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09/11/2023
Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs
Large Language Models (LLMs) have proven their exceptional capabilities ...
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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...
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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...
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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 ...
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03/07/2023
Lformer: Text-to-Image Generation with L-shape Block Parallel Decoding
Generative transformers have shown their superiority in synthesizing hig...
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11/23/2022
NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension
One-shot neural architecture search (NAS) substantially improves the sea...
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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...
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09/28/2022
Nonparametric augmented probability weighting with sparsity
Nonresponse frequently arises in practice, and simply ignoring it may le...
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08/04/2022
Fine-Grained Semantically Aligned Vision-Language Pre-Training
Large-scale vision-language pre-training has shown impressive advances i...
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06/06/2022
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning
In federated learning (FL), model performance typically suffers from cli...
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11/30/2021
EAGAN: Efficient Two-stage Evolutionary Architecture Search for GANs
Generative Adversarial Networks (GANs) have been proven hugely successfu...
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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 ...
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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...
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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 ...
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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...
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04/19/2021
A Competitive Method to VIPriors Object Detection Challenge
In this report, we introduce the technical details of our submission to ...
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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...
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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...
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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...
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10/02/2019
Attacking Vision-based Perception in End-to-End Autonomous Driving Models
Recent advances in machine learning, especially techniques such as deep ...
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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...
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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...
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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...
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03/12/2019
Simple Physical Adversarial Examples against End-to-End Autonomous Driving Models
Recent advances in machine learning, especially techniques such as deep ...
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01/03/2019
Sparse Learning in reproducing kernel Hilbert space
Sparse learning aims to learn the sparse structure of the true target fu...
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11/10/2018
Scene Text Detection and Recognition: The Deep Learning Era
With the rise and development of deep learning, computer vision has been...
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10/27/2018
On Measurement of the Spatio-Frequency Property of OFDM Backscattering
Orthogonal frequency-division multiplexing (OFDM) backscatter system, su...
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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...
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05/21/2018
AxTrain: Hardware-Oriented Neural Network Training for Approximate Inference
The intrinsic error tolerance of neural network (NN) makes approximate c...
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02/26/2018
Scalable kernel-based variable selection with sparsistency
Variable selection is central to high-dimensional data analysis, and var...
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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...
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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...
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01/23/2001