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11/25/2022
BatmanNet: Bi-branch Masked Graph Transformer Autoencoder for Molecular Representation
Although substantial efforts have been made using graph neural networks ...
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05/28/2022
Group-wise Reinforcement Feature Generation for Optimal and Explainable Representation Space Reconstruction
Representation (feature) space is an environment where data points are v...
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05/25/2022
Semi-supervised Drifted Stream Learning with Short Lookback
In many scenarios, 1) data streams are generated in real time; 2) labele...
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08/31/2021
Multistage Pruning of CNN Based ECG Classifiers for Edge Devices
Using smart wearable devices to monitor patients electrocardiogram (ECG)...
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03/22/2021
Server Averaging for Federated Learning
Federated learning allows distributed devices to collectively train a mo...
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10/18/2020
Federated Unsupervised Representation Learning
To leverage enormous unlabeled data on distributed edge devices, we form...
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09/21/2020
ES Attack: Model Stealing against Deep Neural Networks without Data Hurdles
Deep neural networks (DNNs) have become the essential components for var...
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09/17/2020
Distilled One-Shot Federated Learning
Current federated learning algorithms take tens of communication rounds ...
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09/16/2020
Asking Complex Questions with Multi-hop Answer-focused Reasoning
Asking questions from natural language text has attracted increasing att...
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08/31/2020
Connecting Web Event Forecasting with Anomaly Detection: A Case Study on Enterprise Web Applications Using Self-Supervised Neural Networks
Recently web applications have been widely used in enterprises to assist...
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07/13/2020
PRI-VAE: Principle-of-Relevant-Information Variational Autoencoders
Although substantial efforts have been made to learn disentangled repres...
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06/29/2020
Modeling and Computation of High Efficiency and Efficacy Multi-Step Batch Testing for Infectious Diseases
We propose a mathematical model based on probability theory to optimize ...
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05/22/2020
Arbitrary-sized Image Training and Residual Kernel Learning: Towards Image Fraud Identification
Preserving original noise residuals in images are critical to image frau...
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04/27/2020
A Batch Normalized Inference Network Keeps the KL Vanishing Away
Variational Autoencoder (VAE) is widely used as a generative model to ap...
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02/05/2020
Knowledge Federation: Hierarchy and Unification
With the strengthening of data privacy and security, traditional data ce...
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12/02/2019
Improving Question Generation with Sentence-level Semantic Matching and Answer Position Inferring
Taking an answer and its context as input, sequence-to-sequence models h...
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12/01/2019
DeepAtom: A Framework for Protein-Ligand Binding Affinity Prediction
The cornerstone of computational drug design is the calculation of bindi...
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11/15/2019
Adaptive Leader-Follower Formation Control and Obstacle Avoidance via Deep Reinforcement Learning
We propose a deep reinforcement learning (DRL) methodology for the track...
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10/28/2019
Added Value of Intraoperative Data for Predicting Postoperative Complications: Development and Validation of a MySurgeryRisk Extension
To test the hypothesis that accuracy, discrimination, and precision in p...
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12/08/2018
Generalized Batch Normalization: Towards Accelerating Deep Neural Networks
Utilizing recently introduced concepts from statistics and quantitative ...
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12/03/2018
FoldingZero: Protein Folding from Scratch in Hydrophobic-Polar Model
De novo protein structure prediction from amino acid sequence is one of ...
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05/11/2018
Improved Predictive Models for Acute Kidney Injury with IDEAs: Intraoperative Data Embedded Analytics
Acute kidney injury (AKI) is a common and serious complication after a s...
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05/08/2018
A Transfer Learning Approach for Microstructure Reconstruction and Structure-property Predictions
Stochastic microstructure reconstruction has become an indispensable par...
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04/09/2018
Comparing Clinical Judgment with MySurgeryRisk Algorithm for Preoperative Risk Assessment: A Pilot Study
Background: Major postoperative complications are associated with increa...
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02/07/2018
Leveraging Uncertainty for Effective Malware Mitigation
A promising avenue for improving the effectiveness of behavioral-based m...
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12/19/2017
Adversarial Examples: Attacks and Defenses for Deep Learning
With rapid progress and great successes in a wide spectrum of applicatio...
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12/04/2017
Learning Fast and Slow: PROPEDEUTICA for Real-time Malware Detection
In this paper, we introduce and evaluate PROPEDEUTICA, a novel methodolo...
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09/28/2017
Intelligent Perioperative System: Towards Real-time Big Data Analytics in Surgery Risk Assessment
Surgery risk assessment is an effective tool for physicians to manage th...
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12/09/2016
DeepCancer: Detecting Cancer through Gene Expressions via Deep Generative Learning
Transcriptional profiling on microarrays to obtain gene expressions has ...
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11/17/2015