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Unsupervised Extractive Summarization by Pre-training Hierarchical Transformers
Unsupervised extractive document summarization aims to select important ...
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Streaming Graph Neural Networks via Continual Learning
Graph neural networks (GNNs) have achieved strong performance in various...
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Hybrid-Attention Guided Network with Multiple Resolution Features for Person Re-Identification
Extracting effective and discriminative features is very important for a...
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Multi-Authority Ciphertext-Policy Attribute Based Encryption With Accountability
Attribute-based encryption (ABE) is a promising tool for implementing fi...
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Unsupervised Deformable Medical Image Registration via Pyramidal Residual Deformation Fields Estimation
Deformation field estimation is an important and challenging issue in ma...
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Multi-Task Reinforcement Learning with Soft Modularization
Multi-task learning is a very challenging problem in reinforcement learn...
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SaccadeNet: A Fast and Accurate Object Detector
Object detection is an essential step towards holistic scene understandi...
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Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning
In multi-agent games, the complexity of the environment can grow exponen...
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SQLFlow: A Bridge between SQL and Machine Learning
Industrial AI systems are mostly end-to-end machine learning (ML) workfl...
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Influence-Based Multi-Agent Exploration
Intrinsically motivated reinforcement learning aims to address the explo...
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PPGAN: Privacy-preserving Generative Adversarial Network
Generative Adversarial Network (GAN) and its variants serve as a perfect...
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Emergent Tool Use From Multi-Agent Autocurricula
Through multi-agent competition, the simple objective of hide-and-seek, ...
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Bayesian Relational Memory for Semantic Visual Navigation
We introduce a new memory architecture, Bayesian Relational Memory (BRM)...
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Fairness in Recommendation Ranking through Pairwise Comparisons
Recommender systems are one of the most pervasive applications of machin...
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Dominant Dataset Selection Algorithms for Time-Series Data Based on Linear Transformation
With the explosive growth of time-series data, the scale of time-series ...
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Deep Reinforcement Learning for Green Security Games with Real-Time Information
Green Security Games (GSGs) have been proposed and applied to optimize p...
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Learning and Planning with a Semantic Model
Building deep reinforcement learning agents that can generalize and adap...
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Robust Fuzzy-Learning For Partially Overlapping Channels Allocation In UAV Communication Networks
In this paper, we consider a mesh-structured unmanned aerial vehicle (UA...
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Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms
Despite the recent successes of probabilistic programming languages (PPL...
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On Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms
Despite of the recent successes of probabilistic programming languages (...
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Near-Linear Time Local Polynomial Nonparametric Estimation
Local polynomial regression (Fan & Gijbels, 1996) is an important class ...
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Building Generalizable Agents with a Realistic and Rich 3D Environment
Towards bridging the gap between machine and human intelligence, it is o...
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Neural Block Sampling
Efficient Monte Carlo inference often requires manual construction of mo...
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CoupleNet: Coupling Global Structure with Local Parts for Object Detection
The region-based Convolutional Neural Network (CNN) detectors such as Fa...
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Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
We explore deep reinforcement learning methods for multi-agent domains. ...
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Swift: Compiled Inference for Probabilistic Programming Languages
A probabilistic program defines a probability measure over its semantic ...
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Towards Practical Bayesian Parameter and State Estimation
Joint state and parameter estimation is a core problem for dynamic Bayes...
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Value Iteration Networks
We introduce the value iteration network (VIN): a fully differentiable n...
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Adaptive Compressive Tracking via Online Vector Boosting Feature Selection
Recently, the compressive tracking (CT) method has attracted much attent...
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Robust Visual Tracking via Convolutional Networks
Deep networks have been successfully applied to visual tracking by learn...
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Dual-Space Analysis of the Sparse Linear Model
Sparse linear (or generalized linear) models combine a standard likeliho...
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Agnostic Learning of Monomials by Halfspaces is Hard
We prove the following strong hardness result for learning: Given a dist...
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