b'Lei Huang'

research

∙ 09/15/2023

P-ROCKET: Pruning Random Convolution Kernels for Time Series Classification

In recent years, two time series classification models, ROCKET and MINIR...

0 Shaowu Chen, et al. ∙

research

∙ 08/07/2023

High-rate discretely-modulated continuous-variable quantum key distribution using quantum machine learning

We propose a high-rate scheme for discretely-modulated continuous-variab...

0 Qin Liao, et al. ∙

research

∙ 06/24/2023

DiffDTM: A conditional structure-free framework for bioactive molecules generation targeted for dual proteins

Advances in deep generative models shed light on de novo molecule genera...

0 Lei Huang, et al. ∙

research

∙ 06/20/2023

Fine-grained Policy-driven I/O Sharing for Burst Buffers

A burst buffer is a common method to bridge the performance gap between ...

0 Ed Karrels, et al. ∙

research

∙ 05/26/2023

Modulate Your Spectrum in Self-Supervised Learning

Whitening loss provides theoretical guarantee in avoiding feature collap...

0 Xi Weng, et al. ∙

research

∙ 02/16/2023

WHC: Weighted Hybrid Criterion for Filter Pruning on Convolutional Neural Networks

Filter pruning has attracted increasing attention in recent years for it...

0 Shaowu Chen, et al. ∙

research

∙ 12/12/2022

Scale-Semantic Joint Decoupling Network for Image-text Retrieval in Remote Sensing

Image-text retrieval in remote sensing aims to provide flexible informat...

0 Chengyu Zheng, et al. ∙

research

∙ 11/07/2022

FIXED: Frustratingly Easy Domain Generalization with Mixup

Domain generalization (DG) aims to learn a generalizable model from mult...

0 Wang Lu, et al. ∙

research

∙ 10/22/2022

Sub-network Multi-objective Evolutionary Algorithm for Filter Pruning

Filter pruning is a common method to achieve model compression and accel...

0 Xuhua Li, et al. ∙

research

∙ 10/11/2022

Understanding the Failure of Batch Normalization for Transformers in NLP

Batch Normalization (BN) is a core and prevalent technique in accelerati...

0 Jiaxi Wang, et al. ∙

research

∙ 10/07/2022

An Investigation into Whitening Loss for Self-supervised Learning

A desirable objective in self-supervised learning (SSL) is to avoid feat...

8 Xi Weng, et al. ∙

research

∙ 09/13/2022

MDM: Molecular Diffusion Model for 3D Molecule Generation

Molecule generation, especially generating 3D molecular geometries from ...

21 Lei Huang, et al. ∙

research

∙ 07/31/2022

Generalized truncated moment problems with unbounded sets

This paper studies generalized truncated moment problems with unbounded ...

0 Lei Huang, et al. ∙

research

∙ 06/16/2022

Towards Better Understanding with Uniformity and Explicit Regularization of Embeddings in Embedding-based Neural Topic Models

Embedding-based neural topic models could explicitly represent words and...

0 Wei Shao, et al. ∙

research

∙ 03/24/2022

Bi-level Doubly Variational Learning for Energy-based Latent Variable Models

Energy-based latent variable models (EBLVMs) are more expressive than co...

0 Ge Kan, et al. ∙

research

∙ 03/21/2022

Delving into the Estimation Shift of Batch Normalization in a Network

Batch normalization (BN) is a milestone technique in deep learning. It n...

0 Lei Huang, et al. ∙

research

∙ 11/23/2021

Armada: A Robust Latency-Sensitive Edge Cloud in Heterogeneous Edge-Dense Environments

Edge computing has enabled a large set of emerging edge applications by ...

0 Lei Huang, et al. ∙

research

∙ 10/27/2021

Rot-Pro: Modeling Transitivity by Projection in Knowledge Graph Embedding

Knowledge graph embedding models learn the representations of entities a...

0 Tengwei Song, et al. ∙

research

∙ 07/09/2021

Joint Matrix Decomposition for Deep Convolutional Neural Networks Compression

Deep convolutional neural networks (CNNs) with a large number of paramet...

0 Shaowu Chen, et al. ∙

research

∙ 07/04/2021

KAISA: An Adaptive Second-order Optimizer Framework for Deep Neural Networks

Kronecker-factored Approximate Curvature (K-FAC) has recently been shown...

15 J. Gregory Pauloski, et al. ∙

research

∙ 04/08/2021

One-bit Spectrum Sensing with the Eigenvalue Moment Ratio Approach

One-bit analog-to-digital converter (ADC), performing signal sampling as...

0 Yuan Zhao, et al. ∙

research

∙ 02/26/2021

Many-to-One Distribution Learning and K-Nearest Neighbor Smoothing for Thoracic Disease Identification

Chest X-rays are an important and accessible clinical imaging tool for t...

11 Yi Zhou, et al. ∙

research

∙ 02/17/2021

S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration

Previous studies dominantly target at self-supervised learning on real-v...

0 Zhiqiang Shen, et al. ∙

research

∙ 01/25/2021

EGFI: Drug-Drug Interaction Extraction and Generation with Fusion of Enriched Entity and Sentence Information

The rapid growth in literature accumulates diverse and yet comprehensive...

