research
∙
07/31/2023
Accelerating Optimal Power Flow with GPUs: SIMD Abstraction of Nonlinear Programs and Condensed-Space Interior-Point Methods
This paper introduces a novel computational framework for solving altern...
share
research
∙
03/08/2023
Enhancing Low-resolution Face Recognition with Feature Similarity Knowledge Distillation
In this study, we introduce a feature knowledge distillation framework t...
research
∙
12/22/2022
Scalable Primal Decomposition Schemes for Large-Scale Infrastructure Networks
The real-time operation of large-scale infrastructure networks requires ...
research
∙
12/05/2022
Block Selection Method for Using Feature Norm in Out-of-distribution Detection
Detecting out-of-distribution (OOD) inputs during the inference stage is...
research
∙
09/29/2022
Teaching Where to Look: Attention Similarity Knowledge Distillation for Low Resolution Face Recognition
Deep learning has achieved outstanding performance for face recognition ...
research
∙
04/12/2022
Near-Optimal Distributed Linear-Quadratic Regulator for Networked Systems
This paper studies the trade-off between the degree of decentralization ...
research
∙
01/07/2021
Object Detection for Understanding Assembly Instruction Using Context-aware Data Augmentation and Cascade Mask R-CNN
Understanding assembly instruction has the potential to enhance the robo...
research
∙
09/30/2020
Stochastic Precision Ensemble: Self-Knowledge Distillation for Quantized Deep Neural Networks
The quantization of deep neural networks (QDNNs) has been actively studi...
research
∙
09/05/2020
S-SGD: Symmetrical Stochastic Gradient Descent with Weight Noise Injection for Reaching Flat Minima
The stochastic gradient descent (SGD) method is most widely used for dee...
research
∙
08/22/2020
Multiple Classification with Split Learning
Privacy issues were raised in the process of training deep learning in m...
research
∙
05/31/2020
Quantized Neural Networks: Characterization and Holistic Optimization
Quantized deep neural networks (QDNNs) are necessary for low-power, high...
research
∙
05/14/2020
Overlapping Schwarz Decomposition for Nonlinear Optimal Control
We present an overlapping Schwarz decomposition algorithm for solving no...
research
∙
03/16/2020
Unifying Theorems for Subspace Identification and Dynamic Mode Decomposition
This paper presents unifying results for subspace identification (SID) a...
research
∙
03/12/2020
On the Convergence of the Dynamic Inner PCA Algorithm
Dynamic inner principal component analysis (DiPCA) is a powerful method ...
research
∙
02/02/2020
SQWA: Stochastic Quantized Weight Averaging for Improving the Generalization Capability of Low-Precision Deep Neural Networks
Designing a deep neural network (DNN) with good generalization capabilit...
research
∙
09/04/2019
Empirical Analysis of Knowledge Distillation Technique for Optimization of Quantized Deep Neural Networks
Knowledge distillation (KD) is a very popular method for model size redu...
research
∙
11/05/2018
Workload-aware Automatic Parallelization for Multi-GPU DNN Training
Deep neural networks (DNNs) have emerged as successful solutions for var...
research
∙
11/19/2016
Quantized neural network design under weight capacity constraint
The complexity of deep neural network algorithms for hardware implementa...
research
∙
08/14/2016
Dynamic Hand Gesture Recognition for Wearable Devices with Low Complexity Recurrent Neural Networks
Gesture recognition is a very essential technology for many wearable dev...
research
∙
12/04/2015
Fixed-Point Performance Analysis of Recurrent Neural Networks
Recurrent neural networks have shown excellent performance in many appli...
research
∙
11/20/2015