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Bayesian Inference with Certifiable Adversarial Robustness
We consider adversarial training of deep neural networks through the len...
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Towards Robust Neural Networks via Close-loop Control
Despite their success in massive engineering applications, deep neural n...
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Semantic Disentangling Generalized Zero-Shot Learning
Generalized Zero-Shot Learning (GZSL) aims to recognize images from both...
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Entropy-Based Uncertainty Calibration for Generalized Zero-Shot Learning
Compared to conventional zero-shot learning (ZSL) where recognising unse...
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Active Sampling for Accelerated MRI with Low-Rank Tensors
Magnetic resonance imaging (MRI) is a powerful imaging modality that rev...
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TROJANZOO: Everything you ever wanted to know about neural backdoors (but were afraid to ask)
Neural backdoors represent one primary threat to the security of deep le...
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Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings
Cycle-consistent training is widely used for jointly learning a forward ...
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Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning
Contrastive learning methods for unsupervised visual representation lear...
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Overview of the Ninth Dialog System Technology Challenge: DSTC9
This paper introduces the Ninth Dialog System Technology Challenge (DSTC...
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Sparse Tucker Tensor Decomposition on a Hybrid FPGA-CPU Platform
Recommendation systems, social network analysis, medical imaging, and da...
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End-to-End Variational Bayesian Training of Tensorized Neural Networks with Automatic Rank Determination
Low-rank tensor decomposition is one of the most effective approaches to...
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DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs
Graph neural networks (GNN) have shown great success in learning from gr...
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CoLAKE: Contextualized Language and Knowledge Embedding
With the emerging branch of incorporating factual knowledge into pre-tra...
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Efficient Estimation of General Treatment Effects using Neural Networks with A Diverging Number of Confounders
The estimation of causal effects is a primary goal of behavioral, social...
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Dual-constrained Deep Semi-Supervised Coupled Factorization Network with Enriched Prior
Nonnegative matrix factorization is usually powerful for learning the "s...
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High-Dimensional Uncertainty Quantification via Active and Rank-Adaptive Tensor Regression
Uncertainty quantification based on stochastic spectral methods suffers ...
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Robust and Secure Communications in Intelligent Reflecting Surface Assisted NOMA networks
This letter investigates secure transmission in an intelligent reflectin...
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FeatGraph: A Flexible and Efficient Backend for Graph Neural Network Systems
Graph neural networks (GNNs) are gaining increasing popularity as a prom...
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Trojaning Language Models for Fun and Profit
Recent years have witnessed a new paradigm of building natural language ...
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Adversarial Bipartite Graph Learning for Video Domain Adaptation
Domain adaptation techniques, which focus on adapting models between dis...
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RepPoints V2: Verification Meets Regression for Object Detection
Verification and regression are two general methodologies for prediction...
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Parametric Instance Classification for Unsupervised Visual Feature Learning
This paper presents parametric instance classification (PIC) for unsuper...
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Disentangled Non-Local Neural Networks
The non-local block is a popular module for strengthening the context mo...
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Dual-level Semantic Transfer Deep Hashing for Efficient Social Image Retrieval
Social network stores and disseminates a tremendous amount of user share...
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CycleGT: Unsupervised Graph-to-Text and Text-to-Graph Generation via Cycle Training
Two important tasks at the intersection of knowledge graphs and natural ...
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Relation of the Relations: A New Paradigm of the Relation Extraction Problem
In natural language, often multiple entities appear in the same text. Ho...
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Repurpose Open Data to Discover Therapeutics for COVID-19 using Deep Learning
There have been more than 850,000 confirmed cases and over 48,000 deaths...
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Learning Goal-oriented Dialogue Policy with Opposite Agent Awareness
Most existing approaches for goal-oriented dialogue policy learning used...
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DGL-KE: Training Knowledge Graph Embeddings at Scale
Knowledge graphs have emerged as a key abstraction for organizing inform...
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Negative Margin Matters: Understanding Margin in Few-shot Classification
This paper introduces a negative margin loss to metric learning based fe...
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Spatially Adaptive Inference with Stochastic Feature Sampling and Interpolation
In the feature maps of CNNs, there commonly exists considerable spatial ...
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Recent Advances and Challenges in Task-oriented Dialog System
Due to the significance and value in human-computer interaction and natu...
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CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset
To advance multi-domain (cross-domain) dialogue modeling as well as alle...
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Transformer on a Diet
Transformer has been widely used thanks to its ability to capture sequen...
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Race, Gender and Beauty: The Effect of Information Provision on Online Hiring Biases
We conduct a study of hiring bias on a simulation platform where we ask ...
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Dense RepPoints: Representing Visual Objects with Dense Point Sets
We present an object representation, called Dense RepPoints, for flexibl...
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Fast DenseNet: Towards Efficient and Accurate Text Recognition with Fast Dense Networks
Convolutional Recurrent Neural Network (CRNN) is a popular network for r...
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Fully-Convolutional Intensive Feature Flow Neural Network for Text Recognition
The Deep Convolutional Neural Networks (CNNs) have obtained a great succ...
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Deep Self-representative Concept Factorization Network for Representation Learning
In this paper, we investigate the unsupervised deep representation learn...
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Quantum-Inspired Hamiltonian Monte Carlo for Bayesian Sampling
Hamiltonian Monte Carlo (HMC) is an efficient Bayesian sampling method t...
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Multi-Scale Self-Attention for Text Classification
In this paper, we introduce the prior knowledge, multi-scale structure, ...
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Discriminative Local Sparse Representation by Robust Adaptive Dictionary Pair Learning
In this paper, we propose a structured Robust Adaptive Dic-tionary Pair ...
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Transductive Zero-Shot Hashing for Multi-Label Image Retrieval
Hash coding has been widely used in approximate nearest neighbor search ...
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Learning from the Past: Continual Meta-Learning via Bayesian Graph Modeling
Meta-learning for few-shot learning allows a machine to leverage previou...
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BP-Transformer: Modelling Long-Range Context via Binary Partitioning
The Transformer model is widely successful on many natural language proc...
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Deep Collaborative Discrete Hashing with Semantic-Invariant Structure
Existing deep hashing approaches fail to fully explore semantic correlat...
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Active Subspace of Neural Networks: Structural Analysis and Universal Attacks
Active subspace is a model reduction method widely used in the uncertain...
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Cross-Lingual Contextual Word Embeddings Mapping With Multi-Sense Words In Mind
Recent work in cross-lingual contextual word embedding learning cannot h...
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A Deep Learning Framework for Pricing Financial Instruments
We propose an integrated deep learning architecture for the stock moveme...
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Learning Structured Twin-Incoherent Twin-Projective Latent Dictionary Pairs for Classification
In this paper, we extend the popular dictionary pair learning (DPL) into...
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