
-
Sign-regularized Multi-task Learning
Multi-task learning is a framework that enforces different learning task...
read it
-
GP: Context-free Grammar Pre-training for Text-to-SQL Parsers
A new method for Text-to-SQL parsing, Grammar Pre-training (GP), is prop...
read it
-
FamDroid: Learning-Based Android Malware Family Classification Using Static Analysis
Android is currently the most extensively used smartphone platform in th...
read it
-
Study On Coding Tools Beyond Av1
The Alliance for Open Media has recently initiated coding tool explorati...
read it
-
Online Decision Trees with Fairness
While artificial intelligence (AI)-based decision-making systems are inc...
read it
-
Disentangled Dynamic Graph Deep Generation
Deep generative models for graphs have exhibited promising performance i...
read it
-
FedAT: A Communication-Efficient Federated Learning Method with Asynchronous Tiers under Non-IID Data
Federated learning (FL) involves training a model over massive distribut...
read it
-
A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions
High-level classification algorithms focus on the interactions between i...
read it
-
Graph-based Multi-hop Reasoning for Long Text Generation
Long text generation is an important but challenging task.The main probl...
read it
-
A Novel Method for Inference of Acyclic Chemical Compounds with Bounded Branch-height Based on Artificial Neural Networks and Integer Programming
Analysis of chemical graphs is a major research topic in computational m...
read it
-
Factorized Deep Generative Models for Trajectory Generation with Spatiotemporal-Validity Constraints
Trajectory data generation is an important domain that characterizes the...
read it
-
A Network-Based High-Level Data Classification Algorithm Using Betweenness Centrality
Data classification is a major machine learning paradigm, which has been...
read it
-
Tunable Subnetwork Splitting for Model-parallelism of Neural Network Training
Alternating minimization methods have recently been proposed as alternat...
read it
-
Event Prediction in the Big Data Era: A Systematic Survey
Events are occurrences in specific locations, time, and semantics that n...
read it
-
A Systematic Survey on Deep Generative Models for Graph Generation
Graphs are important data representations for describing objects and the...
read it
-
Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement
Disentangled representation learning has recently attracted a significan...
read it
-
TG-GAN: Deep Generative Models for Continuously-time Temporal Graph Generation
Recently deep generative models for static networks have been under acti...
read it
-
Chronnet: a network-based model for spatiotemporal data analysis
The amount and size of spatiotemporal data sets from different domains h...
read it
-
Evolution Features and Behavior Characters of Friendship Networks on Campus Life
Analyzing and mining students' behaviors and interactions from big data ...
read it
-
Generating Tertiary Protein Structures via an Interpretative Variational Autoencoder
Much scientific enquiry across disciplines is founded upon a mechanistic...
read it
-
Dynamic Reconstruction of Deformable Soft-tissue with Stereo Scope in Minimal Invasive Surgery
In minimal invasive surgery, it is important to rebuild and visualize th...
read it
-
Deep Multi-attributed Graph Translation with Node-Edge Co-evolution
Generalized from image and language translation, graph translation aims ...
read it
-
Bridging the Gap between Spatial and Spectral Domains: A Survey on Graph Neural Networks
The success of deep learning has been widely recognized in many machine ...
read it
-
Efficient model-based Bioequivalence Testing
The classical approach to analyze pharmacokinetic (PK) data in bioequiva...
read it
-
Chaotic Phase Synchronization and Desynchronization in an Oscillator Network for Object Selection
Object selection refers to the mechanism of extracting objects of intere...
read it
-
Particle Competition and Cooperation for Semi-Supervised Learning with Label Noise
Semi-supervised learning methods are usually employed in the classificat...
read it
-
Code-Bridged Classifier (CBC): A Low or Negative Overhead Defense for Making a CNN Classifier Robust Against Adversarial Attacks
In this paper, we propose Code-Bridged Classifier (CBC), a framework for...
read it
-
Automated Analysis of Femoral Artery Calcification Using Machine Learning Techniques
We report an object tracking algorithm that combines geometrical constra...
read it
-
Learning to Recommend via Meta Parameter Partition
In this paper we propose to solve an important problem in recommendation...
read it
-
Efficient Global String Kernel with Random Features: Beyond Counting Substructures
Analysis of large-scale sequential data has been one of the most crucial...
read it
-
Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding
Graph kernels are widely used for measuring the similarity between graph...
read it
-
TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Prediction
Critical incident stages identification and reasonable prediction of tra...
read it
-
Analysis of minima for geodesic and chordal cost for a minimal 2D pose-graph SLAM problem
In this paper, we show that for a minimal pose-graph problem, even in th...
read it
-
Existence of local minima of a minimal 2D pose-graph SLAM problem
In this paper, we show that for a minimal pose-graph problem, even in th...
read it
-
Compositional Generalization for Primitive Substitutions
Compositional generalization is a basic mechanism in human language lear...
read it
-
BEAN: Interpretable Representation Learning with Biologically-Enhanced Artificial Neuronal Assembly Regularization
Deep neural networks (DNNs) are known for extracting good representation...
read it
-
Multi-stage Deep Classifier Cascades for Open World Recognition
At present, object recognition studies are mostly conducted in a closed ...
read it
-
DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums
Online health communities such as the online breast cancer forum enable ...
read it
-
CBOWRA: A Representation Learning Approach for Medication Anomaly Detection
Electronic health record is an important source for clinical researches ...
read it
-
Pyramid: Machine Learning Framework to Estimate the Optimal Timing and Resource Usage of a High-Level Synthesis Design
The emergence of High-Level Synthesis (HLS) tools shifted the paradigm o...
read it
-
Counting Roots of a Polynomial in a Convex Compact Region by Means of Winding Number Calculation via Sampling
In this paper, we propose a novel efficient algorithm for calculating wi...
read it
-
An observable time series based SLAM algorithm for deforming environment
In this paper, we study the back-end of simultaneous localization and ma...
read it
-
Efficient two step optimization for large embedded deformation graph based SLAM
Embedded deformation nodes based formulation has been widely applied in ...
read it
-
Low Rank Approximation at Sublinear Cost by Means of Subspace Sampling
Low Rank Approximation (LRA) of a matrix is a hot research subject, fund...
read it
-
ADMM for Efficient Deep Learning with Global Convergence
Alternating Direction Method of Multipliers (ADMM) has been used success...
read it
-
Machine Learning-Based Delay-Aware UAV Detection and Operation Mode Identification over Encrypted Wi-Fi Traffic
The consumer UAV (unmanned aerial vehicle) market has grown significantl...
read it
-
Interpreting and Evaluating Neural Network Robustness
Recently, adversarial deception becomes one of the most considerable thr...
read it
-
Learning Good Representation via Continuous Attention
In this paper we present our scientific discovery that good representati...
read it
-
Algorithms to compute the Burrows-Wheeler Similarity Distribution
The Burrows-Wheeler transform (BWT) is a well studied text transformatio...
read it
-
Global Fire Season Severity Analysis and Forecasting
Global fire activity has a huge impact on human lives. In recent years, ...
read it