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Deep Learning in the Era of Edge Computing: Challenges and Opportunities
The era of edge computing has arrived. Although the Internet is the back...
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Natural Language QA Approaches using Reasoning with External Knowledge
Question answering (QA) in natural language (NL) has been an important a...
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Microscopic fine-grained instance classification through deep attention
Fine-grained classification of microscopic image data with limited sampl...
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FLO: Fast and Lightweight Hyperparameter Optimization for AutoML
Integrating ML models in software is of growing interest. Building accur...
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Accelerating Physics-Informed Neural Network Training with Prior Dictionaries
Physics-Informed Neural Networks (PINNs) can be regarded as general-purp...
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Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning
Current state-of-the-art object detectors can have significant performan...
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On the Anomalous Generalization of GANs
Generative models, especially Generative Adversarial Networks (GANs), ha...
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360-Indoor: Towards Learning Real-World Objects in 360° Indoor Equirectangular Images
While there are several widely used object detection datasets, current c...
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Relationship-Aware Spatial Perception Fusion for Realistic Scene Layout Generation
The significant progress on Generative Adversarial Networks (GANs) have ...
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SQuINTing at VQA Models: Interrogating VQA Models with Sub-Questions
Existing VQA datasets contain questions with varying levels of complexit...
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GPT-GNN: Generative Pre-Training of Graph Neural Networks
Graph neural networks (GNNs) have been demonstrated to be powerful in mo...
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D2D-Enabled Data Sharing for Distributed Machine Learning at Wireless Network Edge
Mobile edge learning is an emerging technique that enables distributed e...
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MixPath: A Unified Approach for One-shot Neural Architecture Search
The expressiveness of search space is a key concern in neural architectu...
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Subspace approximation with outliers
The subspace approximation problem with outliers, for given n points in ...
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Neural Network Compression Via Sparse Optimization
The compression of deep neural networks (DNNs) to reduce inference cost ...
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Security and Machine Learning in the Real World
Machine learning (ML) models deployed in many safety- and business-criti...
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Minmax Optimization: Stable Limit Points of Gradient Descent Ascent are Locally Optimal
Minmax optimization, especially in its general nonconvex-nonconcave form...
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Appending Adversarial Frames for Universal Video Attack
There have been many efforts in attacking image classification models wi...
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DSRGAN: Explicitly Learning Disentangled Representation of Underlying Structure and Rendering for Image Generation without Tuple Supervision
We focus on explicitly learning disentangled representation for natural ...
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Learning Pyramid-Context Encoder Network for High-Quality Image Inpainting
High-quality image inpainting requires filling missing regions in a dama...
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Learning Spatial Awareness to Improve Crowd Counting
The aim of crowd counting is to estimate the number of people in images ...
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Instance-wise Depth and Motion Learning from Monocular Videos
We present an end-to-end joint training framework that explicitly models...
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Non-local Recurrent Neural Memory for Supervised Sequence Modeling
Typical methods for supervised sequence modeling are built upon the recu...
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An Anatomy of Graph Neural Networks Going Deep via the Lens of Mutual Information: Exponential Decay vs. Full Preservation
Graph Convolutional Network (GCN) has attracted intensive interests rece...
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Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization
Domain generalization is the problem of machine learning when the traini...
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The Non-IID Data Quagmire of Decentralized Machine Learning
Many large-scale machine learning (ML) applications need to train ML mod...
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NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results
This paper reviews the NTIRE 2020 challenge on real image denoising with...
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Graph Policy Network for Transferable Active Learning on Graphs
Graph neural networks (GNNs) have been attracting increasing popularity ...
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Densely Semantically Aligned Person Re-Identification
We propose a densely semantically aligned person re-identification (re-I...
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Logic Rules Powered Knowledge Graph Embedding
Large scale knowledge graph embedding has attracted much attention from ...
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Learning Residual Flow as Dynamic Motion from Stereo Videos
We present a method for decomposing the 3D scene flow observed from a mo...
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Affect-based Intrinsic Rewards for Learning General Representations
Positive affect has been linked to increased interest, curiosity and sat...
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Towards Omni-Supervised Face Alignment for Large Scale Unlabeled Videos
In this paper, we propose a spatial-temporal relational reasoning networ...
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Animating Face using Disentangled Audio Representations
All previous methods for audio-driven talking head generation assume the...
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An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare
Reinforcement Learning (RL) has recently been applied to sequential esti...
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RNNbow: Visualizing Learning via Backpropagation Gradients in Recurrent Neural Networks
We present RNNbow, an interactive tool for visualizing the gradient flow...
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Disentangling Interpretable Generative Parameters of Random and Real-World Graphs
While a wide range of interpretable generative procedures for graphs exi...
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AirSim Drone Racing Lab
Autonomous drone racing is a challenging research problem at the interse...
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MetaFuse: A Pre-trained Fusion Model for Human Pose Estimation
Cross view feature fusion is the key to address the occlusion problem in...
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Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks
Sampling methods (e.g., node-wise, layer-wise, or subgraph) has become a...
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Learning Calibratable Policies using Programmatic Style-Consistency
We study the important and challenging problem of controllable generatio...
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Deformable Kernels: Adapting Effective Receptive Fields for Object Deformation
Convolutional networks are not aware of an object's geometric variations...
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STANCY: Stance Classification Based on Consistency Cues
Controversial claims are abundant in online media and discussion forums....
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Resource-Efficient Neural Networks for Embedded Systems
While machine learning is traditionally a resource intensive task, embed...
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Towards information-rich, logical text generation with knowledge-enhanced neural models
Text generation system has made massive promising progress contributed b...
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Explainable Deep Classification Models for Domain Generalization
Conventionally, AI models are thought to trade off explainability for lo...
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Stochastic Gradient Descent Escapes Saddle Points Efficiently
This paper considers the perturbed stochastic gradient descent algorithm...
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Stochastic Online Learning with Probabilistic Graph Feedback
We consider a problem of stochastic online learning with general probabi...
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Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set
Recently, deep learning based 3D face reconstruction methods have shown ...
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DBRec: Dual-Bridging Recommendation via Discovering Latent Groups
In recommender systems, the user-item interaction data is usually sparse...
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