
Evading RealTime Person Detectors by Adversarial Tshirt
It is known that deep neural networks (DNNs) could be vulnerable to adve...
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MultiChannel Attention Selection GAN with Cascaded Semantic Guidance for CrossView Image Translation
Crossview image translation is challenging because it involves images w...
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Embedding Compression with Isotropic Iterative Quantization
Continuous representation of words is a standard component in deep learn...
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Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation
The stateofart DNN structures involve intensive computation and high m...
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An Image Enhancing Patternbased Sparsity for Realtime Inference on Mobile Devices
Weight pruning has been widely acknowledged as a straightforward and eff...
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Structured Adversarial Attack: Towards General Implementation and Better Interpretability
When generating adversarial examples to attack deep neural networks (DNN...
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Progressive Weight Pruning of Deep Neural Networks using ADMM
Deep neural networks (DNNs) although achieving humanlevel performance i...
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Progressive DNN Compression: A Key to Achieve UltraHigh Weight Pruning and Quantization Rates using ADMM
Weight pruning and weight quantization are two important categories of D...
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PatDNN: Achieving RealTime DNN Execution on Mobile Devices with Patternbased Weight Pruning
With the emergence of a spectrum of highend mobile devices, many applic...
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PCNN: Patternbased FineGrained Regular Pruning towards Optimizing CNN Accelerators
Weight pruning is a powerful technique to realize model compression. We ...
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A Unified DNN Weight Compression Framework Using Reweighted Optimization Methods
To address the large model size and intensive computation requirement of...
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Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space
Recent advances in the field of artificial intelligence have been made p...
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PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Realtime Execution on Mobile Devices
Model compression techniques on Deep Neural Network (DNN) have been wide...
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A Unified Framework of DNN Weight Pruning and Weight Clustering/Quantization Using ADMM
Many model compression techniques of Deep Neural Networks (DNNs) have be...
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ADMMNN: An AlgorithmHardware CoDesign Framework of DNNs Using Alternating Direction Method of Multipliers
To facilitate efficient embedded and hardware implementations of deep ne...
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An UltraEfficient MemristorBased DNN Framework with Structured Weight Pruning and Quantization Using ADMM
The high computation and memory storage of large deep neural networks (D...
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BLKREW: A Unified Blockbased DNN Pruning Framework using Reweighted Regularization Method
Accelerating DNN execution on various resourcelimited computing platfor...
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CocoPIE: Making Mobile AI Sweet As PIE –CompressionCompilation CoDesign Goes a Long Way
Assuming hardware is the major constraint for enabling realtime mobile ...
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Second Rethinking of Network Pruning in the Adversarial Setting
It is well known that deep neural networks (DNNs) are vulnerable to adve...
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Braininspired reverse adversarial examples
A human does not have to see all elephants to recognize an animal as an ...
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Toward Extremely Low Bit and Lossless Accuracy in DNNs with Progressive ADMM
Weight quantization is one of the most important techniques of Deep Neur...
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Protecting Neural Networks with Hierarchical Random Switching: Towards Better RobustnessAccuracy Tradeoff for Stochastic Defenses
Despite achieving remarkable success in various domains, recent studies ...
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Nonstructured DNN Weight Pruning Considered Harmful
Large deep neural network (DNN) models pose the key challenge to energy ...
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AutoSlim: An Automatic DNN Structured Pruning Framework for UltraHigh Compression Rates
Structured weight pruning is a representative model compression techniqu...
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Deep Reinforcement Learning: Framework, Applications, and Embedded Implementations
The recent breakthroughs of deep reinforcement learning (DRL) technique ...
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A MemristorBased Optimization Framework for AI Applications
Memristors have recently received significant attention as ubiquitous de...
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CirCNN: Accelerating and Compressing Deep Neural Networks Using BlockCirculantWeight Matrices
Largescale deep neural networks (DNNs) are both compute and memory inte...
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HardwareDriven Nonlinear Activation for Stochastic Computing Based Deep Convolutional Neural Networks
Recently, Deep Convolutional Neural Networks (DCNNs) have made unprecede...
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Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank
Recently low displacement rank (LDR) matrices, or socalled structured m...
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SCDCNN: HighlyScalable Deep Convolutional Neural Network using Stochastic Computing
With recent advancing of Internet of Things (IoTs), it becomes very attr...
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FFTBased Deep Learning Deployment in Embedded Systems
Deep learning has delivered its powerfulness in many application domains...
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Deep Reinforcement Learning for Dynamic Treatment Regimes on Medical Registry Data
This paper presents the first deep reinforcement learning (DRL) framewor...
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Image Dataset for Visual Objects Classification in 3D Printing
The rapid development in additive manufacturing (AM), also known as 3D p...
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Systematic Weight Pruning of DNNs using Alternating Direction Method of Multipliers
We present a systematic weight pruning framework of deep neural networks...
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Towards UltraHigh Performance and Energy Efficiency of Deep Learning Systems: An AlgorithmHardware CoOptimization Framework
Hardware accelerations of deep learning systems have been extensively in...
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Security Analysis and Enhancement of Model Compressed Deep Learning Systems under Adversarial Attacks
DNN is presenting humanlevel performance for many complex intelligent t...
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Efficient Recurrent Neural Networks using Structured Matrices in FPGAs
Recurrent Neural Networks (RNNs) are becoming increasingly important for...
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On the Universal Approximation Property and Equivalence of Stochastic Computingbased Neural Networks and Binary Neural Networks
Largescale deep neural networks are both memory intensive and computati...
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C3PO: Database and Benchmark for Earlystage Malicious Activity Detection in 3D Printing
Increasing malicious users have sought practices to leverage 3D printing...
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Experiencedriven Networking: A Deep Reinforcement Learning based Approach
Modern communication networks have become very complicated and highly dy...
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A Systematic DNN Weight Pruning Framework using Alternating Direction Method of Multipliers
Weight pruning methods for deep neural networks (DNNs) have been investi...
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An ADMMBased Universal Framework for Adversarial Attacks on Deep Neural Networks
Deep neural networks (DNNs) are known vulnerable to adversarial attacks....
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An Area and Energy Efficient Design of DomainWall MemoryBased Deep Convolutional Neural Networks using Stochastic Computing
With recent trend of wearable devices and Internet of Things (IoTs), it ...
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ModelFree Control for Distributed Stream Data Processing using Deep Reinforcement Learning
In this paper, we focus on generalpurpose Distributed Stream Data Proce...
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Feature Distillation: DNNOriented JPEG Compression Against Adversarial Examples
Deep Neural Networks (DNNs) have achieved remarkable performance in a my...
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Towards Robust Training of Neural Networks by Regularizing Adversarial Gradients
In recent years, neural networks have demonstrated outstanding effective...
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Adversarial MetaLearning
Metalearning enables a model to learn from very limited data to underta...
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Learning Topics using Semantic Locality
The topic modeling discovers the latent topic probability of the given t...
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Towards BudgetDriven Hardware Optimization for Deep Convolutional Neural Networks using Stochastic Computing
Recently, Deep Convolutional Neural Network (DCNN) has achieved tremendo...
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Interpreting Adversarial Robustness: A View from Decision Surface in Input Space
One popular hypothesis of neural network generalization is that the flat...
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Yanzhi Wang
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Assistant Professor at Department of Electrical Engineering and Computer Science at Syracuse University, Ph.D. Degree in Computer Engineering from University of Southern California (USC) in 2014, Research Assistant at University of Southern California from 20092014, Visiting Student at Seoul National University 2012, Summer Intern at Sharp Laboratories of America 2011