research
∙
08/22/2023
Meta-Stock: Task-Difficulty-Adaptive Meta-learning for Sub-new Stock Price Prediction
Sub-new stock price prediction, forecasting the price trends of stocks l...
share
research
∙
08/16/2023
Low-Light Image Enhancement with Illumination-Aware Gamma Correction and Complete Image Modelling Network
This paper presents a novel network structure with illumination-aware ga...
research
∙
06/14/2023
Self-supervised Learning and Graph Classification under Heterophily
Self-supervised learning has shown its promising capability in graph rep...
research
∙
06/12/2023
Controlling Text-to-Image Diffusion by Orthogonal Finetuning
Large text-to-image diffusion models have impressive capabilities in gen...
research
∙
05/18/2023
A Survey on Time-Series Pre-Trained Models
Time-Series Mining (TSM) is an important research area since it shows gr...
research
∙
04/13/2023
Boosting Convolutional Neural Networks with Middle Spectrum Grouped Convolution
This paper proposes a novel module called middle spectrum grouped convol...
research
∙
04/04/2023
Locate Then Generate: Bridging Vision and Language with Bounding Box for Scene-Text VQA
In this paper, we propose a novel multi-modal framework for Scene Text V...
research
∙
03/14/2023
MeshDiffusion: Score-based Generative 3D Mesh Modeling
We consider the task of generating realistic 3D shapes, which is useful ...
research
∙
12/05/2022
Minimum Latency Deep Online Video Stabilization
We present a novel camera path optimization framework for the task of on...
research
∙
10/31/2022
Iterative Teaching by Data Hallucination
We consider the problem of iterative machine teaching, where a teacher s...
research
∙
10/11/2022
Continual Learning by Modeling Intra-Class Variation
It has been observed that neural networks perform poorly when the data o...
research
∙
10/09/2022
SML:Enhance the Network Smoothness with Skip Meta Logit for CTR Prediction
In light of the smoothness property brought by skip connections in ResNe...
research
∙
08/10/2022
Ghost-free High Dynamic Range Imaging with Context-aware Transformer
High dynamic range (HDR) deghosting algorithms aim to generate ghost-fre...
research
∙
07/20/2022
Structural Causal 3D Reconstruction
This paper considers the problem of unsupervised 3D object reconstructio...
research
∙
06/24/2022
An Improved Lattice-Based Ring Signature with Unclaimable Anonymity in the Standard Model
Ring signatures enable a user to sign messages on behalf of an arbitrary...
research
∙
06/02/2022
Expressiveness and Learnability: A Unifying View for Evaluating Self-Supervised Learning
We propose a unifying view to analyze the representation quality of self...
research
∙
05/25/2022
NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results
This paper reviews the challenge on constrained high dynamic range (HDR)...
research
∙
02/03/2022
Generative Flow Networks for Discrete Probabilistic Modeling
We present energy-based generative flow networks (EB-GFN), a novel proba...
research
∙
11/11/2021
Hierarchical clustering by aggregating representatives in sub-minimum-spanning-trees
One of the main challenges for hierarchical clustering is how to appropr...
research
∙
10/27/2021
Iterative Teaching by Label Synthesis
In this paper, we consider the problem of iterative machine teaching, wh...
research
∙
06/03/2021
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning
We present an end-to-end, model-based deep reinforcement learning agent ...
research
∙
05/22/2021
ADNet: Attention-guided Deformable Convolutional Network for High Dynamic Range Imaging
In this paper, we present an attention-guided deformable convolutional n...
research
∙
03/27/2021
LSTM Based Sentiment Analysis for Cryptocurrency Prediction
Recent studies in big data analytics and natural language processing dev...
research
∙
03/02/2021
Learning with Hyperspherical Uniformity
Due to the over-parameterization nature, neural networks are a powerful ...
research
∙
02/23/2021
A Bayesian Spatial Modeling Approach to Mortality Forecasting
This paper extends Bayesian mortality projection models for multiple pop...
research
∙
12/06/2020
A Data-driven Human Responsibility Management System
An ideal safe workplace is described as a place where staffs fulfill res...
research
∙
12/06/2020
Using Machine Learning to Automate Mammogram Images Analysis
Breast cancer is the second leading cause of cancer-related death after ...
research
∙
10/09/2020
Bayesian Poisson Log-normal Model with Regularized Time Structure for Mortality Projection of Multi-population
The improvement of mortality projection is a pivotal topic in the divers...
research
∙
04/09/2020
Orthogonal Over-Parameterized Training
The inductive bias of a neural network is largely determined by the arch...
research
∙
01/15/2020
NEW: A Generic Learning Model for Tie Strength Prediction in Networks
Tie strength prediction, sometimes named weight prediction, is vital in ...
research
∙
12/23/2019
A Compared Study Between Some Subspace Based Algorithms
The technology of face recognition has made some progress in recent year...
research
∙
12/06/2019
Visual-Textual Association with Hardest and Semi-Hard Negative Pairs Mining for Person Search
Searching persons in large-scale image databases with the query of natur...
research
∙
10/28/2019
Neural Similarity Learning
Inner product-based convolution has been the founding stone of convoluti...
research
∙
10/23/2019
Context-endcoding for neural network based skull stripping in magnetic resonance imaging
Skull stripping is usually the first step for most brain analysisprocess...
research
∙
06/12/2019
Compressive Hyperspherical Energy Minimization
Recent work on minimum hyperspherical energy (MHE) has demonstrated its ...
research
∙
04/27/2019
Exponential Family Estimation via Adversarial Dynamics Embedding
We present an efficient algorithm for maximum likelihood estimation (MLE...
research
∙
05/23/2018
Learning towards Minimum Hyperspherical Energy
Neural networks are a powerful class of nonlinear functions that can be ...
research
∙
04/22/2018
Decoupled Networks
Inner product-based convolution has been a central component of convolut...
research
∙
10/31/2017
Deep Forward and Inverse Perceptual Models for Tracking and Prediction
We consider the problems of learning forward models that map state to hi...
research
∙
09/11/2017
One-Shot Learning for Semantic Segmentation
Low-shot learning methods for image classification support learning from...
research
∙
09/15/2015
Kernelized Deep Convolutional Neural Network for Describing Complex Images
With the impressive capability to capture visual content, deep convoluti...
research
∙
10/16/2009
