22 citations · 82 across the 18 of their papers we have counts for
19 papers
CRYPTEXT: Database and Interactive Toolkit of Human-Written Text Perturbations in the Wild
Thai Le, Ye Yiran, Yifan Hu +1
User-generated textual contents on the Internet are often noisy, erroneous, and not in correct forms in grammar. In fact, some online users choose to express their opinions online…
MnTTS2: An Open-Source Multi-Speaker Mongolian Text-to-Speech Synthesis Dataset
Kailin Liang, Bin Liu, Yifan Hu +3
Text-to-Speech (TTS) synthesis for low-resource languages is an attractive research issue in academia and industry nowadays. Mongolian is the official language of the Inner Mongoli…
FCTalker: Fine and Coarse Grained Context Modeling for Expressive Conversational Speech Synthesis
Yifan Hu, Rui Liu, Guanglai Gao +1
Conversational Text-to-Speech (TTS) aims to synthesis an utterance with the right linguistic and affective prosody in a conversational context. The correlation between the current…
MnTTS: An Open-Source Mongolian Text-to-Speech Synthesis Dataset and Accompanied Baseline
Yifan Hu, Pengkai Yin, Rui Liu +2
This paper introduces a high-quality open-source text-to-speech (TTS) synthesis dataset for Mongolian, a low-resource language spoken by over 10 million people worldwide. The datas…
BSDGAN: Balancing Sensor Data Generative Adversarial Networks for Human Activity Recognition
Yifan Hu, Yu Wang
The development of IoT technology enables a variety of sensors can be integrated into mobile devices. Human Activity Recognition (HAR) based on sensor data has become an active res…
Construction and Validation of a Geometry-based Mathematical Model for the Hard X-ray Imager
Xian-Kai Jiang, Jian Wu, Deng-Yi Chen +4
Quantitative and analytical analysis of modulation process of the collimator is a great challenge, and is also of great value to the design and development of Fourier transform ima…
SmartGD: A GAN-Based Graph Drawing Framework for Diverse Aesthetic Goals
Xiaoqi Wang, Kevin Yen, Yifan Hu +1
While a multitude of studies have been conducted on graph drawing, many existing methods only focus on optimizing a single aesthetic aspect of graph layouts, which can lead to sub-…
Efficient Algorithms for A Class of Stochastic Hidden Convex Optimization and Its Applications in Network Revenue Management
Xin Chen, Niao He, Yifan Hu +1
We study a class of stochastic nonconvex optimization in the form of , i.e., is a composition of a convex function and…
SuperCone: Unified User Segmentation over Heterogeneous Experts via Concept Meta-learning
Keqian Li, Yifan Hu
We study the problem of user segmentation: given a set of users and one or more predefined groups or segments, assign users to their corresponding segments. As an example, for a se…
Perturbations in the Wild: Leveraging Human-Written Text Perturbations for Realistic Adversarial Attack and Defense
Thai Le, Jooyoung Lee, Kevin Yen +2
We proposes a novel algorithm, ANTHRO, that inductively extracts over 600K human-written text perturbations in the wild and leverages them for realistic adversarial attack. Unlike…
MetaCon: Unified Predictive Segments System with Trillion Concept Meta-Learning
Keqian Li, Yifan Hu, Logan Palanisamy +6
Accurate understanding of users in terms of predicative segments play an essential role in the day to day operation of modern internet enterprises. Nevertheless, there are signific…
Rethinking Pretraining as a Bridge from ANNs to SNNs
Yihan Lin, Yifan Hu, Shijie Ma +2
Spiking neural networks (SNNs) are known as a typical kind of brain-inspired models with their unique features of rich neuronal dynamics, diverse coding schemes and low power consu…
Advancing Deep Residual Learning by Solving the Crux of Degradation in Spiking Neural Networks
Yifan Hu, Yujie Wu, Lei Deng +1
Despite the rapid progress of neuromorphic computing, the inadequate depth and the resulting insufficient representation power of spiking neural networks (SNNs) severely restrict t…
Going Deeper With Directly-Trained Larger Spiking Neural Networks
Hanle Zheng, Yujie Wu, Lei Deng +2
Spiking neural networks (SNNs) are promising in a bio-plausible coding for spatio-temporal information and event-driven signal processing, which is very suited for energy-efficient…
HABERTOR: An Efficient and Effective Deep Hatespeech Detector
Thanh Tran, Yifan Hu, Changwei Hu +4
We present our HABERTOR model for detecting hatespeech in large scale user-generated content. Inspired by the recent success of the BERT model, we propose several modifications to…
GFL: A Decentralized Federated Learning Framework Based On Blockchain
Yifan Hu, Yuhang Zhou, Jun Xiao +1
Federated learning(FL) is a rapidly growing field and many centralized and decentralized FL frameworks have been proposed. However, it is of great challenge for current FL framewor…
Comparing to Learn: Surpassing ImageNet Pretraining on Radiographs By Comparing Image Representations
Hong-Yu Zhou, Shuang Yu, Cheng Bian +3
In deep learning era, pretrained models play an important role in medical image analysis, in which ImageNet pretraining has been widely adopted as the best way. However, it is unde…
Embedding Task Knowledge into 3D Neural Networks via Self-supervised Learning
Jiuwen Zhu, Yuexiang Li, Yifan Hu +1
Deep learning highly relies on the amount of annotated data. However, annotating medical images is extremely laborious and expensive. To this end, self-supervised learning (SSL), a…
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubik's Cube
Xinrui Zhuang, Yuexiang Li, Yifan Hu +3
Witnessed the development of deep learning, increasing number of studies try to build computer aided diagnosis systems for 3D volumetric medical data. However, as the annotations o…