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Locally Free Weight Sharing for Network Width Search
Searching for network width is an effective way to slim deep neural netw...
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Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search
Most differentiable neural architecture search methods construct a super...
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Contrastive Learning Improves Critical Event Prediction in COVID-19 Patients
Machine Learning (ML) models typically require large-scale, balanced tra...
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MCMC Confidence Intervals and Biases
The recent paper "Simple confidence intervals for MCMC without CLTs" by ...
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Biomedical Knowledge Graph Refinement with Embedding and Logic Rules
Currently, there is a rapidly increasing need for high-quality biomedica...
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3D Registration for Self-Occluded Objects in Context
While much progress has been made on the task of 3D point cloud registra...
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Explicitly Learning Topology for Differentiable Neural Architecture Search
Differentiable neural architecture search (DARTS) has gained much succes...
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A Method to Generate High Precision Mesh Model and RGB-D Datasetfor 6D Pose Estimation Task
Recently, 3D version has been improved greatly due to the development of...
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Data Agnostic Filter Gating for Efficient Deep Networks
To deploy a well-trained CNN model on low-end computation edge devices, ...
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ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding
Neural architecture search (NAS) aims to produce the optimal sparse solu...
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Robust Finite Mixture Regression for Heterogeneous Targets
Finite Mixture Regression (FMR) refers to the mixture modeling scheme wh...
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Domain Agnostic Learning for Unbiased Authentication
Authentication is the task of confirming the matching relationship betwe...
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Deep Representation Learning of Patient Data from Electronic Health Records (EHR): A Systematic Review
Patient representation learning refers to learning a dense mathematical ...
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Suicide Risk Modeling with Uncertain Diagnostic Records
Motivated by the pressing need for suicide prevention through improving ...
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HACCLE: An Ecosystem for Building Secure Multi-Party Computations
Cryptographic techniques have the potential to enable distrusting partie...
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A Federated Multi-View Deep Learning Framework for Privacy-Preserving Recommendations
Privacy-preserving recommendations are recently gaining momentum, since ...
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The Coupling/Minorization/Drift Approach to Markov Chain Convergence Rates
This review paper provides an introduction of Markov chains and their co...
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A(DP)^2SGD: Asynchronous Decentralized Parallel Stochastic Gradient Descent with Differential Privacy
As deep learning models are usually massive and complex, distributed lea...
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Dynamic Knowledge Distillation for Black-box Hypothesis Transfer Learning
In real world applications like healthcare, it is usually difficult to b...
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Visualizing Deep Graph Generative Models for Drug Discovery
Drug discovery aims at designing novel molecules with specific desired p...
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MoFlow: An Invertible Flow Model for Generating Molecular Graphs
Generating molecular graphs with desired chemical properties driven by d...
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xOrder: A Model Agnostic Post-Processing Framework for Achieving Ranking Fairness While Maintaining Algorithm Utility
Algorithmic fairness has received lots of interests in machine learning ...
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gPAV-Based Unconditionally Energy-Stable Schemes for the Cahn-Hilliard Equation: Stability and Error Analysis
We present several first-order and second-order numerical schemes for th...
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Why is Attention Not So Attentive?
Attention-based methods have played an important role in model interpret...
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Adversarial Infidelity Learning for Model Interpretation
Model interpretation is essential in data mining and knowledge discovery...
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Learning 3D-3D Correspondences for One-shot Partial-to-partial Registration
While 3D-3D registration is traditionally tacked by optimization-based m...
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General-Purpose User Embeddings based on Mobile App Usage
In this paper, we report our recent practice at Tencent for user modelin...
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Eigendecomposition-Free Training of Deep Networks for Linear Least-Square Problems
Many classical Computer Vision problems, such as essential matrix comput...
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A Framework for Behavior Privacy Preserving in Radio Frequency Signal
Recent years have witnessed the bloom development of the human-centered ...
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Auto-Ensemble: An Adaptive Learning Rate Scheduling based Deep Learning Model Ensembling
Ensembling deep learning models is a shortcut to promote its implementat...
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GreedyNAS: Towards Fast One-Shot NAS with Greedy Supernet
Training a supernet matters for one-shot neural architecture search (NAS...
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CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection
Keypoint-based detectors have achieved pretty-well performance. However,...
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Gated Fusion Network for Degraded Image Super Resolution
Single image super resolution aims to enhance image quality with respect...
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A Coarse-to-Fine Adaptive Network for Appearance-Based Gaze Estimation
Human gaze is essential for various appealing applications. Aiming at mo...
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PPDM: Parallel Point Detection and Matching for Real-time Human-Object Interaction Detection
We propose a single-stage Human-Object Interaction (HOI) detection metho...
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Explicit-Blurred Memory Network for Analyzing Patient Electronic Health Records
In recent years, we have witnessed an increased interest in temporal mod...
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Federated Learning for Healthcare Informatics
Recent rapid development of medical informatization and the correspondin...
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Interactive Attention for Semantic Text Matching
Semantic text matching, which matches a target text to a source text, is...
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Coreference Resolution as Query-based Span Prediction
In this paper, we present an accurate and extensible approach for the co...
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GRAPHENE: A Precise Biomedical Literature Retrieval Engine with Graph Augmented Deep Learning and External Knowledge Empowerment
Effective biomedical literature retrieval (BLR) plays a central role in ...
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A Real-Time Cross-modality Correlation Filtering Method for Referring Expression Comprehension
Referring expression comprehension aims to localize the object instance ...
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Research on Autonomous Maneuvering Decision of UCAV based on Approximate Dynamic Programming
Unmanned aircraft systems can perform some more dangerous and difficult ...
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Learning Reinforced Attentional Representation for End-to-End Visual Tracking
Despite the fact that tremendous advances have been made by numerous rec...
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Interpretable Cognitive Diagnosis with Neural Network
In intelligent education systems, one key issue is to discover students'...
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Interpretable Cognitive Diagnosis with Neural Network for Intelligent Educational Systems
In intelligent education systems, one key issue is to discover students'...
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Neural Dynamics on Complex Networks
We introduce a deep learning model to learn continuous-time dynamics on ...
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SFSegNet: Parse Freehand Sketches using Deep Fully Convolutional Networks
Parsing sketches via semantic segmentation is attractive but challenging...
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Method of Contraction-Expansion (MOCE) for Simultaneous Inference in Linear Models
Simultaneous inference after model selection is of critical importance t...
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CU-Net: Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation
This paper proposes a novel cascaded U-Net for brain tumor segmentation....
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Non-technical Loss Detection with Statistical Profile Images Based on Semi-supervised Learning
In order to keep track of the operational state of power grid, the world...
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