Interesting of AAAI accepted papers

AAAI Accepted Papers 관심있는 논문

AAAI Accepted Papers  관심있는 논문

CircConv: A Structured Convolution with Low Complexity 

Look Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition

Transferable Curriculum for Weakly-Supervised Domain Adaptation

Weighted Channel Dropout for Regularization of Deep Convolutional Neural Network 

Zero-Shot Object Detection with Textual Descriptions

Object Detection based on Region Decomposition and Assembly 

Single-Label Multi-Class Image Classification by Deep Logistic Regression 

DeepChannel: Salience Estimation by Contrastive Learning for Extractive Document Summarization

Augmenting Markov Decision Processes with Advising


Attention-based Multi-Context Guiding for Few-Shot Semantic Segmentation


Multi-view Information-theoretic Co-clustering for Co-occurrence Data


How Does Knowledge of the AUC Constrain the Set of Possible Ground-truth Labelings? 

MEAL: Multi-Model Ensemble via Adversarial Learning


Solving Imperfect-Information Games with Discounted Counterfactual Regret Minimization 

Adversarial Dropout for Recurrent Neural Networks


Adversarial Learning for Weakly-Supervised Social Network Alignment


Perceptual-Sensitive GAN for Generating Adversarial Patches


Sentence-wise Smooth Regularization for Sequence to Sequence Learning


Residual Attribute Attention Network for Face Image Super-Resolution


Embedding Uncertain Knowledge Graphs


Fully Convolutional Network with Multi-Step Reinforcement Learning for Image Processing 

Towards Optimal Fine Grained Retrieval via Decorrelated Centralized Loss with Normalize- Scale layer


Hybrid Attention-based Prototypical Networks for Noisy Few-Shot Relation Classification 

Safeguarded Dynamic Label Regression for Noisy Supervision


Learning to Localize Objects with Noisy Labeled Instances


Similarity Learning via Kernel Preserving Embedding


An Affect-Rich Neural Conversational Model with Biased Attention and Weighted Cross- Entropy Loss


3D Object Detection Using Scale Invariant and Feature Reweighting Networks 

Deep Bayesian Optimization on Attributed Graphs


Deep Latent Generative Models For Energy Disaggregation


Zero-Shot Adaptive Transfer for Conversational Language Understanding 

Efficient Region Embedding with Multi-view Spatial Networks: A Perspective of Locality- Constrained Spatial Autocorrelations


Robust Metric Learning on Grassmann Manifolds with Generalization Guarantees


A Dual Attention Network with Semantic Embedding for Few-shot Learning


Hierarchical Attention Network for Image Captioning


Adversarial Label Learning


Knowledge Distillation with Adversarial Samples Supporting Decision Boundary 

Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons 

Adaptive Region Embedding for Text Classification


Soft Facial Landmark Detection by Label Distribution Learning 

Constrained Generation via Metropolis-Hastings Sampling


DAN : Deep Attention Neural Network for News Recommendation


Densely Supervised Grasp Detector (DSGD)


Outlier Aware Network Embedding for Attributed Networks


Gradient Harmonized Single-stage Detector


Non-Local Context Encoder: Robust Biomedical Image Segmentation against Adversarial Attacks


A Two-Stream Mutual Attention Network for Semi-supervised Biomedical Segmentation with Noisy Labels


Variance Reduction in Monte Carlo Regret Minimization for Extensive Games using Baselines


Self-Supervised Video Representation Learning with Space-Time Cubic Puzzles 

From Zero-Shot Learning to Cold-Start Recommendation


Discriminative Feature Learning for Unsupervised Video Summarization


Backbone Can Not be Trained at Once: Rolling Back to Pre-trained Network for Person Re-Identification


Memory-Augmented Temporal Dynamic Learning for Action Recognition


Video Object Detection with Locally-Weighted Deformable Neighbors


AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black- box Neural Networks


Learning Anytime Predictions in Neural Networks via Adaptive Loss Balancing


Image Block Augmentation for One-Shot Learning


Online Embedding Compression for Text Classification using Low Rank Matrix Factorization


Depthwise Convolution is All You Need for Learning Multiple Visual Domains


Difficulty-Aware Attention Network with Confidence Learning for Medical Image Segmentation


Unsupervised Domain Adaptation by Matching Distributions based on the Maximum Mean Discrepancy via Unilateral Transformations


Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation


Fuzzy-Classification Assisted Solution Preselection in Evolutionary Optimization 

Semantic Adversarial Network with Multi-scale Pyramid Attention for Video Classification 

Residual Invertible Spatio-Temporal Network For Video Super-Resolution


MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization 

Dirichlet Multinomial Mixture with Variational Manifold Regularization: Topic Modeling over Short Texts


Dual Semi-Supervised Learning for Facial Action Unit Recognition


Fine-grained search space classification for hard enumeration variants of subset problems 

On-Line Learning of Linear Dynamical Systems: Exponential Forgetting in Kalman Filters 

I Know the Relationships: Zero-Shot Action Recognition via Two-Stream Graph Convolutional Networks and Knowledge Graphs


Long Short-Term Memory with Dynamic Skip Connections


Argumentation for Explainable Scheduling


A Generalized Language Model in Tensor Space


Greedy maximization of functions with bounded curvature under partition matroid constraints.


