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09/21/2023
SupeRBNN: Randomized Binary Neural Network Using Adiabatic Superconductor Josephson Devices
Adiabatic Quantum-Flux-Parametron (AQFP) is a superconducting logic with...
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06/01/2023
SnapFusion: Text-to-Image Diffusion Model on Mobile Devices within Two Seconds
Text-to-image diffusion models can create stunning images from natural l...
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04/30/2023
DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning
Rehearsal-based approaches are a mainstay of continual learning (CL). Th...
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03/13/2023
Can Adversarial Examples Be Parsed to Reveal Victim Model Information?
Numerous adversarial attack methods have been developed to generate impe...
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03/05/2023
DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network
The rapid advances in Vision Transformer (ViT) refresh the state-of-the-...
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12/15/2022
Rethinking Vision Transformers for MobileNet Size and Speed
With the success of Vision Transformers (ViTs) in computer vision tasks,...
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12/09/2022
All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management
During the deployment of deep neural networks (DNNs) on edge devices, ma...
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11/22/2022
Self-Ensemble Protection: Training Checkpoints Are Good Data Protectors
As data become increasingly vital for deep learning, a company would be ...
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11/21/2022
You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model
Large-scale Transformer models bring significant improvements for variou...
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11/15/2022
HeatViT: Hardware-Efficient Adaptive Token Pruning for Vision Transformers
While vision transformers (ViTs) have continuously achieved new mileston...
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11/02/2022
The Lottery Ticket Hypothesis for Vision Transformers
The conventional lottery ticket hypothesis (LTH) claims that there exist...
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10/09/2022
Pruning Adversarially Robust Neural Networks without Adversarial Examples
Adversarial pruning compresses models while preserving robustness. Curre...
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10/08/2022
Advancing Model Pruning via Bi-level Optimization
The deployment constraints in practical applications necessitate the pru...
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10/06/2022
DeltaFS: Pursuing Zero Update Overhead via Metadata-Enabled Delta Compression for Log-structured File System on Mobile Devices
Data compression has been widely adopted to release mobile devices from ...
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09/22/2022
Layer Freezing Data Sieving: Missing Pieces of a Generic Framework for Sparse Training
Recently, sparse training has emerged as a promising paradigm for effici...
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09/18/2022
PIM-QAT: Neural Network Quantization for Processing-In-Memory (PIM) Systems
Processing-in-memory (PIM), an increasingly studied neuromorphic hardwar...
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09/18/2022
StereoVoxelNet: Real-Time Obstacle Detection Based on Occupancy Voxels from a Stereo Camera Using Deep Neural Networks
Obstacle detection is a safety-critical problem in robot navigation, whe...
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09/12/2022
Understanding Time Variations of DNN Inference in Autonomous Driving
Deep neural networks (DNNs) are widely used in autonomous driving due to...
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07/04/2022
Quantum Neural Network Compression
Model compression, such as pruning and quantization, has been widely app...
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06/21/2022
CoCoPIE XGen: A Full-Stack AI-Oriented Optimizing Framework
There is a growing demand for shifting the delivery of AI capability fro...
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06/04/2022
Student-AI Creative Writing: Pedagogical Strategies for Applying Natural Language Generation in Schools
AI natural language generation (NLG) is a process where computer systems...
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06/02/2022
Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural Reparameterization
Neural architecture search (NAS) and network pruning are widely studied ...
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06/02/2022
EfficientFormer: Vision Transformers at MobileNet Speed
Vision Transformers (ViT) have shown rapid progress in computer vision t...
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05/12/2022
Neural Network-based OFDM Receiver for Resource Constrained IoT Devices
Orthogonal Frequency Division Multiplexing (OFDM)-based waveforms are us...
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04/09/2022
Deep neural network goes lighter: A case study of deep compression techniques on automatic RF modulation recognition for Beyond 5G networks
Automatic RF modulation recognition is a primary signal intelligence (SI...
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02/10/2022
F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization
Neural network quantization is a promising compression technique to redu...
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02/09/2022
Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets
The lottery ticket hypothesis (LTH) has shown that dense models contain ...
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12/21/2021
Compact Multi-level Sparse Neural Networks with Input Independent Dynamic Rerouting
Deep neural networks (DNNs) have shown to provide superb performance in ...
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10/30/2021
ILMPQ : An Intra-Layer Multi-Precision Deep Neural Network Quantization framework for FPGA
This work targets the commonly used FPGA (field-programmable gate array)...
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10/30/2021
RMSMP: A Novel Deep Neural Network Quantization Framework with Row-wise Mixed Schemes and Multiple Precisions
This work proposes a novel Deep Neural Network (DNN) quantization framew...
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10/27/2021
ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers
Adversarial patch attacks that craft the pixels in a confined region of ...
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09/08/2021
Elastic Significant Bit Quantization and Acceleration for Deep Neural Networks
Quantization has been proven to be a vital method for improving the infe...
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07/06/2021
CAP-RAM: A Charge-Domain In-Memory Computing 6T-SRAM for Accurate and Precision-Programmable CNN Inference
A compact, accurate, and bitwidth-programmable in-memory computing (IMC)...
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07/01/2021
Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot?
There have been long-standing controversies and inconsistencies over the...
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06/16/2021
Improving DNN Fault Tolerance using Weight Pruning and Differential Crossbar Mapping for ReRAM-based Edge AI
Recent research demonstrated the promise of using resistive random acces...
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06/16/2021
FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator
Recent works demonstrated the promise of using resistive random access m...
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06/15/2021
Efficient Micro-Structured Weight Unification and Pruning for Neural Network Compression
Compressing Deep Neural Network (DNN) models to alleviate the storage an...
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03/05/2021
Teachers Do More Than Teach: Compressing Image-to-Image Models
Generative Adversarial Networks (GANs) have achieved huge success in gen...
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02/19/2021
Lottery Ticket Implies Accuracy Degradation, Is It a Desirable Phenomenon?
In deep model compression, the recent finding "Lottery Ticket Hypothesis...
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12/13/2020
Learn-Prune-Share for Lifelong Learning
In lifelong learning, we wish to maintain and update a model (e.g., a ne...
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12/08/2020
Mix and Match: A Novel FPGA-Centric Deep Neural Network Quantization Framework
Deep Neural Networks (DNNs) have achieved extraordinary performance in v...
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11/04/2020
DAIS: Automatic Channel Pruning via Differentiable Annealing Indicator Search
The convolutional neural network has achieved great success in fulfillin...
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09/27/2020
Simultaneous Relevance and Diversity: A New Recommendation Inference Approach
Relevance and diversity are both important to the success of recommender...
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09/16/2020
MSP: An FPGA-Specific Mixed-Scheme, Multi-Precision Deep Neural Network Quantization Framework
With the tremendous success of deep learning, there exists imminent need...
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09/03/2020
ESMFL: Efficient and Secure Models for Federated Learning
Deep Neural Networks are widely applied to various domains. The successf...
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08/14/2020
AntiDote: Attention-based Dynamic Optimization for Neural Network Runtime Efficiency
Convolutional Neural Networks (CNNs) achieved great cognitive performanc...
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08/09/2020
One for Many: Transfer Learning for Building HVAC Control
The design of building heating, ventilation, and air conditioning (HVAC)...
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07/20/2020
Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices
Mobile devices are becoming an important carrier for deep learning tasks...
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05/11/2020
CSB-RNN: A Faster-than-Realtime RNN Acceleration Framework with Compressed Structured Blocks
Recurrent neural networks (RNNs) have been widely adopted in temporal se...
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04/22/2020