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Multi-scale Adaptive Task Attention Network for Few-Shot Learning
HaoxingChen, HuaxiongLi, YaohuiLi....
Published date-11/30/2020
Few-ShotLearning, MetricLearning
The goal of few-shot learning is to classify unseen categories with few labeled samples. Recently, the low-level information metric-learning based methods have achieved satisfying performance, since local representations (LRs) are …
Why model why? Assessing the strengths and limitations of LIME
JürgenDieber, SabrinaKirrane....
Published date-11/30/2020
AutonomousVehicles, DecisionMaking
When it comes to complex machine learning models, commonly referred to as black boxes, understanding the underlying decision making process is crucial for domains such as healthcare and financial services, …
Inter-layer Transition in Neural Architecture Search
BentengMa, JingZhang, YongXia....
Published date-11/30/2020
NeuralArchitectureSearch
Differential Neural Architecture Search (NAS) methods represent the network architecture as a repetitive proxy directed acyclic graph (DAG) and optimize the network weights and architecture weights alternatively in a differential …
Systematically Exploring Redundancy Reduction in Summarizing Long Documents
WenXiao, GiuseppeCarenini....
Published date-11/30/2020
Our analysis of large summarization datasets indicates that redundancy is a very serious problem when summarizing long documents. Yet, redundancy reduction has not been thoroughly investigated in neural summarization. In …
PMLB v1.0: an open source dataset collection for benchmarking machine learning methods
TrangT.Le, WilliamLaCava, JosephD.Romano....
Published date-11/30/2020
Multi-classClassification
PMLB (Penn Machine Learning Benchmark) is an open-source data repository containing a curated collection of datasets for evaluating and comparing machine learning (ML) algorithms. Compiled from a broad range of …
Towards constraining warm dark matter with stellar streams through neural simulation-based inference
JoeriHermans, NilanjanBanik, ChristophWeniger....
Published date-11/30/2020
BayesianInference
A statistical analysis of the observed perturbations in the density of stellar streams can in principle set stringent contraints on the mass function of dark matter subhaloes, which in turn …