Tensor Ring Decomposition with Rank Minimization on Latent Space: An Efficient Approach for Tensor Completion


Submodular Optimization Over Streams with Inhomogeneous Decays


Learning Object Context for Dense Captioning


SDRL: Interpretable and Data-efficient Deep Reinforcement Learning Leveraging Symbolic Planning


Generalized Batch Normalization


Task Embedded Coordinate Update: A Realizable Framework for Multivariate Non-convex Optimization 

Interleave Variational Optimization with Monte Carlo Sampling: A Tale of Two Approximate Inference Paradigms


LabelForest: Non-Parametric Semi-Supervised Learning for Activity Recognition 

Exploiting Local Feature Patterns for Unsupervised Domain Adaptation


Smooth Deep Image Generator from Noises


Dual-view Ranking with Hardness Assessment for Zero-shot Learning


f-Similarity Preservation Loss for Soft Labels: A Demonstration on Cross-Corpus Speech Emotion Recognition


Angular Triplet-Center Loss for Multi-view 3D Shape Retrieval


Latent Dirichlet Allocation for Internet Price War


Multiple Saliency and Channel Sensitivity Network for Aggregated Convolutional Feature 

Quantifying Uncertainties in Natural Language Processing Tasks 

Data-Distortion Guided Self-Distillation for Deep Neural Networks


ClusterGAN : Latent Space Clustering in Generative Adversarial Networks


Few-Shot Image and Sentence Matching via Gated Visual-Semantic Embedding


Pareto Optimization for Subset Selection with Dynamic Cost Constraints


Coupled CycleGAN: Unsupervised Hashing Network for Cross-Modal Retrieval


Partial Multi-Label Learning by Low-Rank and Sparse Decomposition


Random Walk Decay Centrality


A Sequential Set Generation Method for Predicting Set-Valued Outputs


Inter-Class Angular Loss for Convolutional Neural Networks 

Meta Learning for Image Captioning


Transferable Interactive Memory Network for Domain Adaptation in Fine-grained Opinion Extraction 

Explainable Recommendation Through Attentive Multi-View Learning


Partial Label Learning with Self-Guided Retraining


Mode Variational LSTM Robust to Unseen Modes of Variation: Application to Facial Expression Recognition


SEGAN: Structure-Enhanced Generative Adversarial Network for Compressed Sensing MRI Reconstruction


Deep Embedding Features for Salient Object Detection


Adaptive Proximal Average based Variance Reducing Stochastic Methods for Optimization with Composite Regularization


Exploiting synthetically generated data with semi-supervised learning for small and imbalanced datasets


A Nonconvex Projection Method for Robust PCA


Robustness Guarantees for Bayesian Inference with Gaussian Processes


Robust Optimization over Multiple Domains 

Practical Algorithms for Multi-stage Voting Rules with Parallel Universes Tiebreaking 

Measurement Maximizing Adaptive Sampling With Risk Bounding Functions 

Generalized Distance Bribery


Zero-shot Neural Transfer for Cross-lingual Entity Linking


Triple Classification Using Regions And Fine-Grained Entity Typing


PCGAN: Partition-Controlled Human Image Generation


Spatially Invariant Unsupervised Object Detection with Convolutional Neural Networks 

Improving GAN with neighbors embedding and gradient matching


Interpretable Predictive Modeling for Climate Variables with Weighted Lasso 

ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning


Marginal Inference in Continuous Markov Random Fields using Mixtures


WK-VQA: World Knowledge-enabled Visual Question Answering


Matrix Completion for Graph-Based Deep Semi-Supervised Learning


A non-convex optimization approach to correlation clustering


High Dimensional Clustering with $r$-nets


Learning Phenotypes and Dynamic Patient Representations via RNN Regularized Collective Non-negative Tensor Factorization


Hierarchical Context enabled Recurrent Neural Network for Recommendation 

Randomized Strategies for Robust Combinatorial Optimization


Learning A Key-Value Memory Co-Attention Matching Network for Person Re- Identification


Direct Training for Spiking Neural Networks: Faster, Larger, Better

Bounding Uncertainty for Active Batch Selection

Modeling Local Dependence in Natural Language with Multi-channel Recurrent Neural Networks


Region-based Message Exploration over Spatio-Temporal Data Streams