Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: Joint Generative-Discriminative Aggregation Model for Multi-Option Crowd Labels
Community-based bayesian aggregation models for crowdsourcing
Multi-label Classification: Dealing with Imbalance by Combining Labels
Joint Feature Selection and Classification for Multilabel Learning
Multi-objective convolutional learning for face labeling
A Randomized Approach for Crowdsourcing in the Presence of Multiple Views
Cumulative Attribute Space for Age and Crowd Density Estimation
Data Driven Evaluation of Crowds
Multi-Instance Multi-Label Learning with Application to Scene Classification
Socially Constrained Structural Learning for Groups Detection in Crowd
SemanticFusion: Joint Labeling, Tracking and Mapping
Online crowdsourcing: Rating annotators and obtaining cost-effective labels
Deep Extreme Multi-label Learning
Dynamic Label Propagation for Semi-supervised Multi-class Multi-label Classification
Multi-label Learning
An intelligent crowd-worker selection approach for reliable content labeling of food images
Simultaneously Combining Multi-view Multi-label Learning with Maximum Margin Classification
Active Learning from Crowds
Exploiting Generative Models in Discriminative Classifiers
Unconstrained Multimodal Multi-Label Learning
Deep Hybrid Models : Bridging Discriminative and Generative Approaches
Mind Your Language: Learning Visually Grounded Dialog in a Multi-Agent Setting.
Active Learning from Crowds
Passive exoskeletons for assisting limb movement
Goal-Oriented Chatbot Dialog Management Bootstrapping with Transfer Learning
Low Cost Heart Multi Parameter Monitoring and Arrhythmia Analysis Using MATLAB