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08/16/2023
Towards Zero Memory Footprint Spiking Neural Network Training
Biologically-inspired Spiking Neural Networks (SNNs), processing informa...
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07/08/2022
FAIVConf: Face enhancement for AI-based Video Conference with Low Bit-rate
Recently, high-quality video conferencing with fewer transmission bits h...
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01/28/2022
A Secure and Efficient Federated Learning Framework for NLP
In this work, we consider the problem of designing secure and efficient ...
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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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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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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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02/19/2020
RTMobile: Beyond Real-Time Mobile Acceleration of RNNs for Speech Recognition
Recurrent neural networks (RNNs) based automatic speech recognition has ...
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01/20/2020
An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices
Weight pruning has been widely acknowledged as a straightforward and eff...
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01/01/2020
PatDNN: Achieving Real-Time DNN Execution on Mobile Devices with Pattern-based Weight Pruning
With the emergence of a spectrum of high-end mobile devices, many applic...
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11/24/2019
A SOT-MRAM-based Processing-In-Memory Engine for Highly Compressed DNN Implementation
The computing wall and data movement challenges of deep neural networks ...
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11/19/2019
DARB: A Density-Aware Regular-Block Pruning for Deep Neural Networks
The rapidly growing parameter volume of deep neural networks (DNNs) hind...
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11/04/2019
Deep Compressed Pneumonia Detection for Low-Power Embedded Devices
Deep neural networks (DNNs) have been expanded into medical fields and t...
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09/04/2019
Learning Dynamic Context Augmentation for Global Entity Linking
Despite of the recent success of collective entity linking (EL) methods,...
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08/29/2019
An Ultra-Efficient Memristor-Based 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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08/27/2019
Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation
The state-of-art DNN structures involve intensive computation and high m...
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07/03/2019
Non-structured DNN Weight Pruning Considered Harmful
Large deep neural network (DNN) models pose the key challenge to energy ...
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06/13/2019
KCAT: A Knowledge-Constraint Typing Annotation Tool
Fine-grained Entity Typing is a tough task which suffers from noise samp...
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05/02/2019
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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04/30/2019
ResNet Can Be Pruned 60x: Introducing Network Purification and Unused Path Removal (P-RM) after Weight Pruning
The state-of-art DNN structures involve high computation and great deman...
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03/23/2019
Progressive DNN Compression: A Key to Achieve Ultra-High Weight Pruning and Quantization Rates using ADMM
Weight pruning and weight quantization are two important categories of D...
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04/11/2018
Learning Topics using Semantic Locality
The topic modeling discovers the latent topic probability of the given t...
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12/13/2017