video Aesthetic Quality Assessment
QiKuang, XinJin, QinpingZhao....
Published date-11/04/2020
VideoClassification
Despite the growing number of unmanned aerial vehicles (UAVs) and aerial videos, there is a paucity of studies focusing on the aesthetics of aerial videos that can provide valuable information …
A Two-Stage Cascade Model with Variational Autoencoders and Attention Gates for MRI Brain Tumor Segmentation
ChenggangLyu, HaiShu....
Published date-11/04/2020
BrainTumorSegmentation, TumorSegmentation
Automatic MRI brain tumor segmentation is of vital importance for the disease diagnosis, monitoring, and treatment planning. In this paper, we propose a two-stage encoder-decoder based model for brain tumor …
Re-Assessing the "Classify and Count" Quantification Method
AlejandroMoreo, FabrizioSebastiani....
Published date-11/04/2020
SentimentAnalysis
Learning to quantify (a.k.a.\ quantification) is a task concerned with training unbiased estimators of class prevalence via supervised learning. This task originated with the observation that "Classify and Count" (CC), …