research
∙
01/27/2023
Adapting Step-size: A Unified Perspective to Analyze and Improve Gradient-based Methods for Adversarial Attacks
Learning adversarial examples can be formulated as an optimization probl...
share
research
∙
08/08/2022
A high-resolution dynamical view on momentum methods for over-parameterized neural networks
In this paper, we present the convergence analysis of momentum methods i...
research
∙
05/26/2022
QSpeech: Low-Qubit Quantum Speech Application Toolkit
Quantum devices with low qubits are common in the Noisy Intermediate-Sca...
research
∙
04/18/2022
A Convergence Analysis of Nesterov's Accelerated Gradient Method in Training Deep Linear Neural Networks
Momentum methods, including heavy-ball (HB) and Nesterov's accelerated g...
research
∙
03/14/2022
A Systematic Review on Affective Computing: Emotion Models, Databases, and Recent Advances
Affective computing plays a key role in human-computer interactions, ent...
research
∙
07/12/2021
On the Evaluation of Commit Message Generation Models: An Experimental Study
Commit messages are natural language descriptions of code changes, which...
research
∙
04/29/2021
CASSOD-Net: Cascaded and Separable Structures of Dilated Convolution for Embedded Vision Systems and Applications
The field of view (FOV) of convolutional neural networks is highly relat...
research
∙
04/29/2021
Hardware Architecture of Embedded Inference Accelerator and Analysis of Algorithms for Depthwise and Large-Kernel Convolutions
In order to handle modern convolutional neural networks (CNNs) efficient...
research
∙
04/29/2021
Condensation-Net: Memory-Efficient Network Architecture with Cross-Channel Pooling Layers and Virtual Feature Maps
"Lightweight convolutional neural networks" is an important research top...
research
∙
02/15/2021
The Role of Momentum Parameters in the Optimal Convergence of Adaptive Polyak's Heavy-ball Methods
The adaptive stochastic gradient descent (SGD) with momentum has been wi...
research
∙
02/08/2021
Datasets and Evaluation for Simultaneous Localization and Mapping Related Problems: A Comprehensive Survey
Simultaneous Localization and Mapping (SLAM) has found an increasing uti...
research
∙
12/29/2020
Gradient Descent Averaging and Primal-dual Averaging for Strongly Convex Optimization
Averaging scheme has attracted extensive attention in deep learning as w...
research
∙
09/29/2020
BAMSProd: A Step towards Generalizing the Adaptive Optimization Methods to Deep Binary Model
Recent methods have significantly reduced the performance degradation of...
research
∙
09/10/2020
QuantNet: Learning to Quantize by Learning within Fully Differentiable Framework
Despite the achievements of recent binarization methods on reducing the ...
research
∙
11/19/2019
IFQ-Net: Integrated Fixed-point Quantization Networks for Embedded Vision
Deploying deep models on embedded devices has been a challenging problem...
research
∙
11/13/2019
DupNet: Towards Very Tiny Quantized CNN with Improved Accuracy for Face Detection
Deploying deep learning based face detectors on edge devices is a challe...
research
∙
11/13/2019
