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08/14/2023
MixBCT: Towards Self-Adapting Backward-Compatible Training
The exponential growth of data, alongside advancements in model structur...
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06/26/2023
Incorporating increased variability in testing for cancer DNA methylation
Cancer development is associated with aberrant DNA methylation, includin...
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06/19/2023
NAR-Former V2: Rethinking Transformer for Universal Neural Network Representation Learning
As more deep learning models are being applied in real-world application...
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05/29/2023
Perimeter Control Using Deep Reinforcement Learning: A Model-free Approach towards Homogeneous Flow Rate Optimization
Perimeter control maintains high traffic efficiency within protected reg...
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05/14/2023
Path Planning for Air-Ground Robot Considering Modal Switching Point Optimization
An innovative sort of mobility platform that can both drive and fly is t...
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05/01/2023
Boosting Weakly-Supervised Temporal Action Localization with Text Information
Due to the lack of temporal annotation, current Weakly-supervised Tempor...
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03/01/2023
A Lifted Bregman Formulation for the Inversion of Deep Neural Networks
We propose a novel framework for the regularised inversion of deep neura...
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01/28/2023
Few-shot Face Image Translation via GAN Prior Distillation
Face image translation has made notable progress in recent years. Howeve...
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12/19/2022
Million-scale Object Detection with Large Vision Model
Over the past few years, developing a broad, universal, and general-purp...
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12/08/2022
All-to-key Attention for Arbitrary Style Transfer
Attention-based arbitrary style transfer studies have shown promising pe...
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11/27/2022
Deep Active Learning for Computer Vision: Past and Future
As an important data selection schema, active learning emerges as the es...
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11/26/2022
A Critical Review of Traffic Signal Control and A Novel Unified View of Reinforcement Learning and Model Predictive Control Approaches for Adaptive Traffic Signal Control
Recent years have witnessed substantial growth in adaptive traffic signa...
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11/18/2022
Being Bayesian in the 2020s: opportunities and challenges in the practice of modern applied Bayesian statistics
Building on a strong foundation of philosophy, theory, methods and compu...
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11/15/2022
NAR-Former: Neural Architecture Representation Learning towards Holistic Attributes Prediction
With the wide and deep adoption of deep learning models in real applicat...
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11/14/2022
CabViT: Cross Attention among Blocks for Vision Transformer
Since the vision transformer (ViT) has achieved impressive performance i...
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11/14/2022
ParCNetV2: Oversized Kernel with Enhanced Attention
Transformers have achieved tremendous success in various computer vision...
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10/30/2022
A Multi-modal Deformable Land-air Robot for Complex Environments
Single locomotion robots often struggle to adapt in highly variable or u...
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10/08/2022
Fast-ParC: Position Aware Global Kernel for ConvNets and ViTs
Transformer models have made tremendous progress in various fields in re...
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10/06/2022
Predictive Edge Caching through Deep Mining of Sequential Patterns in User Content Retrievals
Edge caching plays an increasingly important role in boosting user conte...
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08/18/2022
Lifted Bregman Training of Neural Networks
We introduce a novel mathematical formulation for the training of feed-f...
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07/27/2022
ALBench: A Framework for Evaluating Active Learning in Object Detection
Active learning is an important technology for automated machine learnin...
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07/25/2022
Improving Adversarial Robustness via Mutual Information Estimation
Deep neural networks (DNNs) are found to be vulnerable to adversarial no...
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07/04/2022
Multi-Modal Multi-Correlation Learning for Audio-Visual Speech Separation
In this paper we propose a multi-modal multi-correlation learning framew...
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05/22/2022
Commonsense Knowledge Salience Evaluation with a Benchmark Dataset in E-commerce
In e-commerce, the salience of commonsense knowledge (CSK) is beneficial...
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03/26/2022
Implementation of an Automated Learning System for Non-experts
Automated machine learning systems for non-experts could be critical for...
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03/23/2022
Towards Semi-Supervised Deep Facial Expression Recognition with An Adaptive Confidence Margin
Only parts of unlabeled data are selected to train models for most semi-...
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03/21/2022
FaceMap: Towards Unsupervised Face Clustering via Map Equation
Face clustering is an essential task in computer vision due to the explo...
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03/08/2022
EdgeFormer: Improving Light-weight ConvNets by Learning from Vision Transformers
Recently, vision transformers started to show impressive results which o...
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03/04/2022
Semi-parametric Makeup Transfer via Semantic-aware Correspondence
The large discrepancy between the source non-makeup image and the refere...
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01/25/2022
On Uniform Boundedness Properties of SGD and its Momentum Variants
A theoretical, and potentially also practical, problem with stochastic g...
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11/19/2021
YMIR: A Rapid Data-centric Development Platform for Vision Applications
This paper introduces an open source platform for rapid development of c...
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10/19/2021
Multilevel Stochastic Optimization for Imputation in Massive Medical Data Records
Exploration and analysis of massive datasets has recently generated incr...
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07/30/2021
Enhancing Social Relation Inference with Concise Interaction Graph and Discriminative Scene Representation
There has been a recent surge of research interest in attacking the prob...
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07/30/2021
Compression Network with Transformer for Approximate Nearest Neighbor Search
We propose a generic feature compression method for Approximate Nearest ...
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06/10/2021
Improving White-box Robustness of Pre-processing Defenses via Joint Adversarial Training
Deep neural networks (DNNs) are vulnerable to adversarial noise. A range...
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06/05/2021
Bandwidth-based Step-Sizes for Non-Convex Stochastic Optimization
Many popular learning-rate schedules for deep neural networks combine a ...
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04/19/2021
Removing Adversarial Noise in Class Activation Feature Space
Deep neural networks (DNNs) are vulnerable to adversarial noise. Preproc...
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02/19/2021
SEPAL: Towards a Large-scale Analysis of SEAndroid Policy Customization
To investigate the status quo of SEAndroid policy customization, we prop...
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02/18/2021
On the Convergence of Step Decay Step-Size for Stochastic Optimization
The convergence of stochastic gradient descent is highly dependent on th...
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02/13/2021
Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections
Gaussian noise injections (GNIs) are a family of simple and widely-used ...
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12/07/2020
Generalised Perceptron Learning
We present a generalisation of Rosenblatt's traditional perceptron learn...
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11/16/2020
MAAC: Novel Alert Correlation Method To Detect Multi-step Attack
With the continuous improvement of attack methods, there are more and mo...
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07/03/2020
Weakly Supervised Temporal Action Localization with Segment-Level Labels
Temporal action localization presents a trade-off between test performan...
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04/20/2020
Robust Partial Matching for Person Search in the Wild
Various factors like occlusions, backgrounds, etc., would lead to misali...
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04/06/2020
Non-Convex Stochastic Optimization via Non-Reversible Stochastic Gradient Langevin Dynamics
Stochastic gradient Langevin dynamics (SGLD) is a poweful algorithm for ...
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03/09/2020
Revisiting SGD with Increasingly Weighted Averaging: Optimization and Generalization Perspectives
Stochastic gradient descent (SGD) has been widely studied in the literat...
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02/05/2020
A Reinforcement Learning Framework for Time-Dependent Causal Effects Evaluation in A/B Testing
A/B testing, or online experiment is a standard business strategy to com...
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12/24/2019
a simple and effective framework for pairwise deep metric learning
Deep metric learning (DML) has received much attention in deep learning ...
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11/19/2019
Distributed Generative Adversarial Net
Recently the Generative Adversarial Network has become a hot topic. Cons...
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08/26/2019