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01/26/2023
Distilling Cognitive Backdoor Patterns within an Image
This paper proposes a simple method to distill and detect backdoor patte...
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11/15/2022
Backdoor Attacks on Time Series: A Generative Approach
Backdoor attacks have emerged as one of the major security threats to de...
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09/21/2022
Adaptive Local-Component-aware Graph Convolutional Network for One-shot Skeleton-based Action Recognition
Skeleton-based action recognition receives increasing attention because ...
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07/25/2022
IGFormer: Interaction Graph Transformer for Skeleton-based Human Interaction Recognition
Human interaction recognition is very important in many applications. On...
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06/14/2022
A Survey of Automated Data Augmentation Algorithms for Deep Learning-based Image Classication Tasks
In recent years, one of the most popular techniques in the computer visi...
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12/15/2021
On the Convergence and Robustness of Adversarial Training
Improving the robustness of deep neural networks (DNNs) to adversarial e...
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10/26/2021
Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression
Bounding box (bbox) regression is a fundamental task in computer vision....
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10/24/2021
De Novo Molecular Generation with Stacked Adversarial Model
Generating novel drug molecules with desired biological properties is a ...
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10/07/2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
Deep neural networks (DNNs) are known to be vulnerable to adversarial at...
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08/23/2021
Semantic-Preserving Adversarial Text Attacks
Deep neural networks (DNNs) are known to be vulnerable to adversarial im...
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04/21/2021
Dual Head Adversarial Training
Deep neural networks (DNNs) are known to be vulnerable to adversarial ex...
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04/02/2021
GAVIN: Gaze-Assisted Voice-Based Implicit Note-taking
Annotation is an effective reading strategy people often undertake while...
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01/18/2021
What Do Deep Nets Learn? Class-wise Patterns Revealed in the Input Space
Deep neural networks (DNNs) have been widely adopted in different applic...
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01/17/2021
Adversarial Interaction Attack: Fooling AI to Misinterpret Human Intentions
Understanding the actions of both humans and artificial intelligence (AI...
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01/13/2021
Unlearnable Examples: Making Personal Data Unexploitable
The volume of "free" data on the internet has been key to the current su...
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01/01/2021
Neural Architecture Search via Combinatorial Multi-Armed Bandit
Neural Architecture Search (NAS) has gained significant popularity as an...
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12/05/2020
Using voice note-taking to promote learners' conceptual understanding
Though recent technological advances have enabled note-taking through di...
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12/04/2020
Divide and Learn: A Divide and Conquer Approach for Predict+Optimize
The predict+optimize problem combines machine learning ofproblem coeffic...
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07/24/2020
MurTree: Optimal Classification Trees via Dynamic Programming and Search
Decision tree learning is a widely used approach in machine learning, fa...
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07/05/2020
Reflection Backdoor: A Natural Backdoor Attack on Deep Neural Networks
Recent studies have shown that DNNs can be compromised by backdoor attac...
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06/24/2020
Imbalanced Gradients: A New Cause of Overestimated Adversarial Robustness
Evaluating the robustness of a defense model is a challenging task in ad...
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06/24/2020
Normalized Loss Functions for Deep Learning with Noisy Labels
Robust loss functions are essential for training accurate deep neural ne...
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03/06/2020
Clean-Label Backdoor Attacks on Video Recognition Models
Deep neural networks (DNNs) are vulnerable to backdoor attacks which can...
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02/14/2020
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets
Skip connections are an essential component of current state-of-the-art ...
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08/16/2019
Symmetric Cross Entropy for Robust Learning with Noisy Labels
Training accurate deep neural networks (DNNs) in the presence of noisy l...
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07/24/2019
Understanding Adversarial Attacks on Deep Learning Based Medical Image Analysis Systems
Deep neural networks (DNNs) have become popular for medical image analys...
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05/07/2019
FCC-GAN: A Fully Connected and Convolutional Net Architecture for GANs
Generative Adversarial Networks (GANs) are a powerful class of generativ...
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05/02/2019
Quality Evaluation of GANs Using Cross Local Intrinsic Dimensionality
Generative Adversarial Networks (GANs) are an elegant mechanism for data...
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04/10/2019
Black-box Adversarial Attacks on Video Recognition Models
Deep neural networks (DNNs) are known for their vulnerability to adversa...
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07/22/2018
Learning Deep Hidden Nonlinear Dynamics from Aggregate Data
Learning nonlinear dynamics from diffusion data is a challenging problem...
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06/07/2018
Dimensionality-Driven Learning with Noisy Labels
Datasets with significant proportions of noisy (incorrect) class labels ...
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03/31/2018
Iterative Learning with Open-set Noisy Labels
Large-scale datasets possessing clean label annotations are crucial for ...
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01/08/2018
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality
Deep Neural Networks (DNNs) have recently been shown to be vulnerable ag...
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01/08/2018
Online Cluster Validity Indices for Streaming Data
Cluster analysis is used to explore structure in unlabeled data sets in ...
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06/30/2017
Providing Effective Real-time Feedback in Simulation-based Surgical Training
Virtual reality simulation is becoming popular as a training platform in...
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03/04/2017
Adversarial Generation of Real-time Feedback with Neural Networks for Simulation-based Training
Simulation-based training (SBT) is gaining popularity as a low-cost and ...
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07/29/2016
TopicResponse: A Marriage of Topic Modelling and Rasch Modelling for Automatic Measurement in MOOCs
This paper explores the suitability of using automatically discovered to...
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06/17/2016
Ground Truth Bias in External Cluster Validity Indices
It has been noticed that some external CVIs exhibit a preferential bias ...
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12/03/2015
Adjusting for Chance Clustering Comparison Measures
Adjusted for chance measures are widely used to compare partitions/clust...
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10/27/2015
A Framework to Adjust Dependency Measure Estimates for Chance
Estimating the strength of dependency between two variables is fundament...
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02/16/2015