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Darts-Conformer: Towards Efficient Gradient-Based Neural Architecture Search For End-to-End ASR
Neural architecture search (NAS) has been successfully applied to tasks ...
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Context-aware Biaffine Localizing Network for Temporal Sentence Grounding
This paper addresses the problem of temporal sentence grounding (TSG), w...
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DPlis: Boosting Utility of Differentially Private Deep Learning via Randomized Smoothing
Deep learning techniques have achieved remarkable performance in wide-ra...
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Graph-Evolving Meta-Learning for Low-Resource Medical Dialogue Generation
Human doctors with well-structured medical knowledge can diagnose a dise...
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Adversarial Meta Sampling for Multilingual Low-Resource Speech Recognition
Low-resource automatic speech recognition (ASR) is challenging, as the l...
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F2Net: Learning to Focus on the Foreground for Unsupervised Video Object Segmentation
Although deep learning based methods have achieved great progress in uns...
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V3H: View Variation and View Heredity for Incomplete Multi-view Clustering
Real data often appear in the form of multiple incomplete views. Incompl...
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User-based Network Embedding for Collective Opinion Spammer Detection
Due to the huge commercial interests behind online reviews, a tremendous...
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Target Guided Emotion Aware Chat Machine
The consistency of a response to a given post at semantic-level and emot...
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Video-based Facial Expression Recognition using Graph Convolutional Networks
Facial expression recognition (FER), aiming to classify the expression p...
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Iterative Graph Self-Distillation
How to discriminatively vectorize graphs is a fundamental challenge that...
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How Important is the Train-Validation Split in Meta-Learning?
Meta-learning aims to perform fast adaptation on a new task through lear...
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Towards Theoretically Understanding Why SGD Generalizes Better Than ADAM in Deep Learning
It is not clear yet why ADAM-alike adaptive gradient algorithms suffer f...
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Hybrid Stochastic-Deterministic Minibatch Proximal Gradient: Less-Than-Single-Pass Optimization with Nearly Optimal Generalization
Stochastic variance-reduced gradient (SVRG) algorithms have been shown t...
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Communication-efficient Decentralized Machine Learning over Heterogeneous Networks
In the last few years, distributed machine learning has been usually exe...
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Evasion Attacks to Graph Neural Networks via Influence Function
Graph neural networks (GNNs) have achieved state-of-the-art performance ...
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Reinforcement Learning-based Black-Box Evasion Attacks to Link Prediction in Dynamic Graphs
Link prediction in dynamic graphs (LPDG) is an important research proble...
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Identity-Aware Attribute Recognition via Real-Time Distributed Inference in Mobile Edge Clouds
With the development of deep learning technologies, attribute recognitio...
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Fine-grained Iterative Attention Network for TemporalLanguage Localization in Videos
Temporal language localization in videos aims to ground one video segmen...
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Jointly Cross- and Self-Modal Graph Attention Network for Query-Based Moment Localization
Query-based moment localization is a new task that localizes the best ma...
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Theory-Inspired Path-Regularized Differential Network Architecture Search
Despite its high search efficiency, differential architecture search (DA...
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Federated Mutual Learning
Federated learning enables collaboratively training machine learning mod...
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Learning Decomposed Representation for Counterfactual Inference
One fundamental problem in the learning treatment effect from observatio...
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Improving GAN Training with Probability Ratio Clipping and Sample Reweighting
Despite success on a wide range of problems related to vision, generativ...
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Prototypical Contrastive Learning of Unsupervised Representations
This paper presents Prototypical Contrastive Learning (PCL), an unsuperv...
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Cocktail: Cost-efficient and Data Skew-aware Online In-Network Distributed Machine Learning for Intelligent 5G and Beyond
To facilitate the emerging applications in the 5G networks and beyond, m...
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Crowd Counting via Hierarchical Scale Recalibration Network
The task of crowd counting is extremely challenging due to complicated d...
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Dynamic Graph Correlation Learning for Disease Diagnosis with Incomplete Labels
Disease diagnosis on chest X-ray images is a challenging multi-label cla...
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Transfer Heterogeneous Knowledge Among Peer-to-Peer Teammates: A Model Distillation Approach
Peer-to-peer knowledge transfer in distributed environments has emerged ...
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Prophet: Proactive Candidate-Selection for Federated Learning by Predicting the Qualities of Training and Reporting Phases
Federated Learning (FL) is viewed as a promising technique for future di...
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Improving Generalization of Transformer for Speech Recognition with Parallel Schedule Sampling and Relative Positional Embedding
Transformer showed promising results in many sequence to sequence transf...
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Tell-the-difference: Fine-grained Visual Descriptor via a Discriminating Referee
In this paper, we investigate a novel problem of telling the difference ...
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Enhancing Neural Sequence Labeling with Position-Aware Self-Attention
Sequence labeling is a fundamental task in natural language processing a...
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Enhanced 3D convolutional networks for crowd counting
Recently, convolutional neural networks (CNNs) are the leading defacto m...
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Attend To Count: Crowd Counting with Adaptive Capacity Multi-scale CNNs
Crowd counting is a challenging task due to the large variations in crow...
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Exact Recovery of Tensor Robust Principal Component Analysis under Linear Transforms
This work studies the Tensor Robust Principal Component Analysis (TRPCA)...
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EnlightenGAN: Deep Light Enhancement without Paired Supervision
Deep learning-based methods have achieved remarkable success in image re...
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MHP-VOS: Multiple Hypotheses Propagation for Video Object Segmentation
We address the problem of semi-supervised video object segmentation (VOS...
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A Stochastic Trust Region Method for Non-convex Minimization
We target the problem of finding a local minimum in non-convex finite-su...
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Gradient Scheduling with Global Momentum for Non-IID Data Distributed Asynchronous Training
Distributed asynchronous offline training has received widespread attent...
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De-Health: All Your Online Health Information Are Belong to Us
In this paper, we study the privacy of online health data. We present a ...
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FDI: Quantifying Feature-based Data Inferability
Motivated by many existing security and privacy applications, e.g., netw...
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Bayesian CycleGAN via Marginalizing Latent Sampling
Recent techniques built on Generative Adversarial Networks (GANs) like C...
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Modality Attention for End-to-End Audio-visual Speech Recognition
Audio-visual speech recognition (AVSR) system is thought to be one of th...
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An Online Attention-based Model for Speech Recognition
Attention-based end-to-end (E2E) speech recognition models such as Liste...
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Exploring RNN-Transducer for Chinese Speech Recognition
End-to-end approaches have drawn much attention recently for significant...
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Spatio-temporal Edge Service Placement: A Bandit Learning Approach
Shared edge computing platforms deployed at the radio access network are...
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Spatial-Temporal Synergic Residual Learning for Video Person Re-Identification
We tackle the problem of person re-identification in video setting in th...
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SmartSeed: Smart Seed Generation for Efficient Fuzzing
Fuzzing is an automated application vulnerability detection method. For ...
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Adaptive Fog Configuration for the Industrial Internet of Things
Industrial Fog computing deploys various industrial services, such as au...
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