8 Lei Huang, et al. ∙

research

∙ 12/10/2020

Slimmable Generative Adversarial Networks

Generative adversarial networks (GANs) have achieved remarkable progress...

0 Liang Hou, et al. ∙

research

∙ 12/03/2020

Towards Defending Multiple Adversarial Perturbations via Gated Batch Normalization

There is now extensive evidence demonstrating that deep neural networks ...

0 Aishan Liu, et al. ∙

research

∙ 10/14/2020

Effects of the Nonlinearity in Activation Functions on the Performance of Deep Learning Models

The nonlinearity of activation functions used in deep learning models ar...

0 Nalinda Kulathunga, et al. ∙

research

∙ 09/28/2020

Group Whitening: Balancing Learning Efficiency and Representational Capacity

Batch normalization (BN) is an important technique commonly incorporated...

2 Lei Huang, et al. ∙

research

∙ 09/27/2020

Normalization Techniques in Training DNNs: Methodology, Analysis and Application

Normalization techniques are essential for accelerating the training and...

8 Lei Huang, et al. ∙

research

∙ 07/09/2020

Invertible Zero-Shot Recognition Flows

Deep generative models have been successfully applied to Zero-Shot Learn...

0 Yuming Shen, et al. ∙

research

∙ 07/01/2020

Convolutional Neural Network Training with Distributed K-FAC

Training neural networks with many processors can reduce time-to-solutio...

0 J. Gregory Pauloski, et al. ∙

research

∙ 05/30/2020

Topic Detection and Summarization of User Reviews

A massive amount of reviews are generated daily from various platforms. ...

0 Pengyuan Li, et al. ∙

research

∙ 04/02/2020

Controllable Orthogonalization in Training DNNs

Orthogonality is widely used for training deep neural networks (DNNs) du...

19 Lei Huang, et al. ∙

research

∙ 04/01/2020

An Efficient Agreement Mechanism in CapsNets By Pairwise Product

Capsule networks (CapsNets) are capable of modeling visual hierarchical ...

0 Lei Zhao, et al. ∙

research

∙ 03/27/2020

An Investigation into the Stochasticity of Batch Whitening

Batch Normalization (BN) is extensively employed in various network arch...

0 Lei Huang, et al. ∙

research

∙ 03/12/2020

The Medical Scribe: Corpus Development and Model Performance Analyses

There is a growing interest in creating tools to assist in clinical note...

0 Izhak Shafran, et al. ∙

research

∙ 02/25/2020

Exploring Learning Dynamics of DNNs via Layerwise Conditioning Analysis

Conditioning analysis uncovers the landscape of optimization objective b...

4 Lei Huang, et al. ∙

research

∙ 02/01/2020

Unbiased Scene Graph Generation via Rich and Fair Semantic Extraction

Extracting graph representation of visual scenes in image is a challengi...

11 Bin Wen, et al. ∙

research

∙ 07/03/2019

Deformable Tube Network for Action Detection in Videos

We address the problem of spatio-temporal action detection in videos. Ex...

2 Wei Li, et al. ∙

research

∙ 04/18/2019

Query-Adaptive Hash Code Ranking for Large-Scale Multi-View Visual Search

Hash based nearest neighbor search has become attractive in many applica...

0 Xianglong Liu, et al. ∙

research

∙ 04/06/2019

Iterative Normalization: Beyond Standardization towards Efficient Whitening

Batch Normalization (BN) is ubiquitously employed for accelerating neura...

14 Lei Huang, et al. ∙

research

∙ 01/11/2019

Analyzing Periodicity and Saliency for Adult Video Detection

Content-based adult video detection plays an important role in preventin...

0 Yizhi Liu, et al. ∙

research

∙ 11/29/2018

Utilizing Complex-valued Network for Learning to Compare Image Patches

At present, the great achievements of convolutional neural network(CNN) ...

0 Siwen Jiang, et al. ∙

research

∙ 09/27/2018

FanStore: Enabling Efficient and Scalable I/O for Distributed Deep Learning

Emerging Deep Learning (DL) applications introduce heavy I/O workloads o...

0 Zhao Zhang, et al. ∙

research

∙ 06/05/2018

Data-driven Analytics for Business Architectures: Proposed Use of Graph Theory

Business Architecture (BA) plays a significant role in helping organizat...

0 Lei Huang, et al. ∙

research

∙ 04/23/2018

Decorrelated Batch Normalization

Batch Normalization (BN) is capable of accelerating the training of deep...

0 Lei Huang, et al. ∙

research

∙ 12/10/2017

DGCNN: Disordered Graph Convolutional Neural Network Based on the Gaussian Mixture Model

Convolutional neural networks (CNNs) can be applied to graph similarity ...

0 Yang Liu, et al. ∙

research

∙ 10/06/2017

Projection Based Weight Normalization for Deep Neural Networks

Optimizing deep neural networks (DNNs) often suffers from the ill-condit...

0 Lei Huang, et al. ∙

research

∙ 05/31/2017

Micro Fourier Transform Profilometry (μFTP): 3D shape measurement at 10,000 frames per second

Recent advances in imaging sensors and digital light projection technolo...

0 Chao Zuo, et al. ∙

Lei Huang

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