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09/05/2023
Distributionally Robust Model-based Reinforcement Learning with Large State Spaces
Three major challenges in reinforcement learning are the complex dynamic...
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07/21/2023
Deep Directly-Trained Spiking Neural Networks for Object Detection
Spiking neural networks (SNNs) are brain-inspired energy-efficient model...
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02/02/2023
Deep-Learning Tool for Early Identifying Non-Traumatic Intracranial Hemorrhage Etiology based on CT Scan
Background: To develop an artificial intelligence system that can accura...
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01/16/2023
CRYPTEXT: Database and Interactive Toolkit of Human-Written Text Perturbations in the Wild
User-generated textual contents on the Internet are often noisy, erroneo...
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01/14/2023
Deep-Reinforcement-Learning-based Path Planning for Industrial Robots using Distance Sensors as Observation
Industrial robots are widely used in various manufacturing environments ...
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10/27/2022
FCTalker: Fine and Coarse Grained Context Modeling for Expressive Conversational Speech Synthesis
Conversational Text-to-Speech (TTS) aims to synthesis an utterance with ...
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09/28/2022
Attention Spiking Neural Networks
Benefiting from the event-driven and sparse spiking characteristics of t...
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09/22/2022
MnTTS: An Open-Source Mongolian Text-to-Speech Synthesis Dataset and Accompanied Baseline
This paper introduces a high-quality open-source text-to-speech (TTS) sy...
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08/07/2022
BSDGAN: Balancing Sensor Data Generative Adversarial Networks for Human Activity Recognition
The development of IoT technology enables a variety of sensors can be in...
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06/13/2022
SmartGD: A Self-Challenging Generative Adversarial Network for Graph Drawing
A multitude of studies have been conducted on graph drawing, but many ex...
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05/28/2022
Uniform Convergence and Generalization for Nonconvex Stochastic Minimax Problems
This paper studies the uniform convergence and generalization bounds for...
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03/19/2022
Perturbations in the Wild: Leveraging Human-Written Text Perturbations for Realistic Adversarial Attack and Defense
We proposes a novel algorithm, ANTHRO, that inductively extracts over 60...
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03/09/2022
MetaCon: Unified Predictive Segments System with Trillion Concept Meta-Learning
Accurate understanding of users in terms of predicative segments play an...
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03/09/2022
SuperCone: Modeling Heterogeneous Experts with Concept Meta-learning for Unified Predictive Segments System
Understanding users through predicative segments play an essential role ...
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03/02/2022
Rethinking Pretraining as a Bridge from ANNs to SNNs
Spiking neural networks (SNNs) are known as a typical kind of brain-insp...
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12/15/2021
Advancing Residual Learning towards Powerful Deep Spiking Neural Networks
Despite the rapid progress of neuromorphic computing, inadequate capacit...
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12/09/2021
Advancing Deep Residual Learning by Solving the Crux of Degradation in Spiking Neural Networks
Despite the rapid progress of neuromorphic computing, the inadequate dep...
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09/18/2021
BERT-Beta: A Proactive Probabilistic Approach to Text Moderation
Text moderation for user generated content, which helps to promote healt...
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08/18/2021
TSI: an Ad Text Strength Indicator using Text-to-CTR and Semantic-Ad-Similarity
Coming up with effective ad text is a time consuming process, and partic...
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06/27/2021
DeepGD: A Deep Learning Framework for Graph Drawing Using GNN
In the past decades, many graph drawing techniques have been proposed fo...
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04/15/2021
Efficient Ring-topology Decentralized Federated Learning with Deep Generative Models for Industrial Artificial Intelligent
By leveraging deep learning based technologies, the data-driven based ap...
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02/07/2021
What's in a Name? – Gender Classification of Names with Character Based Machine Learning Models
Gender information is no longer a mandatory input when registering for a...
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12/19/2020
Political Posters Identification with Appearance-Text Fusion
In this paper, we propose a method that efficiently utilizes appearance ...
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10/29/2020
Going Deeper With Directly-Trained Larger Spiking Neural Networks
Spiking neural networks (SNNs) are promising in a bio-plausible coding f...
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10/21/2020
GFL: A Decentralized Federated Learning Framework Based On Blockchain
Due to people's emerging concern about data privacy, federated learning(...
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10/17/2020
HABERTOR: An Efficient and Effective Deep Hatespeech Detector
We present our HABERTOR model for detecting hatespeech in large scale us...
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09/20/2020
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference
The neural attention mechanism plays an important role in many natural l...
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07/15/2020
Comparing to Learn: Surpassing ImageNet Pretraining on Radiographs By Comparing Image Representations
In deep learning era, pretrained models play an important role in medica...
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06/10/2020
Embedding Task Knowledge into 3D Neural Networks via Self-supervised Learning
Deep learning highly relies on the amount of annotated data. However, an...
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05/02/2020
Multi-Modality Generative Adversarial Networks with Tumor Consistency Loss for Brain MR Image Synthesis
Magnetic Resonance (MR) images of different modalities can provide compl...
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02/25/2020
Biased Stochastic Gradient Descent for Conditional Stochastic Optimization
Conditional Stochastic Optimization (CSO) covers a variety of applicatio...
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01/02/2020
Large-scale Gender/Age Prediction of Tumblr Users
Tumblr, as a leading content provider and social media, attracts 371 mil...
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01/02/2020
A Deep Structural Model for Analyzing Correlated Multivariate Time Series
Multivariate time series are routinely encountered in real-world applica...
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11/03/2019
Comprehensive SNN Compression Using ADMM Optimization and Activity Regularization
Spiking neural network is an important family of models to emulate the b...
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10/05/2019
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubik's Cube
Witnessed the development of deep learning, increasing number of studies...
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06/05/2019
A GLCM Embedded CNN Strategy for Computer-aided Diagnosis in Intracerebral Hemorrhage
Computer-aided diagnosis (CADx) systems have been shown to assist radiol...
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05/28/2019
Sample Complexity of Sample Average Approximation for Conditional Stochastic Optimization
In this paper, we study a class of stochastic optimization problems, ref...
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11/05/2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Gliomas are the most common primary brain malignancies, with different d...
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08/25/2017