Browse > Methodology > Multi-Label Classification

Multi-Label Classification

62 papers with code · Methodology

Leaderboards

No evaluation results yet. Help compare methods by submit evaluation metrics.

Latest papers with code

Fast Network Embedding Enhancement via High Order Proximity Approximation

‏‏‎ ‎ 2020 benedekrozemberczki/karateclub

Many Network Representation Learning (NRL) methods have been proposed to learn vector representations for vertices in a network recently.

DIMENSIONALITY REDUCTION LINK PREDICTION MULTI-LABEL CLASSIFICATION NETWORK EMBEDDING

742
13 May 2020

Dense-Caption Matching and Frame-Selection Gating for Temporal Localization in VideoQA

13 May 2020hyounghk/VideoQADenseCapFrameGate-ACL2020

Moreover, our model is also comprised of dual-level attention (word/object and frame level), multi-head self/cross-integration for different sources (video and dense captions), and gates which pass more relevant information to the classifier.

IMAGE CAPTIONING MULTI-LABEL CLASSIFICATION QUESTION ANSWERING TEMPORAL LOCALIZATION VIDEO QUESTION ANSWERING

7
13 May 2020

SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis

12 May 2020baidu/Senta

In particular, the prediction of aspect-sentiment pairs is converted into multi-label classification, aiming to capture the dependency between words in a pair.

MULTI-LABEL CLASSIFICATION SENTIMENT ANALYSIS

807
12 May 2020

Adversarial Learning for Personalized Tag Recommendation

1 Apr 2020vyzuer/ALTReco

We demonstrate the effectiveness of the proposed model on two different large-scale and publicly available datasets, YFCC100M and NUS-WIDE.

IMAGE CLASSIFICATION MULTI-LABEL CLASSIFICATION

1
01 Apr 2020

FrImCla: A Framework for Image Classification Using Traditional and Transfer Learning Techniques

IEEE 2020 ManuGar/FrImCla

In this work, we present FrImCla, an open-source and free tool that simplifies the construction of robust models for image classification from a dataset of images, and only using the computer CPU.

IMAGE CLASSIFICATION MULTI-LABEL CLASSIFICATION TRANSFER LEARNING

0
13 Mar 2020

End-to-End Neural Diarization: Reformulating Speaker Diarization as Simple Multi-label Classification

24 Feb 2020Xflick/EEND_PyTorch

However, the clustering-based approach has a number of problems; i. e., (i) it is not optimized to minimize diarization errors directly, (ii) it cannot handle speaker overlaps correctly, and (iii) it has trouble adapting their speaker embedding models to real audio recordings with speaker overlaps.

MULTI-LABEL CLASSIFICATION SPEAKER DIARIZATION

1
24 Feb 2020

Multi-Label Classification with Label Graph Superimposing

21 Nov 2019mathkey/mssnet

In this paper, we propose a label graph superimposing framework to improve the conventional GCN+CNN framework developed for multi-label recognition in the following two aspects.

MULTI-LABEL CLASSIFICATION REPRESENTATION LEARNING

1
21 Nov 2019

Joint Ranking SVM and Binary Relevance with Robust Low-Rank Learning for Multi-Label Classification

5 Nov 2019GuoqiangWoodrowWu/RBRL

RBRL inherits the ranking loss minimization advantages of Rank-SVM, and thus overcomes the disadvantages of BR suffering the class-imbalance issue and ignoring the label correlations.

MULTI-LABEL CLASSIFICATION

2
05 Nov 2019

Collaborative Graph Walk for Semi-supervised Multi-Label Node Classification

22 Oct 2019Uchman21/MLGW

In this work, we study semi-supervised multi-label node classification problem in attributed graphs.

MULTI-LABEL CLASSIFICATION NODE CLASSIFICATION

0
22 Oct 2019

End-to-End Neural Speaker Diarization with Permutation-Free Objectives

12 Sep 2019hitachi-speech/EEND

To realize such a model, we formulate the speaker diarization problem as a multi-label classification problem, and introduces a permutation-free objective function to directly minimize diarization errors without being suffered from the speaker-label permutation problem.

DOMAIN ADAPTATION MULTI-LABEL CLASSIFICATION SPEAKER DIARIZATION

75
12 Sep 2019