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09/18/2023
Adaptive Reorganization of Neural Pathways for Continual Learning with Hybrid Spiking Neural Networks
The human brain can self-organize rich and diverse sparse neural pathway...
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09/11/2023
Brain-inspired Evolutionary Architectures for Spiking Neural Networks
The complex and unique neural network topology of the human brain formed...
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08/09/2023
Enhancing Efficient Continual Learning with Dynamic Structure Development of Spiking Neural Networks
Children possess the ability to learn multiple cognitive tasks sequentia...
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06/04/2023
Revisiting Data-Free Knowledge Distillation with Poisoned Teachers
Data-free knowledge distillation (KD) helps transfer knowledge from a pr...
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05/17/2023
Spiking Generative Adversarial Network with Attention Scoring Decoding
Generative models based on neural networks present a substantial challen...
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04/28/2023
LAVA: Data Valuation without Pre-Specified Learning Algorithms
Traditionally, data valuation is posed as a problem of equitably splitti...
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04/21/2023
Emergence of Brain-inspired Small-world Spiking Neural Network through Neuroevolution
Human brain is the product of evolution during hundreds over millions of...
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04/13/2023
Temporal Knowledge Sharing enable Spiking Neural Network Learning from Past and Future
Spiking neural networks have attracted extensive attention from research...
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03/31/2023
Adaptive structure evolution and biologically plausible synaptic plasticity for recurrent spiking neural networks
The architecture design and multi-scale learning principles of the human...
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03/22/2023
Brain-inspired bodily self-perception model that replicates the rubber hand illusion
At the core of bodily self-consciousness is the perception of the owners...
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02/22/2023
ASSET: Robust Backdoor Data Detection Across a Multiplicity of Deep Learning Paradigms
Backdoor data detection is traditionally studied in an end-to-end superv...
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01/29/2023
Exploiting High Performance Spiking Neural Networks with Efficient Spiking Patterns
Spiking Neural Networks (SNNs) use discrete spike sequences to transmit ...
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01/18/2023
Multi-compartment Neuron and Population Encoding improved Spiking Neural Network for Deep Distributional Reinforcement Learning
Inspired by the information processing with binary spikes in the brain, ...
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01/07/2023
A Brain-inspired Memory Transformation based Differentiable Neural Computer for Reasoning-based Question Answering
Reasoning and question answering as a basic cognitive function for human...
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01/05/2023
FireFly: A High-Throughput Hardware Accelerator for Spiking Neural Networks with Efficient DSP and Memory Optimization
Spiking neural networks (SNNs) have been widely used due to their strong...
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11/23/2022
Developmental Plasticity-inspired Adaptive Pruning for Deep Spiking and Artificial Neural Networks
Developmental plasticity plays a prominent role in shaping the brain's s...
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11/22/2022
Adaptive Sparse Structure Development with Pruning and Regeneration for Spiking Neural Networks
Spiking Neural Networks (SNNs) are more biologically plausible and compu...
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11/02/2022
tSF: Transformer-based Semantic Filter for Few-Shot Learning
Few-Shot Learning (FSL) alleviates the data shortage challenge via embed...
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10/12/2022
How to Sift Out a Clean Data Subset in the Presence of Data Poisoning?
Given the volume of data needed to train modern machine learning models,...
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09/19/2022
CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks
Previous works have validated that text generation APIs can be stolen th...
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08/08/2022
Abutting Grating Illusion: Cognitive Challenge to Neural Network Models
Even the state-of-the-art deep learning models lack fundamental abilitie...
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07/11/2022
Brain-inspired Graph Spiking Neural Networks for Commonsense Knowledge Representation and Reasoning
How neural networks in the human brain represent commonsense knowledge, ...
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06/14/2022
Turning a Curse Into a Blessing: Enabling Clean-Data-Free Defenses by Model Inversion
It is becoming increasingly common to utilize pre-trained models provide...
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05/24/2022
EventMix: An Efficient Augmentation Strategy for Event-Based Data
High-quality and challenging event stream datasets play an important rol...
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05/24/2022
DPSNN: A Differentially Private Spiking Neural Network
Privacy-preserving is a key problem for the machine learning algorithm. ...
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04/11/2022
Narcissus: A Practical Clean-Label Backdoor Attack with Limited Information
Backdoor attacks insert malicious data into a training set so that, duri...
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03/18/2022
FORCE: A Framework of Rule-Based Conversational Recommender System
The conversational recommender systems (CRSs) have received extensive at...
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10/17/2021
Backpropagation with Biologically Plausible Spatio-Temporal Adjustment For Training Deep Spiking Neural Networks
The spiking neural network (SNN) mimics the information processing opera...
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10/07/2021
Adversarial Unlearning of Backdoors via Implicit Hypergradient
We propose a minimax formulation for removing backdoors from a given poi...
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06/10/2021
A Unified Framework for Task-Driven Data Quality Management
High-quality data is critical to train performant Machine Learning (ML) ...
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04/07/2021
Rethinking the Backdoor Attacks' Triggers: A Frequency Perspective
Backdoor attacks have been considered a severe security threat to deep l...
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03/27/2021
SelfGait: A Spatiotemporal Representation Learning Method for Self-supervised Gait Recognition
Gait recognition plays a vital role in human identification since gait i...
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12/13/2020
DeepSweep: An Evaluation Framework for Mitigating DNN Backdoor Attacks using Data Augmentation
Public resources and services (e.g., datasets, training platforms, pre-t...
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12/03/2020
FenceBox: A Platform for Defeating Adversarial Examples with Data Augmentation Techniques
It is extensively studied that Deep Neural Networks (DNNs) are vulnerabl...
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10/23/2020
Quantum Superposition Spiking Neural Network
Quantum brain as a novel hypothesis states that some non-trivial mechani...
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09/18/2020
The Hidden Vulnerability of Watermarking for Deep Neural Networks
Watermarking has shown its effectiveness in protecting the intellectual ...
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07/30/2020
A Data Augmentation-based Defense Method Against Adversarial Attacks in Neural Networks
Deep Neural Networks (DNNs) in Computer Vision (CV) are well-known to be...
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06/07/2020
SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds
Accurate 3D object detection from point clouds has become a crucial comp...
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05/27/2020
Mitigating Advanced Adversarial Attacks with More Advanced Gradient Obfuscation Techniques
Deep Neural Networks (DNNs) are well-known to be vulnerable to Adversari...
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09/19/2019
Responsible Facial Recognition and Beyond
Facial recognition is changing the way we live in and interact with our ...
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08/26/2019
TEST: an End-to-End Network Traffic Examination and Identification Framework Based on Spatio-Temporal Features Extraction
With more encrypted network traffic gets involved in the Internet, how t...
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08/20/2019
Towards High-Resolution Salient Object Detection
Deep neural network based methods have made a significant breakthrough i...
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08/14/2019
FlexNER: A Flexible LSTM-CNN Stack Framework for Named Entity Recognition
Named entity recognition (NER) is a foundational technology for informat...
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12/12/2018
