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Knowledge-guided Open Attribute Value Extraction with Reinforcement Learning
Open attribute value extraction for emerging entities is an important bu...
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Worst-Case-Aware Curriculum Learning for Zero and Few Shot Transfer
Multi-task transfer learning based on pre-trained language encoders achi...
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Augmented Gaussian Random Field: Theory and Computation
We provide a rigorous theoretical foundation for incorporating data of o...
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DeepFaceLab: A simple, flexible and extensible face swapping framework
DeepFaceLab is an open-source deepfake system created by iperov for face...
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Error Model of Radio Fingerprint and PDR Fusion Indoor Localization
Multi-source fusion positioning is one of the technical frameworks for o...
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Transductive Parsing for Universal Decompositional Semantics
We introduce a transductive model for parsing into Universal Decompositi...
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The Universal Decompositional Semantics Dataset and Decomp Toolkit
We present the Universal Decompositional Semantics (UDS) dataset (v1.0),...
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Broad-Coverage Semantic Parsing as Transduction
We unify different broad-coverage semantic parsing tasks under a transdu...
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Robust subsampling-based sparse Bayesian inference to tackle four challenges (large noise, outliers, data integration, and extrapolation) in the discovery of physical laws from
The derivation of physical laws is a dominant topic in scientific resear...
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Robust data-driven discovery of governing physical laws using a new subsampling-based sparse Bayesian method to tackle four challenges (large noise, outliers, data integration,
The derivation of physical laws is a dominant topic in scientific resear...
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Neural Machine Reading Comprehension: Methods and Trends
Machine Reading Comprehension (MRC), which requires the machine to answe...
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Omnidirectional Scene Text Detection with Sequential-free Box Discretization
Scene text in the wild is commonly presented with high variant character...
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Finite-Time Analysis of Q-Learning with Linear Function Approximation
In this paper, we consider the model-free reinforcement learning problem...
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AMR Parsing as Sequence-to-Graph Transduction
We propose an attention-based model that treats AMR parsing as sequence-...
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Unsupervised Deep Structured Semantic Models for Commonsense Reasoning
Commonsense reasoning is fundamental to natural language understanding. ...
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Learning to Detect Instantaneous Changes with Retrospective Convolution and Static Sample Synthesis
Change detection has been a challenging visual task due to the dynamic n...
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ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension
We present a large-scale dataset, ReCoRD, for machine reading comprehens...
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Halo: Learning Semantics-Aware Representations for Cross-Lingual Information Extraction
Cross-lingual information extraction (CLIE) is an important and challeng...
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Cross-lingual Semantic Parsing
We introduce the task of cross-lingual semantic parsing: mapping content...
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Fine-grained Entity Typing through Increased Discourse Context and Adaptive Classification Thresholds
Fine-grained entity typing is the task of assigning fine-grained semanti...
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Neural Davidsonian Semantic Proto-role Labeling
We present state-of-the-art results for semantic proto-role labeling (SP...
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FPGA Implementations of 3D-SIMD Processor Architecture for Deep Neural Networks Using Relative Indexed Compressed Sparse Filter Encoding Format and Stacked Filters Stationary F
It is a challenging task to deploy computationally and memory intensive ...
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Towards Reliable (and Efficient) Job Executions in a Practical Geo-distributed Data Analytics System
Geo-distributed data analytics are increasingly common to derive useful ...
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Stacked Filters Stationary Flow For Hardware-Oriented Acceleration Of Deep Convolutional Neural Networks
To address memory and computation resource limitations for hardware-orie...
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Random Euler Complex-Valued Nonlinear Filters
Over the last decade, both the neural network and kernel adaptive filter...
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Feature Enhancement Network: A Refined Scene Text Detector
In this paper, we propose a refined scene text detector with a novel Fea...
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Deep Generalized Canonical Correlation Analysis
We present Deep Generalized Canonical Correlation Analysis (DGCCA) -- a ...
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Ordinal Common-sense Inference
Humans have the capacity to draw common-sense inferences from natural la...
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Randomized Structural Sparsity based Support Identification with Applications to Locating Activated or Discriminative Brain Areas: A Multi-center Reproducibility Study
In this paper, we focus on how to locate the relevant or discriminative ...
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Randomized Structural Sparsity via Constrained Block Subsampling for Improved Sensitivity of Discriminative Voxel Identification
In this paper, we consider voxel selection for functional Magnetic Reson...
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