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08/19/2023
Physics-Guided Human Motion Capture with Pose Probability Modeling
Incorporating physics in human motion capture to avoid artifacts like fl...
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07/19/2023
Multi-Grained Multimodal Interaction Network for Entity Linking
Multimodal entity linking (MEL) task, which aims at resolving ambiguous ...
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07/03/2023
A Comprehensive Survey of Artificial Intelligence Techniques for Talent Analytics
In today's competitive and fast-evolving business environment, it is a c...
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06/28/2023
On the Exploitability of Instruction Tuning
Instruction tuning is an effective technique to align large language mod...
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05/31/2023
A Survey on Large Language Models for Recommendation
Large Language Models (LLMs) have emerged as powerful tools in the field...
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05/21/2023
Social Context-aware GCN for Video Character Search via Scene-prior Enhancement
With the increasing demand for intelligent services of online video plat...
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05/03/2023
DELTA: Direct Embedding Enhancement and Leverage Truncated Conscious Attention for Recommendation System
Click-Through Rate (CTR) prediction is the most critical task in product...
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12/15/2022
Multi-Level Association Rule Mining for Wireless Network Time Series Data
Key performance indicators(KPIs) are of great significance in the monito...
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12/11/2022
CPMLHO:Hyperparameter Tuning via Cutting Plane and Mixed-Level Optimization
The hyperparameter optimization of neural network can be expressed as a ...
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11/02/2022
Heterogeneous Trajectory Forecasting via Risk and Scene Graph Learning
Heterogeneous trajectory forecasting is critical for intelligent transpo...
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05/20/2022
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors
Deep learning is increasingly moving towards a transfer learning paradig...
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05/12/2022
Outage Analysis of Aerial Semi-Grant-Free NOMA Systems
In this paper, we analyze the outage performance of unmanned aerial vehi...
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01/31/2022
Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations
Existing techniques for model inversion typically rely on hard-to-tune r...
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10/27/2021
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization
Most state-of-the-art Graph Neural Networks (GNNs) can be defined as a f...
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10/26/2021
Understanding the Role of Self-Supervised Learning in Out-of-Distribution Detection Task
Self-supervised learning (SSL) has achieved great success in a variety o...
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07/05/2021
Long-Short Transformer: Efficient Transformers for Language and Vision
Transformers have achieved success in both language and vision domains. ...
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04/18/2021
The Intrinsic Dimension of Images and Its Impact on Learning
It is widely believed that natural image data exhibits low-dimensional s...
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02/16/2021
GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training
Changes in neural architectures have fostered significant breakthroughs ...
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12/08/2020
LAMP: Label Augmented Multimodal Pretraining
Multi-modal representation learning by pretraining has become an increas...
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12/01/2020
Modifying Memories in Transformer Models
Large Transformer models have achieved impressive performance in many na...
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10/24/2020
Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks
Adversarial Training is proved to be an efficient method to defend again...
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10/15/2020
Spherical Knowledge Distillation
Knowledge distillation aims at obtaining a small but effective deep mode...
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10/14/2020
Towards Accurate Quantization and Pruning via Data-free Knowledge Transfer
When large scale training data is available, one can obtain compact and ...
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06/21/2020
Adaptive Learning Rates with Maximum Variation Averaging
Adaptive gradient methods such as RMSProp and Adam use exponential movin...
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06/11/2020
Large-Scale Adversarial Training for Vision-and-Language Representation Learning
We present VILLA, the first known effort on large-scale adversarial trai...
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04/20/2020
Headless Horseman: Adversarial Attacks on Transfer Learning Models
Transfer learning facilitates the training of task-specific classifiers ...
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03/14/2020
Certified Defenses for Adversarial Patches
Adversarial patch attacks are among one of the most practical threat mod...
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02/23/2020
SetRank: A Setwise Bayesian Approach for Collaborative Ranking from Implicit Feedback
The recent development of online recommender systems has a focus on coll...
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02/22/2020
Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers
Convex relaxations are effective for training and certifying neural netw...
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12/11/2019
Learning from Noisy Anchors for One-stage Object Detection
State-of-the-art object detectors rely on regressing and classifying an ...
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09/29/2019
Strong Baseline Defenses Against Clean-Label Poisoning Attacks
Targeted clean-label poisoning is a type of adversarial attack on machin...
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09/25/2019
FreeLB: Enhanced Adversarial Training for Language Understanding
Adversarial training, which minimizes the maximal risk for label-preserv...
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05/20/2019
Adversarially robust transfer learning
Transfer learning, in which a network is trained on one task and re-purp...
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05/15/2019
Transferable Clean-Label Poisoning Attacks on Deep Neural Nets
In this paper, we explore clean-label poisoning attacks on deep convolut...
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12/21/2018
Enhancing Person-Job Fit for Talent Recruitment: An Ability-aware Neural Network Approach
The wide spread use of online recruitment services has led to informatio...
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10/26/2018
Fine-grained Video Categorization with Redundancy Reduction Attention
For fine-grained categorization tasks, videos could serve as a better so...
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10/08/2018
Person-Job Fit: Adapting the Right Talent for the Right Job with Joint Representation Learning
Person-Job Fit is the process of matching the right talent for the right...
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10/02/2018
Fusion of Monocular Vision and Radio-based Ranging for Global Scale Estimation and Drift Mitigation
Monocular vision-based Simultaneous Localization and Mapping (SLAM) is u...
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06/13/2018
Learning Visual Knowledge Memory Networks for Visual Question Answering
Visual question answering (VQA) requires joint comprehension of images a...
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02/28/2018
Compressing Neural Networks using the Variational Information Bottleneck
Neural networks can be compressed to reduce memory and computational req...
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12/08/2017
Collaborative Company Profiling: Insights from an Employee's Perspective
Company profiling is an analytical process to build an indepth understan...
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12/08/2017
Recruitment Market Trend Analysis with Sequential Latent Variable Models
Recruitment market analysis provides valuable understanding of industry-...
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12/06/2017
Measuring the Popularity of Job Skills in Recruitment Market: A Multi-Criteria Approach
To cope with the accelerating pace of technological changes, talents are...
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08/07/2017