b'Xin He'

research

∙ 09/11/2023

Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs

Large Language Models (LLMs) have proven their exceptional capabilities ...

0 Wenhua Cheng, et al. ∙

research

∙ 09/03/2023

FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs

The rapid growth of memory and computation requirements of large languag...

0 Zhenheng Tang, et al. ∙

research

∙ 05/23/2023

NeuralMatrix: Moving Entire Neural Networks to General Matrix Multiplication for Efficient Inference

In this study, we introduce NeuralMatrix, a novel framework that enables...

0 Ruiqi Sun, et al. ∙

research

∙ 04/07/2023

BS-GAT Behavior Similarity Based Graph Attention Network for Network Intrusion Detection

With the development of the Internet of Things (IoT), network intrusion ...

0 Yalu Wang, et al. ∙

research

∙ 03/07/2023

Lformer: Text-to-Image Generation with L-shape Block Parallel Decoding

Generative transformers have shown their superiority in synthesizing hig...

0 Jiacheng Li, et al. ∙

research

∙ 11/23/2022

NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension

One-shot neural architecture search (NAS) substantially improves the sea...

0 Xin He, et al. ∙

research

∙ 10/27/2022

Learning One-Class Hyperspectral Classifier from Positive and Unlabeled Data for Low Proportion Target

Hyperspectral imagery (HSI) one-class classification is aimed at identif...

0 Hengwei Zhao, et al. ∙

research

∙ 09/28/2022

Nonparametric augmented probability weighting with sparsity

Nonresponse frequently arises in practice, and simply ignoring it may le...

0 Xin He, et al. ∙

research

∙ 08/04/2022

Fine-Grained Semantically Aligned Vision-Language Pre-Training

Large-scale vision-language pre-training has shown impressive advances i...

2 Juncheng Li, et al. ∙

research

∙ 06/06/2022

Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning

In federated learning (FL), model performance typically suffers from cli...

0 Zhenheng Tang, et al. ∙

research

∙ 11/30/2021

EAGAN: Efficient Two-stage Evolutionary Architecture Search for GANs

Generative Adversarial Networks (GANs) have been proven hugely successfu...

0 Guohao Ying, et al. ∙

research

∙ 11/01/2021

Efficient Learning of Quadratic Variance Function Directed Acyclic Graphs via Topological Layers

Directed acyclic graph (DAG) models are widely used to represent causal ...

0 Wei Zhou, et al. ∙

research

∙ 11/01/2021

Learning linear non-Gaussian directed acyclic graph with diverging number of nodes

Acyclic model, often depicted as a directed acyclic graph (DAG), has bee...

0 Ruixuan Zhao, et al. ∙

research

∙ 10/18/2021

Kernel-based estimation for partially functional linear model: Minimax rates and randomized sketches

This paper considers the partially functional linear model (PFLM) where ...

0 Shaogao Lv, et al. ∙

research

∙ 10/08/2021

Maximize the Exploration of Congeneric Semantics for Weakly Supervised Semantic Segmentation

With the increase in the number of image data and the lack of correspond...

0 Ke Zhang, et al. ∙

research

∙ 04/19/2021

A Competitive Method to VIPriors Object Detection Challenge

In this report, we introduce the technical details of our submission to ...

0 Fei Shen, et al. ∙

research

∙ 01/26/2021

Efficient Multi-objective Evolutionary 3D Neural Architecture Search for COVID-19 Detection with Chest CT Scans

COVID-19 pandemic has spread globally for months. Due to its long incuba...

0 Xin He, et al. ∙

research

∙ 01/14/2021

Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT Scans

The COVID-19 pandemic has spread globally for several months. Because it...

0 Xin He, et al. ∙

research

∙ 11/20/2019

Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models

Skin disease is one of the most common types of human diseases, which ma...

18 Xin He, et al. ∙

research

∙ 10/02/2019

Attacking Vision-based Perception in End-to-End Autonomous Driving Models

Recent advances in machine learning, especially techniques such as deep ...

35 Adith Boloor, et al. ∙

research

∙ 09/15/2019

Performance and Power Evaluation of AI Accelerators for Training Deep Learning Models

Deep neural networks (DNNs) have become widely used in many AI applicati...

0 Yuxin Wang, et al. ∙

research

∙ 08/06/2019

Symmetry-constrained Rectification Network for Scene Text Recognition

Reading text in the wild is a very challenging task due to the diversity...

8 Mingkun Yang, et al. ∙

research

∙ 08/02/2019

AutoML: A Survey of the State-of-the-Art

Deep learning has penetrated all aspects of our lives and brought us gre...

257 Xin He, et al. ∙

research

∙ 03/12/2019

Simple Physical Adversarial Examples against End-to-End Autonomous Driving Models

Recent advances in machine learning, especially techniques such as deep ...

14 Adith Boloor, et al. ∙

research

∙ 01/03/2019

Sparse Learning in reproducing kernel Hilbert space

Sparse learning aims to learn the sparse structure of the true target fu...

0 Xin He, et al. ∙

research

∙ 11/10/2018

Scene Text Detection and Recognition: The Deep Learning Era

With the rise and development of deep learning, computer vision has been...

0 Shangbang Long, et al. ∙

research

∙ 10/27/2018

On Measurement of the Spatio-Frequency Property of OFDM Backscattering

Orthogonal frequency-division multiplexing (OFDM) backscatter system, su...

0 Xiaoxue Zhang, et al. ∙

research

∙ 07/04/2018

TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes

Driven by deep neural networks and large scale datasets, scene text dete...

0 Shangbang Long, et al. ∙

research

∙ 05/21/2018

AxTrain: Hardware-Oriented Neural Network Training for Approximate Inference

The intrinsic error tolerance of neural network (NN) makes approximate c...

0 Xin He, et al. ∙

research

∙ 02/26/2018

Scalable kernel-based variable selection with sparsistency

Variable selection is central to high-dimensional data analysis, and var...

0 Xin He, et al. ∙

research

∙ 11/13/2017

Multilayer Nonlinear Processing for Information Privacy in Sensor Networks

A sensor network wishes to transmit information to a fusion center to al...

0 Xin He, et al. ∙

research

∙ 01/27/2001

Linear-Time Succinct Encodings of Planar Graphs via Canonical Orderings

Let G be an embedded planar undirected graph that has n vertices, m edge...

0 Xin He, et al. ∙

research

∙ 01/23/2001

A Fast General Methodology for Information-Theoretically Optimal Encodings of Graphs

We propose a fast methodology for encoding graphs with information-theor...

0 Xin He, et al. ∙

Xin He

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