Representation Learning and Embedding
Episode Adaptive Embedding Networks for Few-shot Learning
Universal Representation for Code
Self-supervised Adaptive Aggregator Learning on Graph
A Fast Algorithm for Simultaneous Sparse Approximation
STEPs-RL: Speech-Text Entanglement for Phonetically Sound Representation Learning
RW-GCN: Training Graph Convolution Networks with biased random walk for Semi-Supervised Classification
Loss-aware Pattern Inference: A Correction on the Wrongly Claimed Limitations of Embedding Models
SST-GNN: Simplified Spatio-temporal Traffic forecasting model using Graph Neural Network
VIKING: Adversarial Attack on Network Embeddings via Supervised Network Poisoning
Self-supervised Graph Representation Learning with Variational Inference
Manifold Approximation and Projection by Maximizing Graph Information
Learning Attention-based Translational Knowledge Graph Embedding via Nonlinear Dynamic Mapping
Multi-Grained Dependency Graph Neural Network for Chinese Open Information Extraction
Human-Understandable Decision Making for Visual Recognition
LightCAKE: A Lightweight Framework for Context-Aware Knowledge Graph Embedding
Transferring Domain Knowledge with an Adviser in Continuous Tasks
Inferring Hierarchical Mixture Structures: A Bayesian Nonparametric Approach
Quality Control for Hierarchical Classification with Incomplete Annotations
Learning from Data
Learning Discriminative Features using Multi-label Dual Space
AutoCluster: Meta-learning Based Ensemble Method for Automated Unsupervised Clustering
BanditRank: Learning to Rank Using Contextual Bandits
A compressed and accelerated SegNet for plant leaf disease segmentation: A Differential Evolution based approach
Meta-Context Transformers for Domain-Specific Response Generation
A Multi-task Kernel Learning Algorithm for Survival Analysis
Meta-data Augmentation based Search Strategy through Generative Adversarial Network for AutoML Model Selection
Tree-Capsule: Tree-Structured Capsule Network for Improving Relation Extraction
Rule Injection-based Generative Adversarial Imitation Learning for Knowledge Graph Reasoning
Hierarchical Self Attention Based Autoencoder for Open-Set Human Activity Recognition
Reinforced Natural Language Inference for Distantly Supervised Relation Classification
SaGCN: Structure-aware Graph Convolution Network for Document-level Relation Extraction
Addressing the class imbalance problem in medical image segmentation via accelerated Tversky loss function
Incorporating Relational Knowledge in Explainable Fake News Detection
Incorporating Syntactic Information into Relation Representations for Enhanced Relation Extraction.